SYMBOL INDEX (14415 symbols across 1363 files)

FILE: demo/autoaug/hub_fitter.py
  class HubFitterClassifer (line 27) | class HubFitterClassifer(object):
    method __init__ (line 30) | def __init__(self, hparams: dict) -> None:
    method _fit_param (line 80) | def _fit_param(self, show: bool = False) -> None:
    method _get_label_info (line 92) | def _get_label_info(self, hparams: dict) -> None:
    method reset_config (line 111) | def reset_config(self, new_hparams: dict) -> None:
    method save_model (line 124) | def save_model(self, checkpoint_dir: str, step: Optional[str] = None) ...
    method extract_model_spec (line 137) | def extract_model_spec(self, checkpoint_path: str) -> None:
    method eval_child_model (line 143) | def eval_child_model(self, mode: str, pass_id: int = 0) -> dict:
    method train_one_epoch (line 165) | def train_one_epoch(self, pass_id: int) -> dict:
    method _run_training_loop (line 195) | def _run_training_loop(self, curr_epoch: int) -> dict:
    method _compute_final_accuracies (line 202) | def _compute_final_accuracies(self, iteration: int) -> dict:
    method run_model (line 215) | def run_model(self, epoch: int) -> dict:

FILE: demo/autoaug/paddlehub_utils/reader.py
  class PbaAugment (line 41) | class PbaAugment(object):
    method __init__ (line 46) | def __init__(self,
    method set_epoch (line 80) | def set_epoch(self, indx: int) -> None:
    method reset_policy (line 91) | def reset_policy(self, new_hparams: dict) -> None:
    method __call__ (line 102) | def __call__(self, img: np.ndarray):
  class PicRecord (line 120) | class PicRecord(object):
    method __init__ (line 125) | def __init__(self, row: list) -> None:
    method sub_path (line 134) | def sub_path(self) -> str:
    method label (line 143) | def label(self) -> str:
  class PicReader (line 152) | class PicReader(paddle.io.Dataset):
    method __init__ (line 157) | def __init__(self,
    method _get_all_img (line 191) | def _get_all_img(self, **kwargs) -> None:
    method _load_image (line 218) | def _load_image(self, directory: str) -> np.ndarray:
    method _parse_list (line 242) | def _parse_list(self, **kwargs) -> None:
    method __getitem__ (line 271) | def __getitem__(self, index: int):
    method get (line 284) | def get(self, record: PicRecord) -> tuple:
    method __len__ (line 321) | def __len__(self) -> int:
    method set_meta (line 329) | def set_meta(self, meta: bool) -> None:
    method set_epoch (line 340) | def set_epoch(self, epoch: int) -> None:
    method reset_policy (line 353) | def reset_policy(self, new_hparams: dict) -> None:
  function _parse (line 366) | def _parse(value: str, function: callable, fmt: str) -> None:
  function _read_classes (line 380) | def _read_classes(csv_file: str) -> dict:
  function _init_loader (line 400) | def _init_loader(hparams: dict, TrainTransform=None) -> tuple:

FILE: demo/autoaug/paddlehub_utils/trainer.py
  class CustomTrainer (line 23) | class CustomTrainer(Trainer):
    method __init__ (line 25) | def __init__(self, **kwargs) -> None:
    method init_train_and_eval (line 28) | def init_train_and_eval(self,
    method init_train (line 39) | def init_train(self, train_dataset: paddle.io.Dataset, batch_size: int...
    method train_one_epoch (line 55) | def train_one_epoch(self, loader: paddle.io.DataLoader, timer: Timer, ...
    method train (line 95) | def train(self,
    method init_evaluate (line 153) | def init_evaluate(self, eval_dataset: paddle.io.Dataset, batch_size: i...
    method evaluate_process (line 170) | def evaluate_process(self, loader: paddle.io.DataLoader) -> dict:
    method evaluate (line 205) | def evaluate(self, eval_dataset: paddle.io.Dataset, batch_size: int = ...

FILE: demo/autoaug/search.py
  function main (line 22) | def main():
  function search_test (line 26) | def search_test():

FILE: demo/serving/module_serving/object_detection_pyramidbox_lite_server_mask/pyramidbox_lite_server_mask_serving_demo.py
  function cv2_to_base64 (line 8) | def cv2_to_base64(image):

FILE: demo/text_classification/embedding/model.py
  class BoWModel (line 30) | class BoWModel(nn.Layer):
    method __init__ (line 45) | def __init__(self,
    method training_step (line 72) | def training_step(self, batch: List[paddle.Tensor], batch_idx: int):
    method validation_step (line 86) | def validation_step(self, batch: List[paddle.Tensor], batch_idx: int):
    method forward (line 100) | def forward(self, ids: paddle.Tensor, labels: paddle.Tensor = None):
    method _batchify (line 126) | def _batchify(self, data: List[List[str]], max_seq_len: int, batch_siz...
    method predict (line 150) | def predict(

FILE: docs/conf.py
  function setup (line 80) | def setup(app):

FILE: modules/audio/asr/deepspeech2_aishell/deepspeech_tester.py
  class DeepSpeech2Tester (line 28) | class DeepSpeech2Tester:
    method __init__ (line 29) | def __init__(self, config):
    method compute_result_transcripts (line 34) | def compute_result_transcripts(self, audio, audio_len, vocab_list, cfg):
    method test (line 54) | def test(self, audio_file):
    method setup_model (line 67) | def setup_model(self):
    method resume (line 76) | def resume(self, checkpoint):

FILE: modules/audio/asr/deepspeech2_aishell/module.py
  class DeepSpeech2 (line 49) | class DeepSpeech2(paddle.nn.Layer):
    method __init__ (line 50) | def __init__(self):
    method check_audio (line 82) | def check_audio(audio_file):
    method speech_recognize (line 87) | def speech_recognize(self, audio_file, device='cpu'):

FILE: modules/audio/asr/deepspeech2_librispeech/deepspeech_tester.py
  class DeepSpeech2Tester (line 28) | class DeepSpeech2Tester:
    method __init__ (line 29) | def __init__(self, config):
    method compute_result_transcripts (line 34) | def compute_result_transcripts(self, audio, audio_len, vocab_list, cfg):
    method test (line 54) | def test(self, audio_file):
    method setup_model (line 67) | def setup_model(self):
    method resume (line 76) | def resume(self, checkpoint):

FILE: modules/audio/asr/deepspeech2_librispeech/module.py
  class DeepSpeech2 (line 50) | class DeepSpeech2(paddle.nn.Layer):
    method __init__ (line 51) | def __init__(self):
    method check_audio (line 83) | def check_audio(audio_file):
    method speech_recognize (line 88) | def speech_recognize(self, audio_file, device='cpu'):

FILE: modules/audio/asr/u2_conformer_aishell/module.py
  class U2Conformer (line 35) | class U2Conformer(paddle.nn.Layer):
    method __init__ (line 36) | def __init__(self):
    method check_audio (line 63) | def check_audio(audio_file):
    method speech_recognize (line 68) | def speech_recognize(self, audio_file, device='cpu'):

FILE: modules/audio/asr/u2_conformer_aishell/u2_conformer_tester.py
  class U2ConformerTester (line 27) | class U2ConformerTester:
    method __init__ (line 28) | def __init__(self, config):
    method test (line 36) | def test(self, audio_file):
    method setup_model (line 67) | def setup_model(self):
    method resume (line 75) | def resume(self, checkpoint):

FILE: modules/audio/asr/u2_conformer_librispeech/module.py
  class U2Conformer (line 36) | class U2Conformer(paddle.nn.Layer):
    method __init__ (line 37) | def __init__(self):
    method check_audio (line 64) | def check_audio(audio_file):
    method speech_recognize (line 69) | def speech_recognize(self, audio_file, device='cpu'):

FILE: modules/audio/asr/u2_conformer_librispeech/u2_conformer_tester.py
  class U2ConformerTester (line 27) | class U2ConformerTester:
    method __init__ (line 28) | def __init__(self, config):
    method test (line 36) | def test(self, audio_file):
    method setup_model (line 67) | def setup_model(self):
    method resume (line 75) | def resume(self, checkpoint):

FILE: modules/audio/asr/u2_conformer_wenetspeech/module.py
  class U2Conformer (line 26) | class U2Conformer(paddle.nn.Layer):
    method __init__ (line 27) | def __init__(self):
    method check_audio (line 39) | def check_audio(audio_file):
    method speech_recognize (line 52) | def speech_recognize(self, audio_file, device='cpu'):

FILE: modules/audio/audio_classification/PANNs/cnn10/module.py
  class PANN (line 38) | class PANN(nn.Layer):
    method __init__ (line 39) | def __init__(
    method forward (line 72) | def forward(self, feats, labels=None):

FILE: modules/audio/audio_classification/PANNs/cnn10/network.py
  class ConvBlock (line 24) | class ConvBlock(nn.Layer):
    method __init__ (line 25) | def __init__(self, in_channels, out_channels):
    method forward (line 45) | def forward(self, x, pool_size=(2, 2), pool_type='avg'):
  class CNN10 (line 66) | class CNN10(nn.Layer):
    method __init__ (line 69) | def __init__(self, extract_embedding: bool = True, checkpoint: str = N...
    method forward (line 90) | def forward(self, x):

FILE: modules/audio/audio_classification/PANNs/cnn14/module.py
  class PANN (line 38) | class PANN(nn.Layer):
    method __init__ (line 39) | def __init__(
    method forward (line 72) | def forward(self, feats, labels=None):

FILE: modules/audio/audio_classification/PANNs/cnn14/network.py
  class ConvBlock (line 24) | class ConvBlock(nn.Layer):
    method __init__ (line 25) | def __init__(self, in_channels, out_channels):
    method forward (line 45) | def forward(self, x, pool_size=(2, 2), pool_type='avg'):
  class CNN14 (line 66) | class CNN14(nn.Layer):
    method __init__ (line 69) | def __init__(self, extract_embedding: bool = True, checkpoint: str = N...
    method forward (line 92) | def forward(self, x):

FILE: modules/audio/audio_classification/PANNs/cnn6/module.py
  class PANN (line 38) | class PANN(nn.Layer):
    method __init__ (line 39) | def __init__(
    method forward (line 72) | def forward(self, feats, labels=None):

FILE: modules/audio/audio_classification/PANNs/cnn6/network.py
  class ConvBlock5x5 (line 24) | class ConvBlock5x5(nn.Layer):
    method __init__ (line 25) | def __init__(self, in_channels, out_channels):
    method forward (line 37) | def forward(self, x, pool_size=(2, 2), pool_type='avg'):
  class CNN6 (line 54) | class CNN6(nn.Layer):
    method __init__ (line 57) | def __init__(self, extract_embedding: bool = True, checkpoint: str = N...
    method forward (line 78) | def forward(self, x):

FILE: modules/audio/keyword_spotting/kwmlp_speech_commands/feature.py
  function create_dct (line 21) | def create_dct(n_mfcc: int, n_mels: int, norm: str = 'ortho'):
  function compute_mfcc (line 34) | def compute_mfcc(

FILE: modules/audio/keyword_spotting/kwmlp_speech_commands/kwmlp.py
  class Residual (line 19) | class Residual(nn.Layer):
    method __init__ (line 20) | def __init__(self, fn):
    method forward (line 24) | def forward(self, x):
  class PreNorm (line 28) | class PreNorm(nn.Layer):
    method __init__ (line 29) | def __init__(self, dim, fn):
    method forward (line 34) | def forward(self, x, **kwargs):
  class PostNorm (line 39) | class PostNorm(nn.Layer):
    method __init__ (line 40) | def __init__(self, dim, fn):
    method forward (line 45) | def forward(self, x, **kwargs):
  class SpatialGatingUnit (line 49) | class SpatialGatingUnit(nn.Layer):
    method __init__ (line 50) | def __init__(self, dim, dim_seq, act=nn.Identity(), init_eps=1e-3):
    method forward (line 61) | def forward(self, x):
  class gMLPBlock (line 71) | class gMLPBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self, *, dim, dim_ff, seq_len, act=nn.Identity()):
    method forward (line 79) | def forward(self, x):
  class Rearrange (line 86) | class Rearrange(nn.Layer):
    method __init__ (line 87) | def __init__(self):
    method forward (line 90) | def forward(self, x):
  class Reduce (line 95) | class Reduce(nn.Layer):
    method __init__ (line 96) | def __init__(self, axis=1):
    method forward (line 100) | def forward(self, x):
  class KW_MLP (line 105) | class KW_MLP(nn.Layer):
    method __init__ (line 108) | def __init__(self,
    method forward (line 139) | def forward(self, x):

FILE: modules/audio/keyword_spotting/kwmlp_speech_commands/module.py
  class KWS (line 33) | class KWS(paddle.nn.Layer):
    method __init__ (line 34) | def __init__(self):
    method load_audio (line 59) | def load_audio(self, wav):
    method keyword_recognize (line 65) | def keyword_recognize(self, wav):
    method forward (line 79) | def forward(self, x):

FILE: modules/audio/language_identification/ecapa_tdnn_common_language/ecapa_tdnn.py
  function length_to_mask (line 22) | def length_to_mask(length, max_len=None, dtype=None):
  class Conv1d (line 36) | class Conv1d(nn.Layer):
    method __init__ (line 37) | def __init__(
    method forward (line 68) | def forward(self, x):
    method _manage_padding (line 76) | def _manage_padding(self, x, kernel_size: int, dilation: int, stride: ...
    method _get_padding_elem (line 82) | def _get_padding_elem(self, L_in: int, stride: int, kernel_size: int, ...
  class BatchNorm1d (line 95) | class BatchNorm1d(nn.Layer):
    method __init__ (line 96) | def __init__(
    method forward (line 118) | def forward(self, x):
  class TDNNBlock (line 123) | class TDNNBlock(nn.Layer):
    method __init__ (line 124) | def __init__(
    method forward (line 142) | def forward(self, x):
  class Res2NetBlock (line 146) | class Res2NetBlock(nn.Layer):
    method __init__ (line 147) | def __init__(self, in_channels, out_channels, scale=8, dilation=1):
    method forward (line 159) | def forward(self, x):
  class SEBlock (line 173) | class SEBlock(nn.Layer):
    method __init__ (line 174) | def __init__(self, in_channels, se_channels, out_channels):
    method forward (line 182) | def forward(self, x, lengths=None):
  class AttentiveStatisticsPooling (line 198) | class AttentiveStatisticsPooling(nn.Layer):
    method __init__ (line 199) | def __init__(self, channels, attention_channels=128, global_context=Tr...
    method forward (line 211) | def forward(self, x, lengths=None):
  class SERes2NetBlock (line 253) | class SERes2NetBlock(nn.Layer):
    method __init__ (line 254) | def __init__(
    method forward (line 291) | def forward(self, x, lengths=None):
  class ECAPA_TDNN (line 304) | class ECAPA_TDNN(nn.Layer):
    method __init__ (line 305) | def __init__(
    method forward (line 372) | def forward(self, x, lengths=None):
  class Classifier (line 395) | class Classifier(nn.Layer):
    method __init__ (line 396) | def __init__(self, backbone, num_class, dtype=paddle.float32):
    method forward (line 402) | def forward(self, x):

FILE: modules/audio/language_identification/ecapa_tdnn_common_language/feature.py
  function compute_fbank_matrix (line 23) | def compute_fbank_matrix(sample_rate: int = 16000,
  function compute_log_fbank (line 51) | def compute_log_fbank(
  function compute_stats (line 84) | def compute_stats(x: paddle.Tensor, mean_norm: bool = True, std_norm: bo...
  function normalize (line 100) | def normalize(

FILE: modules/audio/language_identification/ecapa_tdnn_common_language/module.py
  class LanguageIdentification (line 38) | class LanguageIdentification(paddle.nn.Layer):
    method __init__ (line 39) | def __init__(self):
    method load_audio (line 65) | def load_audio(self, wav):
    method language_identify (line 71) | def language_identify(self, wav):
    method forward (line 77) | def forward(self, x):

FILE: modules/audio/speaker_recognition/ecapa_tdnn_voxceleb/ecapa_tdnn.py
  function length_to_mask (line 22) | def length_to_mask(length, max_len=None, dtype=None):
  class Conv1d (line 36) | class Conv1d(nn.Layer):
    method __init__ (line 37) | def __init__(
    method forward (line 68) | def forward(self, x):
    method _manage_padding (line 76) | def _manage_padding(self, x, kernel_size: int, dilation: int, stride: ...
    method _get_padding_elem (line 82) | def _get_padding_elem(self, L_in: int, stride: int, kernel_size: int, ...
  class BatchNorm1d (line 95) | class BatchNorm1d(nn.Layer):
    method __init__ (line 96) | def __init__(
    method forward (line 118) | def forward(self, x):
  class TDNNBlock (line 123) | class TDNNBlock(nn.Layer):
    method __init__ (line 124) | def __init__(
    method forward (line 142) | def forward(self, x):
  class Res2NetBlock (line 146) | class Res2NetBlock(nn.Layer):
    method __init__ (line 147) | def __init__(self, in_channels, out_channels, scale=8, dilation=1):
    method forward (line 159) | def forward(self, x):
  class SEBlock (line 173) | class SEBlock(nn.Layer):
    method __init__ (line 174) | def __init__(self, in_channels, se_channels, out_channels):
    method forward (line 182) | def forward(self, x, lengths=None):
  class AttentiveStatisticsPooling (line 198) | class AttentiveStatisticsPooling(nn.Layer):
    method __init__ (line 199) | def __init__(self, channels, attention_channels=128, global_context=Tr...
    method forward (line 211) | def forward(self, x, lengths=None):
  class SERes2NetBlock (line 253) | class SERes2NetBlock(nn.Layer):
    method __init__ (line 254) | def __init__(
    method forward (line 291) | def forward(self, x, lengths=None):
  class ECAPA_TDNN (line 304) | class ECAPA_TDNN(nn.Layer):
    method __init__ (line 305) | def __init__(
    method forward (line 372) | def forward(self, x, lengths=None):

FILE: modules/audio/speaker_recognition/ecapa_tdnn_voxceleb/feature.py
  function compute_fbank_matrix (line 23) | def compute_fbank_matrix(sample_rate: int = 16000,
  function compute_log_fbank (line 51) | def compute_log_fbank(
  function compute_stats (line 84) | def compute_stats(x: paddle.Tensor, mean_norm: bool = True, std_norm: bo...
  function normalize (line 100) | def normalize(

FILE: modules/audio/speaker_recognition/ecapa_tdnn_voxceleb/module.py
  class SpeakerRecognition (line 37) | class SpeakerRecognition(paddle.nn.Layer):
    method __init__ (line 38) | def __init__(self, threshold=0.25):
    method load_audio (line 63) | def load_audio(self, wav):
    method speaker_embedding (line 69) | def speaker_embedding(self, wav):
    method speaker_verify (line 74) | def speaker_verify(self, wav1, wav2):
    method forward (line 84) | def forward(self, x):

FILE: modules/audio/svs/diffsinger/infer.py
  class Infer (line 15) | class Infer:
    method __init__ (line 17) | def __init__(self, root='.', providers=None):
    method model (line 55) | def model(self, txt_tokens, **kwargs):
    method norm_spec (line 131) | def norm_spec(self, x):
    method denorm_spec (line 134) | def denorm_spec(self, x):
    method forward_model (line 137) | def forward_model(self, inp):
    method run_vocoder (line 164) | def run_vocoder(self, c, **kwargs):
    method preprocess_word_level_input (line 179) | def preprocess_word_level_input(self, inp):
    method preprocess_phoneme_level_input (line 249) | def preprocess_phoneme_level_input(self, inp):
    method preprocess_input (line 263) | def preprocess_input(self, inp, input_type='word'):
    method input_to_batch (line 315) | def input_to_batch(self, item):
    method infer_once (line 340) | def infer_once(self, inp):

FILE: modules/audio/svs/diffsinger/inference/svs/opencpop/map.py
  function cpop_pinyin2ph_func (line 1) | def cpop_pinyin2ph_func(path):

FILE: modules/audio/svs/diffsinger/module.py
  class DiffSinger (line 23) | class DiffSinger:
    method __init__ (line 25) | def __init__(self, providers: List[str] = None) -> None:
    method singing_voice_synthesis (line 32) | def singing_voice_synthesis(self,
    method run_cmd (line 65) | def run_cmd(self, argvs: List[str]) -> str:

FILE: modules/audio/svs/diffsinger/test.py
  class TestHubModule (line 7) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 10) | def setUpClass(cls) -> None:
    method tearDownClass (line 14) | def tearDownClass(cls) -> None:
    method test_singing_voice_synthesis1 (line 17) | def test_singing_voice_synthesis1(self):
    method test_singing_voice_synthesis2 (line 35) | def test_singing_voice_synthesis2(self):

FILE: modules/audio/svs/diffsinger/utils/__init__.py
  class AvgrageMeter (line 8) | class AvgrageMeter(object):
    method __init__ (line 10) | def __init__(self):
    method reset (line 13) | def reset(self):
    method update (line 18) | def update(self, val, n=1):
  function collate_1d (line 24) | def collate_1d(values, pad_idx=0, left_pad=False, shift_right=False, max...
  function collate_2d (line 42) | def collate_2d(values, pad_idx=0, left_pad=False, shift_right=False, max...
  function _is_batch_full (line 59) | def _is_batch_full(batch, num_tokens, max_tokens, max_sentences):
  function batch_by_size (line 69) | def batch_by_size(indices,
  function unpack_dict_to_list (line 125) | def unpack_dict_to_list(samples):
  function remove_padding (line 139) | def remove_padding(x, padding_idx=0):
  class Timer (line 149) | class Timer:
    method __init__ (line 152) | def __init__(self, name, print_time=False):
    method __enter__ (line 158) | def __enter__(self):
    method __exit__ (line 161) | def __exit__(self, exc_type, exc_val, exc_tb):

FILE: modules/audio/svs/diffsinger/utils/audio.py
  function save_wav (line 13) | def save_wav(wav, path, sr, norm=False):
  function get_hop_size (line 21) | def get_hop_size(hparams):
  function _stft (line 30) | def _stft(y, hparams):
  function _istft (line 38) | def _istft(y, hparams):
  function librosa_pad_lr (line 42) | def librosa_pad_lr(x, fsize, fshift, pad_sides=1):
  function amp_to_db (line 55) | def amp_to_db(x):
  function normalize (line 59) | def normalize(S, hparams):

FILE: modules/audio/svs/diffsinger/utils/cwt.py
  function load_wav (line 7) | def load_wav(wav_file, sr):
  function convert_continuos_f0 (line 12) | def convert_continuos_f0(f0):
  function get_cont_lf0 (line 46) | def get_cont_lf0(f0, frame_period=5.0):
  function get_lf0_cwt (line 53) | def get_lf0_cwt(lf0):
  function norm_scale (line 72) | def norm_scale(Wavelet_lf0):
  function normalize_cwt_lf0 (line 80) | def normalize_cwt_lf0(f0, mean, std):
  function get_lf0_cwt_norm (line 89) | def get_lf0_cwt_norm(f0s, mean, std):
  function inverse_cwt (line 118) | def inverse_cwt(Wavelet_lf0, scales):

FILE: modules/audio/svs/diffsinger/utils/hparams.py
  class Args (line 10) | class Args:
    method __init__ (line 12) | def __init__(self, **kwargs):
  function override_config (line 17) | def override_config(old_config: dict, new_config: dict):
  function set_hparams (line 25) | def set_hparams(config='', exp_name='', hparams_str='', print_hparams=Tr...

FILE: modules/audio/svs/diffsinger/utils/multiprocess_utils.py
  function chunked_worker (line 7) | def chunked_worker(worker_id, map_func, args, results_queue=None, init_c...
  function chunked_multiprocess_run (line 21) | def chunked_multiprocess_run(map_func, args, num_workers=None, ordered=T...

FILE: modules/audio/svs/diffsinger/utils/text_encoder.py
  function strip_ids (line 28) | def strip_ids(ids, ids_to_strip):
  class TextEncoder (line 36) | class TextEncoder(object):
    method __init__ (line 39) | def __init__(self, num_reserved_ids=NUM_RESERVED_TOKENS):
    method num_reserved_ids (line 43) | def num_reserved_ids(self):
    method encode (line 46) | def encode(self, s):
    method decode (line 62) | def decode(self, ids, strip_extraneous=False):
    method decode_list (line 79) | def decode_list(self, ids):
    method vocab_size (line 101) | def vocab_size(self):
  class ByteTextEncoder (line 105) | class ByteTextEncoder(TextEncoder):
    method encode (line 108) | def encode(self, s):
    method decode (line 112) | def decode(self, ids, strip_extraneous=False):
    method decode_list (line 128) | def decode_list(self, ids):
    method vocab_size (line 141) | def vocab_size(self):
  class ByteTextEncoderWithEos (line 145) | class ByteTextEncoderWithEos(ByteTextEncoder):
    method encode (line 148) | def encode(self, s):
  class TokenTextEncoder (line 152) | class TokenTextEncoder(TextEncoder):
    method __init__ (line 155) | def __init__(self,
    method encode (line 192) | def encode(self, s):
    method decode (line 201) | def decode(self, ids, strip_eos=False, strip_padding=False):
    method decode_list (line 210) | def decode_list(self, ids):
    method vocab_size (line 215) | def vocab_size(self):
    method __len__ (line 218) | def __len__(self):
    method _safe_id_to_token (line 221) | def _safe_id_to_token(self, idx):
    method _init_vocab_from_file (line 224) | def _init_vocab_from_file(self, filename):
    method _init_vocab_from_list (line 239) | def _init_vocab_from_list(self, vocab_list):
    method _init_vocab (line 256) | def _init_vocab(self, token_generator, add_reserved_tokens=True):
    method pad (line 271) | def pad(self):
    method eos (line 274) | def eos(self):
    method unk (line 277) | def unk(self):
    method seg (line 280) | def seg(self):
    method store_to_file (line 283) | def store_to_file(self, filename):
    method sil_phonemes (line 296) | def sil_phonemes(self):

FILE: modules/audio/svs/diffsinger/utils/text_norm.py
  class ChineseChar (line 61) | class ChineseChar(object):
    method __init__ (line 69) | def __init__(self, simplified, traditional):
    method __str__ (line 74) | def __str__(self):
    method __repr__ (line 77) | def __repr__(self):
  class ChineseNumberUnit (line 81) | class ChineseNumberUnit(ChineseChar):
    method __init__ (line 88) | def __init__(self, power, simplified, traditional, big_s, big_t):
    method __str__ (line 94) | def __str__(self):
    method create (line 98) | def create(cls, index, value, numbering_type=NUMBERING_TYPES[1], small...
  class ChineseNumberDigit (line 128) | class ChineseNumberDigit(ChineseChar):
    method __init__ (line 133) | def __init__(self, value, simplified, traditional, big_s, big_t, alt_s...
    method __str__ (line 141) | def __str__(self):
    method create (line 145) | def create(cls, i, v):
  class ChineseMath (line 149) | class ChineseMath(ChineseChar):
    method __init__ (line 154) | def __init__(self, simplified, traditional, symbol, expression=None):
  class NumberSystem (line 165) | class NumberSystem(object):
  class MathSymbol (line 172) | class MathSymbol(object):
    method __init__ (line 180) | def __init__(self, positive, negative, point):
    method __iter__ (line 185) | def __iter__(self):
  function create_system (line 206) | def create_system(numbering_type=NUMBERING_TYPES[1]):
  function chn2num (line 242) | def chn2num(chinese_string, numbering_type=NUMBERING_TYPES[1]):
  function num2chn (line 326) | def num2chn(number_string,
  class Cardinal (line 427) | class Cardinal:
    method __init__ (line 432) | def __init__(self, cardinal=None, chntext=None):
    method chntext2cardinal (line 436) | def chntext2cardinal(self):
    method cardinal2chntext (line 439) | def cardinal2chntext(self):
  class Digit (line 443) | class Digit:
    method __init__ (line 448) | def __init__(self, digit=None, chntext=None):
    method digit2chntext (line 455) | def digit2chntext(self):
  class TelePhone (line 459) | class TelePhone:
    method __init__ (line 464) | def __init__(self, telephone=None, raw_chntext=None, chntext=None):
    method telephone2chntext (line 476) | def telephone2chntext(self, fixed=False):
  class Fraction (line 489) | class Fraction:
    method __init__ (line 494) | def __init__(self, fraction=None, chntext=None):
    method chntext2fraction (line 498) | def chntext2fraction(self):
    method fraction2chntext (line 502) | def fraction2chntext(self):
  class Date (line 507) | class Date:
    method __init__ (line 512) | def __init__(self, date=None, chntext=None):
    method date2chntext (line 540) | def date2chntext(self):
  class Money (line 565) | class Money:
    method __init__ (line 570) | def __init__(self, money=None, chntext=None):
    method money2chntext (line 577) | def money2chntext(self):
  class Percentage (line 588) | class Percentage:
    method __init__ (line 593) | def __init__(self, percentage=None, chntext=None):
    method chntext2percentage (line 597) | def chntext2percentage(self):
    method percentage2chntext (line 600) | def percentage2chntext(self):
  class NSWNormalizer (line 607) | class NSWNormalizer:
    method __init__ (line 609) | def __init__(self, raw_text):
    method _particular (line 613) | def _particular(self):
    method normalize (line 624) | def normalize(self, remove_punc=True):
  function nsw_test_case (line 717) | def nsw_test_case(raw_text):
  function nsw_test (line 723) | def nsw_test():

FILE: modules/audio/tts/deepvoice3_ljspeech/module.py
  class AttrDict (line 68) | class AttrDict(dict):
    method __init__ (line 69) | def __init__(self, *args, **kwargs):
  class WaveflowVocoder (line 74) | class WaveflowVocoder(object):
    method __init__ (line 75) | def __init__(self, config_path, checkpoint_path):
    method __call__ (line 86) | def __call__(self, mel):
  class GriffinLimVocoder (line 94) | class GriffinLimVocoder(object):
    method __init__ (line 95) | def __init__(self, sharpening_factor=1.4, sample_rate=22050, n_fft=102...
    method __call__ (line 102) | def __call__(self, mel):
  class DeepVoice3 (line 118) | class DeepVoice3(hub.NLPPredictionModule):
    method _initialize (line 119) | def _initialize(self):
    method synthesize (line 183) | def synthesize(self, texts, use_gpu=False, vocoder="griffin-lim"):
    method serving_method (line 248) | def serving_method(self, texts, use_gpu=False, vocoder="griffin-lim"):
    method add_module_config_arg (line 257) | def add_module_config_arg(self):
    method add_module_output_arg (line 267) | def add_module_output_arg(self):
    method run_cmd (line 278) | def run_cmd(self, argvs):

FILE: modules/audio/tts/fastspeech2_baker/module.py
  class FastSpeech (line 36) | class FastSpeech(paddle.nn.Layer):
    method __init__ (line 37) | def __init__(self, output_dir='./wavs'):
    method forward (line 96) | def forward(self, text: str):
    method generate (line 112) | def generate(self, sentences: List[str], device='cpu'):

FILE: modules/audio/tts/fastspeech2_ljspeech/module.py
  class FastSpeech (line 36) | class FastSpeech(paddle.nn.Layer):
    method __init__ (line 37) | def __init__(self, output_dir='./wavs'):
    method forward (line 101) | def forward(self, text: str):
    method generate (line 117) | def generate(self, sentences: List[str], device='cpu'):

FILE: modules/audio/tts/fastspeech_ljspeech/module.py
  class AttrDict (line 68) | class AttrDict(dict):
    method __init__ (line 69) | def __init__(self, *args, **kwargs):
  class FastSpeech (line 83) | class FastSpeech(hub.NLPPredictionModule):
    method _initialize (line 84) | def _initialize(self):
    method synthesize (line 107) | def synthesize(self, texts, use_gpu=False, speed=1.0, vocoder="griffin...
    method synthesis_with_griffinlim (line 164) | def synthesis_with_griffinlim(self, mel_output, cfg):
    method synthesis_with_waveflow (line 176) | def synthesis_with_waveflow(self, mel_output, sigma):
    method serving_method (line 189) | def serving_method(self, texts, use_gpu=False, speed=1.0, vocoder="gri...
    method add_module_config_arg (line 198) | def add_module_config_arg(self):
    method add_module_output_arg (line 208) | def add_module_output_arg(self):
    method run_cmd (line 219) | def run_cmd(self, argvs):

FILE: modules/audio/tts/transformer_tts_ljspeech/module.py
  class AttrDict (line 69) | class AttrDict(dict):
    method __init__ (line 70) | def __init__(self, *args, **kwargs):
  class TransformerTTS (line 84) | class TransformerTTS(hub.NLPPredictionModule):
    method _initialize (line 85) | def _initialize(self):
    method synthesize (line 120) | def synthesize(self, texts, use_gpu=False, vocoder="griffin-lim"):
    method synthesis_with_griffinlim (line 181) | def synthesis_with_griffinlim(self, mel_output, cfg):
    method synthesis_with_waveflow (line 193) | def synthesis_with_waveflow(self, mel_output, sigma):
    method serving_method (line 206) | def serving_method(self, texts, use_gpu=False, vocoder="griffin-lim"):
    method add_module_config_arg (line 215) | def add_module_config_arg(self):
    method add_module_output_arg (line 225) | def add_module_output_arg(self):
    method run_cmd (line 236) | def run_cmd(self, argvs):

FILE: modules/audio/voice_cloning/ge2e_fastspeech2_pwgan/module.py
  class VoiceCloner (line 45) | class VoiceCloner(paddle.nn.Layer):
    method __init__ (line 46) | def __init__(self, speaker_audio: str = None, output_dir: str = './'):
    method get_speaker_embedding (line 127) | def get_speaker_embedding(self):
    method set_speaker_embedding (line 131) | def set_speaker_embedding(self, speaker_audio: str):
    method generate (line 140) | def generate(self, data: Union[str, List[str]], use_gpu: bool = False):

FILE: modules/audio/voice_cloning/lstm_tacotron2/audio_processor.py
  function normalize_volume (line 32) | def normalize_volume(wav, target_dBFS, increase_only=False, decrease_onl...
  function trim_long_silences (line 49) | def trim_long_silences(wav, vad_window_length: int, vad_moving_average_w...
  function compute_partial_slices (line 92) | def compute_partial_slices(n_samples: int,
  class SpeakerVerificationPreprocessor (line 148) | class SpeakerVerificationPreprocessor(object):
    method __init__ (line 149) | def __init__(self,
    method preprocess_wav (line 176) | def preprocess_wav(self, fpath_or_wav, source_sr=None):
    method melspectrogram (line 196) | def melspectrogram(self, wav):
    method extract_mel_partials (line 202) | def extract_mel_partials(self, wav):

FILE: modules/audio/voice_cloning/lstm_tacotron2/chinese_g2p.py
  function convert_to_pinyin (line 21) | def convert_to_pinyin(text: str) -> List[str]:
  function convert_sentence (line 29) | def convert_sentence(text: str) -> List[Tuple[str]]:

FILE: modules/audio/voice_cloning/lstm_tacotron2/module.py
  class VoiceCloner (line 43) | class VoiceCloner(nn.Layer):
    method __init__ (line 44) | def __init__(self, speaker_audio: str = None, output_dir: str = './'):
    method get_speaker_embedding (line 119) | def get_speaker_embedding(self):
    method set_speaker_embedding (line 122) | def set_speaker_embedding(self, speaker_audio: str):
    method forward (line 129) | def forward(self, phones: paddle.Tensor, tones: paddle.Tensor, speaker...
    method _convert_text_to_input (line 135) | def _convert_text_to_input(self, text: str):
    method _batchify (line 144) | def _batchify(self, data: List[str], batch_size: int):
    method generate (line 170) | def generate(self, data: List[str], batch_size: int = 1, use_gpu: bool...

FILE: modules/audio/voice_cloning/lstm_tacotron2/preprocess_transcription.py
  function is_zh (line 108) | def is_zh(word):
  function ernized (line 114) | def ernized(syllable):
  function convert (line 118) | def convert(syllable):
  function split_syllable (line 148) | def split_syllable(syllable: str):

FILE: modules/demo/senta_test/module.py
  class SentaTest (line 18) | class SentaTest:
    method __init__ (line 19) | def __init__(self):
    method sentiment_classify (line 29) | def sentiment_classify(self, texts):
    method run_cmd (line 42) | def run_cmd(self, argvs):

FILE: modules/demo/senta_test/processor.py
  function load_vocab (line 1) | def load_vocab(vocab_path):

FILE: modules/image/Image_editing/colorization/deoldify/base_module.py
  class SequentialEx (line 10) | class SequentialEx(nn.Layer):
    method __init__ (line 13) | def __init__(self, *layers):
    method forward (line 17) | def forward(self, x):
    method __getitem__ (line 28) | def __getitem__(self, i):
    method append (line 31) | def append(self, l):
    method extend (line 34) | def extend(self, l):
    method insert (line 37) | def insert(self, i, l):
  class Deoldify (line 41) | class Deoldify(SequentialEx):
    method __init__ (line 43) | def __init__(self,
  function custom_conv_layer (line 107) | def custom_conv_layer(ni: int,
  function relu (line 145) | def relu(inplace: bool = False, leaky: float = None):
  class UnetBlockWide (line 150) | class UnetBlockWide(nn.Layer):
    method __init__ (line 153) | def __init__(self,
    method forward (line 172) | def forward(self, up_in):
  class UnetBlockDeep (line 182) | class UnetBlockDeep(nn.Layer):
    method __init__ (line 185) | def __init__(
    method forward (line 206) | def forward(self, up_in):
  function ifnone (line 216) | def ifnone(a, b):
  class PixelShuffle_ICNR (line 221) | class PixelShuffle_ICNR(nn.Layer):
    method __init__ (line 225) | def __init__(self,
    method forward (line 242) | def forward(self, x):
  function conv_layer (line 247) | def conv_layer(ni: int,
  class CustomPixelShuffle_ICNR (line 279) | class CustomPixelShuffle_ICNR(nn.Layer):
    method __init__ (line 283) | def __init__(self, ni: int, nf: int = None, scale: int = 2, blur: bool...
    method forward (line 294) | def forward(self, x):
  class MergeLayer (line 299) | class MergeLayer(nn.Layer):
    method __init__ (line 302) | def __init__(self, dense: bool = False):
    method forward (line 307) | def forward(self, x):
  function res_block (line 313) | def res_block(nf, dense: bool = False, norm_type='Batch', bottle: bool =...
  class SigmoidRange (line 322) | class SigmoidRange(nn.Layer):
    method __init__ (line 325) | def __init__(self, low, high):
    method forward (line 329) | def forward(self, x):
  function sigmoid_range (line 333) | def sigmoid_range(x, low, high):
  class PixelShuffle (line 338) | class PixelShuffle(nn.Layer):
    method __init__ (line 340) | def __init__(self, upscale_factor):
    method forward (line 344) | def forward(self, x):
  class ReplicationPad2d (line 348) | class ReplicationPad2d(nn.Layer):
    method __init__ (line 350) | def __init__(self, size):
    method forward (line 354) | def forward(self, x):
  function conv1d (line 358) | def conv1d(ni: int, no: int, ks: int = 1, stride: int = 1, padding: int ...
  class SelfAttention (line 364) | class SelfAttention(nn.Layer):
    method __init__ (line 367) | def __init__(self, n_channels):
    method forward (line 375) | def forward(self, x):
  function _get_sfs_idxs (line 386) | def _get_sfs_idxs(sizes):
  function build_model (line 395) | def build_model():

FILE: modules/image/Image_editing/colorization/deoldify/module.py
  class DeOldifyPredictor (line 37) | class DeOldifyPredictor(nn.Layer):
    method __init__ (line 39) | def __init__(self, render_factor: int = 32, output_path: int = 'output...
    method norm (line 59) | def norm(self, img, render_factor=32, render_base=16):
    method denorm (line 72) | def denorm(self, img):
    method post_process (line 82) | def post_process(self, raw_color, orig):
    method run_image (line 92) | def run_image(self, img):
    method run_video (line 111) | def run_video(self, video):
    method predict (line 144) | def predict(self, input):
    method serving_method (line 158) | def serving_method(self, images, **kwargs):
    method create_gradio_app (line 167) | def create_gradio_app(self):

FILE: modules/image/Image_editing/colorization/deoldify/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_run_image1 (line 32) | def test_run_image1(self):
    method test_run_image2 (line 36) | def test_run_image2(self):
    method test_run_image3 (line 40) | def test_run_image3(self):
    method test_predict1 (line 43) | def test_predict1(self):
    method test_predict2 (line 48) | def test_predict2(self):

FILE: modules/image/Image_editing/colorization/deoldify/utils.py
  function cv2_to_base64 (line 12) | def cv2_to_base64(image):
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function is_listy (line 24) | def is_listy(x):
  class Hook (line 28) | class Hook():
    method __init__ (line 31) | def __init__(self, m, hook_func, is_forward=True, detach=True):
    method hook_fn (line 37) | def hook_fn(self, module, input, output):
    method remove (line 44) | def remove(self):
    method __enter__ (line 50) | def __enter__(self, *args):
    method __exit__ (line 53) | def __exit__(self, *args):
  class Hooks (line 57) | class Hooks():
    method __init__ (line 60) | def __init__(self, ms, hook_func, is_forward=True, detach=True):
    method __getitem__ (line 68) | def __getitem__(self, i: int) -> Hook:
    method __len__ (line 71) | def __len__(self) -> int:
    method __iter__ (line 74) | def __iter__(self):
    method stored (line 78) | def stored(self):
    method remove (line 81) | def remove(self):
    method __enter__ (line 86) | def __enter__(self, *args):
    method __exit__ (line 89) | def __exit__(self, *args):
  function _hook_inner (line 93) | def _hook_inner(m, i, o):
  function hook_output (line 97) | def hook_output(module, detach=True, grad=False):
  function hook_outputs (line 102) | def hook_outputs(modules, detach=True, grad=False):
  function model_sizes (line 107) | def model_sizes(m, size=(64, 64)):
  function dummy_eval (line 114) | def dummy_eval(m, size=(64, 64)):
  function dummy_batch (line 120) | def dummy_batch(size=(64, 64), ch_in=3):
  class _SpectralNorm (line 126) | class _SpectralNorm(nn.SpectralNorm):
    method __init__ (line 128) | def __init__(self, weight_shape, dim=0, power_iters=1, eps=1e-12, dtyp...
    method forward (line 131) | def forward(self, weight):
  class Spectralnorm (line 149) | class Spectralnorm(paddle.nn.Layer):
    method __init__ (line 151) | def __init__(self, layer, dim=0, power_iters=1, eps=1e-12, dtype='floa...
    method forward (line 163) | def forward(self, x):
  function video2frames (line 170) | def video2frames(video_path, outpath, **kargs):
  function frames2video (line 200) | def frames2video(frame_path, video_path, r):
  function is_image (line 211) | def is_image(input):

FILE: modules/image/Image_editing/colorization/photo_restoration/module.py
  class PhotoRestoreModel (line 32) | class PhotoRestoreModel(nn.Layer):
    method __init__ (line 41) | def __init__(self, visualization: bool = False):
    method run_image (line 47) | def run_image(self,
    method serving_method (line 75) | def serving_method(self, images, model_select):

FILE: modules/image/Image_editing/colorization/photo_restoration/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_run_image1 (line 31) | def test_run_image1(self):
    method test_run_image2 (line 37) | def test_run_image2(self):
    method test_run_image3 (line 43) | def test_run_image3(self):

FILE: modules/image/Image_editing/colorization/photo_restoration/utils.py
  function cv2_to_base64 (line 6) | def cv2_to_base64(image):
  function base64_to_cv2 (line 11) | def base64_to_cv2(b64str):

FILE: modules/image/Image_editing/colorization/user_guided_colorization/data_feed.py
  class ColorizeHint (line 5) | class ColorizeHint:
    method __init__ (line 22) | def __init__(self, percent: float, num_points: int = None, samp: str =...
    method __call__ (line 28) | def __call__(self, data: np.ndarray, hint: np.ndarray, mask: np.ndarray):
  class ColorizePreprocess (line 69) | class ColorizePreprocess:
    method __init__ (line 85) | def __init__(self,
    method __call__ (line 98) | def __call__(self, data_lab):

FILE: modules/image/Image_editing/colorization/user_guided_colorization/module.py
  class UserGuidedColorization (line 34) | class UserGuidedColorization(nn.Layer):
    method __init__ (line 44) | def __init__(self, use_tanh: bool = True, load_checkpoint: str = None):
    method transforms (line 186) | def transforms(self, images: str) -> callable:
    method set_config (line 191) | def set_config(self, classification: bool = True, prob: float = 1., nu...
    method preprocess (line 195) | def preprocess(self, inputs: paddle.Tensor):
    method forward (line 199) | def forward(self,

FILE: modules/image/Image_editing/colorization/user_guided_colorization/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_predict1 (line 31) | def test_predict1(self):
    method test_predict2 (line 46) | def test_predict2(self):
    method test_predict3 (line 61) | def test_predict3(self):
    method test_predict4 (line 76) | def test_predict4(self):

FILE: modules/image/Image_editing/enhancement/fbcnn_color/fbcnn.py
  function sequential (line 13) | def sequential(*args):
  function conv (line 37) | def conv(in_channels=64,
  class ResBlock (line 99) | class ResBlock(nn.Layer):
    method __init__ (line 101) | def __init__(self,
    method forward (line 118) | def forward(self, x):
  function upsample_pixelshuffle (line 126) | def upsample_pixelshuffle(in_channels=64,
  function upsample_upconv (line 149) | def upsample_upconv(in_channels=64,
  function upsample_convtranspose (line 172) | def upsample_convtranspose(in_channels=64,
  function downsample_strideconv (line 203) | def downsample_strideconv(in_channels=64,
  function downsample_maxpool (line 222) | def downsample_maxpool(in_channels=64,
  function downsample_avgpool (line 249) | def downsample_avgpool(in_channels=64,
  class QFAttention (line 273) | class QFAttention(nn.Layer):
    method __init__ (line 275) | def __init__(self,
    method forward (line 292) | def forward(self, x, gamma, beta):
  class FBCNN (line 299) | class FBCNN(nn.Layer):
    method __init__ (line 301) | def __init__(self,
    method forward (line 378) | def forward(self, x, qf_input=None):

FILE: modules/image/Image_editing/enhancement/fbcnn_color/module.py
  function cv2_to_base64 (line 18) | def cv2_to_base64(image):
  function base64_to_cv2 (line 23) | def base64_to_cv2(b64str):
  class FBCNNColor (line 38) | class FBCNNColor(nn.Layer):
    method __init__ (line 40) | def __init__(self):
    method preprocess (line 48) | def preprocess(self, img: np.ndarray) -> np.ndarray:
    method postprocess (line 54) | def postprocess(self, img: np.ndarray) -> np.ndarray:
    method artifacts_removal (line 61) | def artifacts_removal(self,
    method run_cmd (line 97) | def run_cmd(self, argvs):
    method serving_method (line 119) | def serving_method(self, image, **kwargs):

FILE: modules/image/Image_editing/enhancement/fbcnn_color/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_artifacts_removal1 (line 32) | def test_artifacts_removal1(self):
    method test_artifacts_removal2 (line 37) | def test_artifacts_removal2(self):
    method test_artifacts_removal3 (line 44) | def test_artifacts_removal3(self):
    method test_artifacts_removal4 (line 51) | def test_artifacts_removal4(self):
    method test_artifacts_removal5 (line 54) | def test_artifacts_removal5(self):

FILE: modules/image/Image_editing/enhancement/fbcnn_gray/fbcnn.py
  function sequential (line 13) | def sequential(*args):
  function conv (line 37) | def conv(in_channels=64,
  class ResBlock (line 99) | class ResBlock(nn.Layer):
    method __init__ (line 101) | def __init__(self,
    method forward (line 118) | def forward(self, x):
  function upsample_pixelshuffle (line 126) | def upsample_pixelshuffle(in_channels=64,
  function upsample_upconv (line 149) | def upsample_upconv(in_channels=64,
  function upsample_convtranspose (line 172) | def upsample_convtranspose(in_channels=64,
  function downsample_strideconv (line 203) | def downsample_strideconv(in_channels=64,
  function downsample_maxpool (line 222) | def downsample_maxpool(in_channels=64,
  function downsample_avgpool (line 249) | def downsample_avgpool(in_channels=64,
  class QFAttention (line 273) | class QFAttention(nn.Layer):
    method __init__ (line 275) | def __init__(self,
    method forward (line 292) | def forward(self, x, gamma, beta):
  class FBCNN (line 299) | class FBCNN(nn.Layer):
    method __init__ (line 301) | def __init__(self,
    method forward (line 378) | def forward(self, x, qf_input=None):

FILE: modules/image/Image_editing/enhancement/fbcnn_gray/module.py
  function cv2_to_base64 (line 18) | def cv2_to_base64(image):
  function base64_to_cv2 (line 23) | def base64_to_cv2(b64str):
  class FBCNNGary (line 38) | class FBCNNGary(nn.Layer):
    method __init__ (line 40) | def __init__(self):
    method preprocess (line 48) | def preprocess(self, img: np.ndarray) -> np.ndarray:
    method postprocess (line 53) | def postprocess(self, img: np.ndarray) -> np.ndarray:
    method artifacts_removal (line 58) | def artifacts_removal(self,
    method run_cmd (line 94) | def run_cmd(self, argvs):
    method serving_method (line 116) | def serving_method(self, image, **kwargs):

FILE: modules/image/Image_editing/enhancement/fbcnn_gray/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_artifacts_removal1 (line 32) | def test_artifacts_removal1(self):
    method test_artifacts_removal2 (line 37) | def test_artifacts_removal2(self):
    method test_artifacts_removal3 (line 44) | def test_artifacts_removal3(self):
    method test_artifacts_removal4 (line 51) | def test_artifacts_removal4(self):
    method test_artifacts_removal5 (line 54) | def test_artifacts_removal5(self):

FILE: modules/image/Image_editing/super_resolution/dcscn/data_feed.py
  function reader (line 13) | def reader(images=None, paths=None):

FILE: modules/image/Image_editing/super_resolution/dcscn/module.py
  class Dcscn (line 38) | class Dcscn:
    method __init__ (line 39) | def __init__(self):
    method _set_config (line 43) | def _set_config(self):
    method reconstruct (line 66) | def reconstruct(self, images=None, paths=None, use_gpu=False, visualiz...
    method serving_method (line 128) | def serving_method(self, images, **kwargs):
    method run_cmd (line 138) | def run_cmd(self, argvs):
    method add_module_config_arg (line 162) | def add_module_config_arg(self):
    method add_module_input_arg (line 175) | def add_module_input_arg(self):

FILE: modules/image/Image_editing/super_resolution/dcscn/processor.py
  function cv2_to_base64 (line 12) | def cv2_to_base64(image):
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function postprocess (line 24) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 61) | def check_dir(dir_path):
  function get_save_image_name (line 69) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/Image_editing/super_resolution/dcscn/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_reconstruct1 (line 32) | def test_reconstruct1(self):
    method test_reconstruct2 (line 40) | def test_reconstruct2(self):
    method test_reconstruct3 (line 48) | def test_reconstruct3(self):
    method test_reconstruct4 (line 56) | def test_reconstruct4(self):
    method test_reconstruct5 (line 64) | def test_reconstruct5(self):
    method test_reconstruct6 (line 71) | def test_reconstruct6(self):
    method test_save_inference_model (line 78) | def test_save_inference_model(self):

FILE: modules/image/Image_editing/super_resolution/falsr_a/data_feed.py
  function reader (line 11) | def reader(images=None, paths=None):

FILE: modules/image/Image_editing/super_resolution/falsr_a/module.py
  class Falsr_A (line 38) | class Falsr_A:
    method __init__ (line 40) | def __init__(self):
    method _set_config (line 44) | def _set_config(self):
    method reconstruct (line 67) | def reconstruct(self, images=None, paths=None, use_gpu=False, visualiz...
    method serving_method (line 124) | def serving_method(self, images, **kwargs):
    method run_cmd (line 134) | def run_cmd(self, argvs):
    method add_module_config_arg (line 159) | def add_module_config_arg(self):
    method add_module_input_arg (line 180) | def add_module_input_arg(self):
    method create_gradio_app (line 186) | def create_gradio_app(self):

FILE: modules/image/Image_editing/super_resolution/falsr_a/processor.py
  function cv2_to_base64 (line 11) | def cv2_to_base64(image):
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function postprocess (line 23) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 58) | def check_dir(dir_path):
  function get_save_image_name (line 66) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/Image_editing/super_resolution/falsr_a/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_reconstruct1 (line 33) | def test_reconstruct1(self):
    method test_reconstruct2 (line 37) | def test_reconstruct2(self):
    method test_reconstruct3 (line 41) | def test_reconstruct3(self):
    method test_reconstruct4 (line 45) | def test_reconstruct4(self):
    method test_reconstruct5 (line 49) | def test_reconstruct5(self):
    method test_reconstruct6 (line 52) | def test_reconstruct6(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/Image_editing/super_resolution/falsr_b/data_feed.py
  function reader (line 11) | def reader(images=None, paths=None):

FILE: modules/image/Image_editing/super_resolution/falsr_b/module.py
  class Falsr_B (line 38) | class Falsr_B:
    method __init__ (line 40) | def __init__(self):
    method _set_config (line 44) | def _set_config(self):
    method reconstruct (line 67) | def reconstruct(self, images=None, paths=None, use_gpu=False, visualiz...
    method serving_method (line 124) | def serving_method(self, images, **kwargs):
    method run_cmd (line 134) | def run_cmd(self, argvs):
    method add_module_config_arg (line 159) | def add_module_config_arg(self):
    method add_module_input_arg (line 180) | def add_module_input_arg(self):
    method create_gradio_app (line 186) | def create_gradio_app(self):

FILE: modules/image/Image_editing/super_resolution/falsr_b/processor.py
  function cv2_to_base64 (line 11) | def cv2_to_base64(image):
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function postprocess (line 23) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 58) | def check_dir(dir_path):
  function get_save_image_name (line 66) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/Image_editing/super_resolution/falsr_b/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_reconstruct1 (line 33) | def test_reconstruct1(self):
    method test_reconstruct2 (line 37) | def test_reconstruct2(self):
    method test_reconstruct3 (line 41) | def test_reconstruct3(self):
    method test_reconstruct4 (line 45) | def test_reconstruct4(self):
    method test_reconstruct5 (line 49) | def test_reconstruct5(self):
    method test_reconstruct6 (line 52) | def test_reconstruct6(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/Image_editing/super_resolution/falsr_c/data_feed.py
  function reader (line 11) | def reader(images=None, paths=None):

FILE: modules/image/Image_editing/super_resolution/falsr_c/module.py
  class Falsr_C (line 39) | class Falsr_C:
    method __init__ (line 41) | def __init__(self):
    method _set_config (line 45) | def _set_config(self):
    method reconstruct (line 68) | def reconstruct(self, images=None, paths=None, use_gpu=False, visualiz...
    method serving_method (line 125) | def serving_method(self, images, **kwargs):
    method run_cmd (line 135) | def run_cmd(self, argvs):
    method add_module_config_arg (line 160) | def add_module_config_arg(self):
    method add_module_input_arg (line 181) | def add_module_input_arg(self):
    method create_gradio_app (line 187) | def create_gradio_app(self):

FILE: modules/image/Image_editing/super_resolution/falsr_c/processor.py
  function cv2_to_base64 (line 11) | def cv2_to_base64(image):
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function postprocess (line 23) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 58) | def check_dir(dir_path):
  function get_save_image_name (line 66) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/Image_editing/super_resolution/falsr_c/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_reconstruct1 (line 33) | def test_reconstruct1(self):
    method test_reconstruct2 (line 37) | def test_reconstruct2(self):
    method test_reconstruct3 (line 41) | def test_reconstruct3(self):
    method test_reconstruct4 (line 45) | def test_reconstruct4(self):
    method test_reconstruct5 (line 49) | def test_reconstruct5(self):
    method test_reconstruct6 (line 52) | def test_reconstruct6(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/Image_editing/super_resolution/realsr/module.py
  class RealSRPredictor (line 36) | class RealSRPredictor(nn.Layer):
    method __init__ (line 37) | def __init__(self, output='output', weight_path=None, load_checkpoint:...
    method norm (line 58) | def norm(self, img):
    method denorm (line 62) | def denorm(self, img):
    method run_image (line 66) | def run_image(self, img):
    method run_video (line 85) | def run_video(self, video):
    method predict (line 119) | def predict(self, input):
    method serving_method (line 140) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_editing/super_resolution/realsr/rrdb.py
  class Registry (line 7) | class Registry(object):
    method __init__ (line 23) | def __init__(self, name):
    method _do_register (line 32) | def _do_register(self, name, obj):
    method register (line 38) | def register(self, obj=None, name=None):
    method get (line 58) | def get(self, name):
  class ResidualDenseBlock_5C (line 66) | class ResidualDenseBlock_5C(nn.Layer):
    method __init__ (line 67) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 77) | def forward(self, x):
  class RRDB (line 86) | class RRDB(nn.Layer):
    method __init__ (line 88) | def __init__(self, nf, gc=32):
    method forward (line 94) | def forward(self, x):
  function make_layer (line 101) | def make_layer(block, n_layers):
  class RRDBNet (line 110) | class RRDBNet(nn.Layer):
    method __init__ (line 111) | def __init__(self, in_nc, out_nc, nf, nb, gc=32):
    method forward (line 126) | def forward(self, x):

FILE: modules/image/Image_editing/super_resolution/realsr/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_run_image1 (line 31) | def test_run_image1(self):
    method test_run_image2 (line 37) | def test_run_image2(self):
    method test_run_image3 (line 43) | def test_run_image3(self):
    method test_predict1 (line 50) | def test_predict1(self):
    method test_predict2 (line 57) | def test_predict2(self):

FILE: modules/image/Image_editing/super_resolution/realsr/utils.py
  function video2frames (line 10) | def video2frames(video_path, outpath, **kargs):
  function frames2video (line 39) | def frames2video(frame_path, video_path, r):
  function is_image (line 52) | def is_image(input):
  function cv2_to_base64 (line 61) | def cv2_to_base64(image):
  function base64_to_cv2 (line 66) | def base64_to_cv2(b64str):

FILE: modules/image/Image_editing/super_resolution/swin2sr_real_sr_x4/module.py
  function cv2_to_base64 (line 18) | def cv2_to_base64(image):
  function base64_to_cv2 (line 23) | def base64_to_cv2(b64str):
  class SwinIRMRealSR (line 38) | class SwinIRMRealSR(nn.Layer):
    method __init__ (line 40) | def __init__(self):
    method preprocess (line 59) | def preprocess(self, img: np.ndarray) -> np.ndarray:
    method postprocess (line 65) | def postprocess(self, img: np.ndarray) -> np.ndarray:
    method real_sr (line 72) | def real_sr(self,
    method run_cmd (line 104) | def run_cmd(self, argvs):
    method serving_method (line 122) | def serving_method(self, image, **kwargs):

FILE: modules/image/Image_editing/super_resolution/swin2sr_real_sr_x4/swin2sr.py
  function _ntuple (line 11) | def _ntuple(n):
  class Mlp (line 24) | class Mlp(nn.Layer):
    method __init__ (line 26) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 35) | def forward(self, x):
  function window_partition (line 44) | def window_partition(x, window_size):
  function window_reverse (line 58) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 74) | class WindowAttention(nn.Layer):
    method __init__ (line 87) | def __init__(self,
    method forward (line 159) | def forward(self, x, mask=None):
    method extra_repr (line 203) | def extra_repr(self) -> str:
    method flops (line 207) | def flops(self, N):
  class SwinTransformerBlock (line 221) | class SwinTransformerBlock(nn.Layer):
    method __init__ (line 239) | def __init__(self,
    method calculate_mask (line 288) | def calculate_mask(self, x_size):
    method forward (line 317) | def forward(self, x, x_size):
    method extra_repr (line 361) | def extra_repr(self) -> str:
    method flops (line 365) | def flops(self):
  class PatchMerging (line 380) | class PatchMerging(nn.Layer):
    method __init__ (line 388) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
    method forward (line 395) | def forward(self, x):
    method extra_repr (line 418) | def extra_repr(self) -> str:
    method flops (line 421) | def flops(self):
  class BasicLayer (line 428) | class BasicLayer(nn.Layer):
    method __init__ (line 447) | def __init__(self,
    method forward (line 491) | def forward(self, x, x_size):
    method extra_repr (line 498) | def extra_repr(self) -> str:
    method flops (line 501) | def flops(self):
  class PatchEmbed (line 510) | class PatchEmbed(nn.Layer):
    method __init__ (line 520) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 539) | def forward(self, x):
    method flops (line 549) | def flops(self):
  class RSTB (line 558) | class RSTB(nn.Layer):
    method __init__ (line 579) | def __init__(self,
    method forward (line 635) | def forward(self, x, x_size):
    method flops (line 638) | def flops(self):
  class PatchUnEmbed (line 649) | class PatchUnEmbed(nn.Layer):
    method __init__ (line 659) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 672) | def forward(self, x, x_size):
    method flops (line 677) | def flops(self):
  class Upsample (line 682) | class Upsample(nn.Sequential):
    method __init__ (line 689) | def __init__(self, scale, num_feat):
  class Upsample_hf (line 704) | class Upsample_hf(nn.Sequential):
    method __init__ (line 711) | def __init__(self, scale, num_feat):
  class UpsampleOneStep (line 726) | class UpsampleOneStep(nn.Sequential):
    method __init__ (line 734) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
    method flops (line 742) | def flops(self):
  class Swin2SR (line 748) | class Swin2SR(nn.Layer):
    method __init__ (line 774) | def __init__(self,
    method check_image_size (line 951) | def check_image_size(self, x):
    method forward_features (line 958) | def forward_features(self, x):
    method forward_features_hf (line 973) | def forward_features_hf(self, x):
    method forward (line 988) | def forward(self, x):
    method flops (line 1059) | def flops(self):

FILE: modules/image/Image_editing/super_resolution/swin2sr_real_sr_x4/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_real_sr1 (line 35) | def test_real_sr1(self):
    method test_real_sr2 (line 40) | def test_real_sr2(self):
    method test_real_sr3 (line 45) | def test_real_sr3(self):
    method test_real_sr4 (line 50) | def test_real_sr4(self):
    method test_real_sr5 (line 53) | def test_real_sr5(self):

FILE: modules/image/Image_editing/super_resolution/swinir_l_real_sr_x4/module.py
  function cv2_to_base64 (line 18) | def cv2_to_base64(image):
  function base64_to_cv2 (line 23) | def base64_to_cv2(b64str):
  class SwinIRMRealSR (line 38) | class SwinIRMRealSR(nn.Layer):
    method __init__ (line 40) | def __init__(self):
    method preprocess (line 59) | def preprocess(self, img: np.ndarray) -> np.ndarray:
    method postprocess (line 65) | def postprocess(self, img: np.ndarray) -> np.ndarray:
    method real_sr (line 72) | def real_sr(self,
    method run_cmd (line 104) | def run_cmd(self, argvs):
    method serving_method (line 122) | def serving_method(self, image, **kwargs):

FILE: modules/image/Image_editing/super_resolution/swinir_l_real_sr_x4/swinir.py
  function to_2tuple (line 8) | def to_2tuple(x):
  class Mlp (line 15) | class Mlp(nn.Layer):
    method __init__ (line 17) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 26) | def forward(self, x):
  function window_partition (line 35) | def window_partition(x, window_size):
  function window_reverse (line 49) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 65) | class WindowAttention(nn.Layer):
    method __init__ (line 78) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 113) | def forward(self, x, mask=None):
    method extra_repr (line 147) | def extra_repr(self) -> str:
    method flops (line 150) | def flops(self, N):
  class SwinTransformerBlock (line 164) | class SwinTransformerBlock(nn.Layer):
    method __init__ (line 182) | def __init__(self,
    method calculate_mask (line 230) | def calculate_mask(self, x_size):
    method forward (line 257) | def forward(self, x, x_size):
    method extra_repr (line 299) | def extra_repr(self) -> str:
    method flops (line 303) | def flops(self):
  class PatchMerging (line 318) | class PatchMerging(nn.Layer):
    method __init__ (line 326) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
    method forward (line 333) | def forward(self, x):
    method extra_repr (line 356) | def extra_repr(self) -> str:
    method flops (line 359) | def flops(self):
  class BasicLayer (line 366) | class BasicLayer(nn.Layer):
    method __init__ (line 385) | def __init__(self,
    method forward (line 429) | def forward(self, x, x_size):
    method extra_repr (line 436) | def extra_repr(self) -> str:
    method flops (line 439) | def flops(self):
  class RSTB (line 448) | class RSTB(nn.Layer):
    method __init__ (line 470) | def __init__(self,
    method forward (line 528) | def forward(self, x, x_size):
    method flops (line 531) | def flops(self):
  class PatchEmbed (line 542) | class PatchEmbed(nn.Layer):
    method __init__ (line 552) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 570) | def forward(self, x):
    method flops (line 576) | def flops(self):
  class PatchUnEmbed (line 584) | class PatchUnEmbed(nn.Layer):
    method __init__ (line 594) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 607) | def forward(self, x, x_size):
    method flops (line 612) | def flops(self):
  class Upsample (line 617) | class Upsample(nn.Sequential):
    method __init__ (line 624) | def __init__(self, scale, num_feat):
  class UpsampleOneStep (line 639) | class UpsampleOneStep(nn.Sequential):
    method __init__ (line 647) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
    method flops (line 655) | def flops(self):
  class SwinIR (line 661) | class SwinIR(nn.Layer):
    method __init__ (line 688) | def __init__(self,
    method _init_weights (line 827) | def _init_weights(self, m):
    method check_image_size (line 835) | def check_image_size(self, x):
    method forward_features (line 842) | def forward_features(self, x):
    method forward (line 857) | def forward(self, x):
    method flops (line 894) | def flops(self):

FILE: modules/image/Image_editing/super_resolution/swinir_l_real_sr_x4/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_real_sr1 (line 35) | def test_real_sr1(self):
    method test_real_sr2 (line 40) | def test_real_sr2(self):
    method test_real_sr3 (line 45) | def test_real_sr3(self):
    method test_real_sr4 (line 50) | def test_real_sr4(self):
    method test_real_sr5 (line 53) | def test_real_sr5(self):

FILE: modules/image/Image_editing/super_resolution/swinir_m_real_sr_x2/module.py
  function cv2_to_base64 (line 18) | def cv2_to_base64(image):
  function base64_to_cv2 (line 23) | def base64_to_cv2(b64str):
  class SwinIRMRealSR (line 38) | class SwinIRMRealSR(nn.Layer):
    method __init__ (line 40) | def __init__(self):
    method preprocess (line 59) | def preprocess(self, img: np.ndarray) -> np.ndarray:
    method postprocess (line 65) | def postprocess(self, img: np.ndarray) -> np.ndarray:
    method real_sr (line 72) | def real_sr(self,
    method run_cmd (line 104) | def run_cmd(self, argvs):
    method serving_method (line 122) | def serving_method(self, image, **kwargs):

FILE: modules/image/Image_editing/super_resolution/swinir_m_real_sr_x2/swinir.py
  function to_2tuple (line 8) | def to_2tuple(x):
  class Mlp (line 15) | class Mlp(nn.Layer):
    method __init__ (line 17) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 26) | def forward(self, x):
  function window_partition (line 35) | def window_partition(x, window_size):
  function window_reverse (line 49) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 65) | class WindowAttention(nn.Layer):
    method __init__ (line 78) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 113) | def forward(self, x, mask=None):
    method extra_repr (line 147) | def extra_repr(self) -> str:
    method flops (line 150) | def flops(self, N):
  class SwinTransformerBlock (line 164) | class SwinTransformerBlock(nn.Layer):
    method __init__ (line 182) | def __init__(self,
    method calculate_mask (line 230) | def calculate_mask(self, x_size):
    method forward (line 257) | def forward(self, x, x_size):
    method extra_repr (line 299) | def extra_repr(self) -> str:
    method flops (line 303) | def flops(self):
  class PatchMerging (line 318) | class PatchMerging(nn.Layer):
    method __init__ (line 326) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
    method forward (line 333) | def forward(self, x):
    method extra_repr (line 356) | def extra_repr(self) -> str:
    method flops (line 359) | def flops(self):
  class BasicLayer (line 366) | class BasicLayer(nn.Layer):
    method __init__ (line 385) | def __init__(self,
    method forward (line 429) | def forward(self, x, x_size):
    method extra_repr (line 436) | def extra_repr(self) -> str:
    method flops (line 439) | def flops(self):
  class RSTB (line 448) | class RSTB(nn.Layer):
    method __init__ (line 470) | def __init__(self,
    method forward (line 528) | def forward(self, x, x_size):
    method flops (line 531) | def flops(self):
  class PatchEmbed (line 542) | class PatchEmbed(nn.Layer):
    method __init__ (line 552) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 570) | def forward(self, x):
    method flops (line 576) | def flops(self):
  class PatchUnEmbed (line 584) | class PatchUnEmbed(nn.Layer):
    method __init__ (line 594) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 607) | def forward(self, x, x_size):
    method flops (line 612) | def flops(self):
  class Upsample (line 617) | class Upsample(nn.Sequential):
    method __init__ (line 624) | def __init__(self, scale, num_feat):
  class UpsampleOneStep (line 639) | class UpsampleOneStep(nn.Sequential):
    method __init__ (line 647) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
    method flops (line 655) | def flops(self):
  class SwinIR (line 661) | class SwinIR(nn.Layer):
    method __init__ (line 688) | def __init__(self,
    method _init_weights (line 827) | def _init_weights(self, m):
    method check_image_size (line 835) | def check_image_size(self, x):
    method forward_features (line 842) | def forward_features(self, x):
    method forward (line 857) | def forward(self, x):
    method flops (line 894) | def flops(self):

FILE: modules/image/Image_editing/super_resolution/swinir_m_real_sr_x2/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_real_sr1 (line 35) | def test_real_sr1(self):
    method test_real_sr2 (line 40) | def test_real_sr2(self):
    method test_real_sr3 (line 45) | def test_real_sr3(self):
    method test_real_sr4 (line 50) | def test_real_sr4(self):
    method test_real_sr5 (line 53) | def test_real_sr5(self):

FILE: modules/image/Image_editing/super_resolution/swinir_m_real_sr_x4/module.py
  function cv2_to_base64 (line 18) | def cv2_to_base64(image):
  function base64_to_cv2 (line 23) | def base64_to_cv2(b64str):
  class SwinIRMRealSR (line 38) | class SwinIRMRealSR(nn.Layer):
    method __init__ (line 40) | def __init__(self):
    method preprocess (line 59) | def preprocess(self, img: np.ndarray) -> np.ndarray:
    method postprocess (line 65) | def postprocess(self, img: np.ndarray) -> np.ndarray:
    method real_sr (line 72) | def real_sr(self,
    method run_cmd (line 104) | def run_cmd(self, argvs):
    method serving_method (line 122) | def serving_method(self, image, **kwargs):

FILE: modules/image/Image_editing/super_resolution/swinir_m_real_sr_x4/swinir.py
  function to_2tuple (line 8) | def to_2tuple(x):
  class Mlp (line 15) | class Mlp(nn.Layer):
    method __init__ (line 17) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 26) | def forward(self, x):
  function window_partition (line 35) | def window_partition(x, window_size):
  function window_reverse (line 49) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 65) | class WindowAttention(nn.Layer):
    method __init__ (line 78) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 113) | def forward(self, x, mask=None):
    method extra_repr (line 147) | def extra_repr(self) -> str:
    method flops (line 150) | def flops(self, N):
  class SwinTransformerBlock (line 164) | class SwinTransformerBlock(nn.Layer):
    method __init__ (line 182) | def __init__(self,
    method calculate_mask (line 230) | def calculate_mask(self, x_size):
    method forward (line 257) | def forward(self, x, x_size):
    method extra_repr (line 299) | def extra_repr(self) -> str:
    method flops (line 303) | def flops(self):
  class PatchMerging (line 318) | class PatchMerging(nn.Layer):
    method __init__ (line 326) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
    method forward (line 333) | def forward(self, x):
    method extra_repr (line 356) | def extra_repr(self) -> str:
    method flops (line 359) | def flops(self):
  class BasicLayer (line 366) | class BasicLayer(nn.Layer):
    method __init__ (line 385) | def __init__(self,
    method forward (line 429) | def forward(self, x, x_size):
    method extra_repr (line 436) | def extra_repr(self) -> str:
    method flops (line 439) | def flops(self):
  class RSTB (line 448) | class RSTB(nn.Layer):
    method __init__ (line 470) | def __init__(self,
    method forward (line 528) | def forward(self, x, x_size):
    method flops (line 531) | def flops(self):
  class PatchEmbed (line 542) | class PatchEmbed(nn.Layer):
    method __init__ (line 552) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 570) | def forward(self, x):
    method flops (line 576) | def flops(self):
  class PatchUnEmbed (line 584) | class PatchUnEmbed(nn.Layer):
    method __init__ (line 594) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 607) | def forward(self, x, x_size):
    method flops (line 612) | def flops(self):
  class Upsample (line 617) | class Upsample(nn.Sequential):
    method __init__ (line 624) | def __init__(self, scale, num_feat):
  class UpsampleOneStep (line 639) | class UpsampleOneStep(nn.Sequential):
    method __init__ (line 647) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
    method flops (line 655) | def flops(self):
  class SwinIR (line 661) | class SwinIR(nn.Layer):
    method __init__ (line 688) | def __init__(self,
    method _init_weights (line 827) | def _init_weights(self, m):
    method check_image_size (line 835) | def check_image_size(self, x):
    method forward_features (line 842) | def forward_features(self, x):
    method forward (line 857) | def forward(self, x):
    method flops (line 894) | def flops(self):

FILE: modules/image/Image_editing/super_resolution/swinir_m_real_sr_x4/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_real_sr1 (line 35) | def test_real_sr1(self):
    method test_real_sr2 (line 40) | def test_real_sr2(self):
    method test_real_sr3 (line 45) | def test_real_sr3(self):
    method test_real_sr4 (line 50) | def test_real_sr4(self):
    method test_real_sr5 (line 53) | def test_real_sr5(self):

FILE: modules/image/Image_gan/gan/first_order_motion/model.py
  class FirstOrderPredictor (line 34) | class FirstOrderPredictor:
    method __init__ (line 35) | def __init__(self,
    method read_img (line 111) | def read_img(self, path):
    method run (line 120) | def run(self, source_image, driving_video, ratio, image_size, output_d...
    method load_checkpoints (line 212) | def load_checkpoints(self, config, checkpoint_path):
    method make_animation (line 229) | def make_animation(self,
    method find_best_frame_func (line 274) | def find_best_frame_func(self, source, driving):
    method extract_bbox (line 299) | def extract_bbox(self, image):
    method IOU (line 342) | def IOU(self, ax1, ay1, ax2, ay2, sa, bx1, by1, bx2, by2, sb):

FILE: modules/image/Image_gan/gan/first_order_motion/module.py
  class FirstOrderMotion (line 32) | class FirstOrderMotion:
    method __init__ (line 33) | def __init__(self):
    method generate (line 37) | def generate(self,
    method run_cmd (line 63) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 88) | def add_module_config_arg(self):
    method add_module_input_arg (line 98) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/gan/photopen/model.py
  class PhotoPenPredictor (line 26) | class PhotoPenPredictor:
    method __init__ (line 27) | def __init__(self, weight_path, gen_cfg):
    method run (line 50) | def run(self, image):

FILE: modules/image/Image_gan/gan/photopen/module.py
  class Photopen (line 36) | class Photopen:
    method __init__ (line 37) | def __init__(self):
    method photo_transfer (line 42) | def photo_transfer(self,
    method run_cmd (line 86) | def run_cmd(self, argvs: list):
    method serving_method (line 110) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 119) | def add_module_config_arg(self):
    method add_module_input_arg (line 129) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/gan/photopen/util.py
  function base64_to_cv2 (line 7) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/gan/pixel2style2pixel/model.py
  function run_alignment (line 69) | def run_alignment(image):
  class AttrDict (line 148) | class AttrDict(dict):
    method __init__ (line 149) | def __init__(self, *args, **kwargs):
  class Pixel2Style2PixelPredictor (line 154) | class Pixel2Style2PixelPredictor:
    method __init__ (line 155) | def __init__(self,
    method run (line 195) | def run(self, image):

FILE: modules/image/Image_gan/gan/pixel2style2pixel/module.py
  class pixel2style2pixel (line 38) | class pixel2style2pixel:
    method __init__ (line 39) | def __init__(self):
    method style_transfer (line 44) | def style_transfer(self,
    method run_cmd (line 90) | def run_cmd(self, argvs: list):
    method serving_method (line 114) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 123) | def add_module_config_arg(self):
    method add_module_input_arg (line 133) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/gan/pixel2style2pixel/util.py
  function base64_to_cv2 (line 6) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/gan/stgan_bald/data_feed.py
  function reader (line 12) | def reader(images=None, paths=None, org_labels=None, target_labels=None):

FILE: modules/image/Image_gan/gan/stgan_bald/module.py
  function check_attribute_conflict (line 26) | def check_attribute_conflict(label_batch):
  class StganBald (line 50) | class StganBald:
    method __init__ (line 51) | def __init__(self):
    method _set_config (line 56) | def _set_config(self):
    method bald (line 83) | def bald(self,
    method serving_method (line 172) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/gan/stgan_bald/processor.py
  function cv2_to_base64 (line 12) | def cv2_to_base64(image):
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function postprocess (line 24) | def postprocess(data_out,
  function check_dir (line 64) | def check_dir(dir_path):
  function get_save_image_name (line 72) | def get_save_image_name(org_im_path, output_dir, num):

FILE: modules/image/Image_gan/gan/stgan_bald/test.py
  class TestHubModule (line 11) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 13) | def setUpClass(cls) -> None:
    method tearDownClass (line 24) | def tearDownClass(cls) -> None:
    method test_bald1 (line 29) | def test_bald1(self):
    method test_bald2 (line 40) | def test_bald2(self):
    method test_bald3 (line 51) | def test_bald3(self):
    method test_bald4 (line 63) | def test_bald4(self):
    method test_bald5 (line 70) | def test_bald5(self):
    method test_save_inference_model (line 77) | def test_save_inference_model(self):

FILE: modules/image/Image_gan/gan/styleganv2_editing/basemodel.py
  function get_mean_style (line 42) | def get_mean_style(generator):
  function sample (line 59) | def sample(generator, mean_style, n_sample):
  function style_mixing (line 70) | def style_mixing(generator, mean_style, n_source, n_target):
  class StyleGANv2Predictor (line 97) | class StyleGANv2Predictor:
    method __init__ (line 98) | def __init__(self,
    method run (line 131) | def run(self, n_row=3, n_col=5):

FILE: modules/image/Image_gan/gan/styleganv2_editing/model.py
  function make_image (line 30) | def make_image(tensor):
  class StyleGANv2EditingPredictor (line 34) | class StyleGANv2EditingPredictor(StyleGANv2Predictor):
    method __init__ (line 35) | def __init__(self, model_type=None, direction_path=None, **kwargs):
    method run (line 44) | def run(self, latent, direction, offset):

FILE: modules/image/Image_gan/gan/styleganv2_editing/module.py
  class styleganv2_editing (line 38) | class styleganv2_editing:
    method __init__ (line 39) | def __init__(self):
    method generate (line 45) | def generate(self,
    method run_cmd (line 98) | def run_cmd(self, argvs: list):
    method serving_method (line 124) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 133) | def add_module_config_arg(self):
    method add_module_input_arg (line 143) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/gan/styleganv2_editing/util.py
  function base64_to_cv2 (line 6) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/gan/styleganv2_mixing/basemodel.py
  function get_mean_style (line 42) | def get_mean_style(generator):
  function sample (line 59) | def sample(generator, mean_style, n_sample):
  function style_mixing (line 70) | def style_mixing(generator, mean_style, n_source, n_target):
  class StyleGANv2Predictor (line 97) | class StyleGANv2Predictor:
    method __init__ (line 98) | def __init__(self,
    method run (line 131) | def run(self, n_row=3, n_col=5):

FILE: modules/image/Image_gan/gan/styleganv2_mixing/model.py
  function make_image (line 23) | def make_image(tensor):
  class StyleGANv2MixingPredictor (line 27) | class StyleGANv2MixingPredictor(StyleGANv2Predictor):
    method run (line 29) | def run(self, latent1, latent2, weights=[0.5] * 18):

FILE: modules/image/Image_gan/gan/styleganv2_mixing/module.py
  class styleganv2_mixing (line 38) | class styleganv2_mixing:
    method __init__ (line 39) | def __init__(self):
    method generate (line 44) | def generate(self,
    method run_cmd (line 100) | def run_cmd(self, argvs: list):
    method serving_method (line 128) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 140) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/gan/styleganv2_mixing/util.py
  function base64_to_cv2 (line 6) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/gan/wav2lip/model.py
  class Wav2LipPredictor (line 18) | class Wav2LipPredictor:
    method __init__ (line 19) | def __init__(self,
    method get_smoothened_boxes (line 52) | def get_smoothened_boxes(self, boxes, T):
    method face_detect (line 61) | def face_detect(self, images):
    method datagen (line 102) | def datagen(self, frames, mels):
    method run (line 150) | def run(self, face, audio_seq, output_dir, visualization=True):

FILE: modules/image/Image_gan/gan/wav2lip/module.py
  class wav2lip (line 29) | class wav2lip:
    method __init__ (line 30) | def __init__(self):
    method wav2lip_transfer (line 48) | def wav2lip_transfer(self, face, audio, output_dir='./output_result/',...
    method run_cmd (line 62) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 86) | def add_module_config_arg(self):
    method add_module_input_arg (line 96) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/ID_Photo_GEN/module.py
  class ID_Photo_GEN (line 19) | class ID_Photo_GEN(nn.Layer):
    method __init__ (line 20) | def __init__(self):
    method load_datas (line 30) | def load_datas(paths, images):
    method preprocess (line 47) | def preprocess(self, images, batch_size, use_gpu):
    method predict (line 133) | def predict(self, input_datas):
    method postprocess (line 151) | def postprocess(faces, masks, visualization, output_dir):
    method Photo_GEN (line 175) | def Photo_GEN(self, images=None, paths=None, batch_size=1, output_dir=...

FILE: modules/image/Image_gan/style_transfer/Photo2Cartoon/model/networks.py
  class ResnetGenerator (line 6) | class ResnetGenerator(nn.Layer):
    method __init__ (line 7) | def __init__(self, ngf=32, img_size=256, n_blocks=4, light=True):
    method forward (line 91) | def forward(self, x):
  class ConvBlock (line 131) | class ConvBlock(nn.Layer):
    method __init__ (line 132) | def __init__(self, dim_in, dim_out):
    method __convblock (line 147) | def __convblock(dim_in, dim_out):
    method forward (line 152) | def forward(self, x):
  class HourGlassBlock (line 166) | class HourGlassBlock(nn.Layer):
    method __init__ (line 167) | def __init__(self, dim_in):
    method forward (line 179) | def forward(self, x):
  class HourGlass (line 196) | class HourGlass(nn.Layer):
    method __init__ (line 197) | def __init__(self, dim_in, dim_out, use_res=True):
    method forward (line 212) | def forward(self, x):
  class ResnetBlock (line 225) | class ResnetBlock(nn.Layer):
    method __init__ (line 226) | def __init__(self, dim, use_bias=False):
    method forward (line 244) | def forward(self, x):
  class ResnetSoftAdaLINBlock (line 249) | class ResnetSoftAdaLINBlock(nn.Layer):
    method __init__ (line 250) | def __init__(self, dim, use_bias=False):
    method forward (line 261) | def forward(self, x, content_features, style_features):
  class SoftAdaLIN (line 273) | class SoftAdaLIN(nn.Layer):
    method __init__ (line 274) | def __init__(self, num_features, eps=1e-5):
    method forward (line 290) | def forward(self, x, content_features, style_features):
  class AdaLIN (line 305) | class AdaLIN(nn.Layer):
    method __init__ (line 306) | def __init__(self, num_features, eps=1e-5):
    method forward (line 311) | def forward(self, x, gamma, beta):
  class LIN (line 323) | class LIN(nn.Layer):
    method __init__ (line 324) | def __init__(self, num_features, eps=1e-5):
    method forward (line 331) | def forward(self, x):

FILE: modules/image/Image_gan/style_transfer/Photo2Cartoon/module.py
  class Photo2Cartoon (line 20) | class Photo2Cartoon(nn.Layer):
    method __init__ (line 21) | def __init__(self):
    method load_datas (line 41) | def load_datas(paths, images):
    method preprocess (line 58) | def preprocess(self, images, batch_size, use_gpu):
    method predict (line 167) | def predict(self, input_datas):
    method postprocess (line 185) | def postprocess(outputs, masks, visualization, output_dir):
    method Cartoon_GEN (line 210) | def Cartoon_GEN(self,

FILE: modules/image/Image_gan/style_transfer/U2Net_Portrait/module.py
  class U2Net_Portrait (line 18) | class U2Net_Portrait(nn.Layer):
    method __init__ (line 19) | def __init__(self):
    method predict (line 26) | def predict(self, input_datas):
    method Portrait_GEN (line 37) | def Portrait_GEN(self,

FILE: modules/image/Image_gan/style_transfer/U2Net_Portrait/processor.py
  class Processor (line 9) | class Processor():
    method __init__ (line 10) | def __init__(self, paths, images, batch_size, face_detection=True, sca...
    method load_datas (line 18) | def load_datas(self, paths, images):
    method preprocess (line 35) | def preprocess(self, imgs, batch_size=1, face_detection=True, scale=1):
    method normPRED (line 110) | def normPRED(self, d):
    method postprocess (line 119) | def postprocess(self, outputs, visualization=False, output_dir='output'):

FILE: modules/image/Image_gan/style_transfer/U2Net_Portrait/u2net.py
  class REBNCONV (line 8) | class REBNCONV(nn.Layer):
    method __init__ (line 9) | def __init__(self, in_ch=3, out_ch=3, dirate=1):
    method forward (line 16) | def forward(self, x):
  function _upsample_like (line 25) | def _upsample_like(src, tar):
  class RSU7 (line 33) | class RSU7(nn.Layer):  #UNet07DRES(nn.Layer):
    method __init__ (line 34) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 65) | def forward(self, x):
  class RSU6 (line 110) | class RSU6(nn.Layer):  #UNet06DRES(nn.Layer):
    method __init__ (line 111) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 138) | def forward(self, x):
  class RSU5 (line 178) | class RSU5(nn.Layer):  #UNet05DRES(nn.Layer):
    method __init__ (line 179) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 202) | def forward(self, x):
  class RSU4 (line 236) | class RSU4(nn.Layer):  #UNet04DRES(nn.Layer):
    method __init__ (line 237) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 256) | def forward(self, x):
  class RSU4F (line 284) | class RSU4F(nn.Layer):  #UNet04FRES(nn.Layer):
    method __init__ (line 285) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 300) | def forward(self, x):
  class U2NET (line 320) | class U2NET(nn.Layer):
    method __init__ (line 321) | def __init__(self, in_ch=3, out_ch=1):
    method forward (line 357) | def forward(self, x):
  class U2NETP (line 424) | class U2NETP(nn.Layer):
    method __init__ (line 425) | def __init__(self, in_ch=3, out_ch=1):
    method forward (line 461) | def forward(self, x):

FILE: modules/image/Image_gan/style_transfer/UGATIT_100w/model.py
  class Model (line 9) | class Model():
    method __init__ (line 11) | def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined...
    method load_model (line 22) | def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
    method predict (line 61) | def predict(self, input_datas):

FILE: modules/image/Image_gan/style_transfer/UGATIT_100w/module.py
  class UGATIT_100w (line 18) | class UGATIT_100w(Module):
    method __init__ (line 20) | def __init__(self, name=None, use_gpu=False):
    method style_transfer (line 28) | def style_transfer(self, images=None, paths=None, batch_size=1, output...
    method serving_method (line 43) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/UGATIT_100w/processor.py
  function check_dir (line 10) | def check_dir(dir_path):
  function base64_to_cv2 (line 19) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 27) | def cv2_to_base64(image):
  class Processor (line 33) | class Processor():
    method __init__ (line 35) | def __init__(self, images=None, paths=None, output_dir='output', batch...
    method load_datas (line 49) | def load_datas(self):
    method preprocess (line 66) | def preprocess(self):
    method postprocess (line 95) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/UGATIT_83w/model.py
  class Model (line 9) | class Model():
    method __init__ (line 11) | def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined...
    method load_model (line 22) | def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
    method predict (line 61) | def predict(self, input_datas):

FILE: modules/image/Image_gan/style_transfer/UGATIT_83w/module.py
  class UGATIT_83w (line 18) | class UGATIT_83w(Module):
    method __init__ (line 20) | def __init__(self, name=None, use_gpu=False):
    method style_transfer (line 28) | def style_transfer(self, images=None, paths=None, batch_size=1, output...
    method serving_method (line 43) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/UGATIT_83w/processor.py
  function check_dir (line 10) | def check_dir(dir_path):
  function base64_to_cv2 (line 19) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 27) | def cv2_to_base64(image):
  class Processor (line 33) | class Processor():
    method __init__ (line 35) | def __init__(self, images=None, paths=None, output_dir='output', batch...
    method load_datas (line 49) | def load_datas(self):
    method preprocess (line 66) | def preprocess(self):
    method postprocess (line 95) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/UGATIT_92w/model.py
  class Model (line 9) | class Model():
    method __init__ (line 11) | def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined...
    method load_model (line 22) | def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
    method predict (line 61) | def predict(self, input_datas):

FILE: modules/image/Image_gan/style_transfer/UGATIT_92w/module.py
  class UGATIT_92w (line 18) | class UGATIT_92w(Module):
    method __init__ (line 20) | def __init__(self, name=None, use_gpu=False):
    method style_transfer (line 28) | def style_transfer(self, images=None, paths=None, batch_size=1, output...
    method serving_method (line 43) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/UGATIT_92w/processor.py
  function check_dir (line 10) | def check_dir(dir_path):
  function base64_to_cv2 (line 19) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 27) | def cv2_to_base64(image):
  class Processor (line 33) | class Processor():
    method __init__ (line 35) | def __init__(self, images=None, paths=None, output_dir='output', batch...
    method load_datas (line 49) | def load_datas(self):
    method preprocess (line 66) | def preprocess(self):
    method postprocess (line 95) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v1_hayao_60/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v1_hayao_60/module.py
  class Animegan_V1_Hayao_60 (line 19) | class Animegan_V1_Hayao_60:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v1_hayao_60/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v1_hayao_60/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_64/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_64/module.py
  class Animegan_V2_Hayao_64 (line 19) | class Animegan_V2_Hayao_64:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_64/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_64/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_99/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_99/module.py
  class Animegan_V2_Hayao_99 (line 19) | class Animegan_V2_Hayao_99:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_99/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_hayao_99/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_54/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_54/module.py
  class Animegan_V2_Paprika_54 (line 19) | class Animegan_V2_Paprika_54:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_54/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_54/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_74/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_74/module.py
  class Animegan_V2_Paprika_74 (line 19) | class Animegan_V2_Paprika_74:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_74/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_74/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_97/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_97/module.py
  class Animegan_V2_Paprika_97 (line 19) | class Animegan_V2_Paprika_97:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_97/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_97/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_98/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_98/module.py
  class Animegan_V2_Paprika_98 (line 19) | class Animegan_V2_Paprika_98:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_98/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_paprika_98/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_33/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_33/module.py
  class Animegan_V2_Shinkai_33 (line 19) | class Animegan_V2_Shinkai_33:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_33/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_33/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_53/model.py
  class InferenceModel (line 10) | class InferenceModel:
    method __init__ (line 12) | def __init__(self, modelpath, use_gpu=False, gpu_id=0, use_mkldnn=Fals...
    method __repr__ (line 23) | def __repr__(self):
    method __call__ (line 31) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 38) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 98) | def eval(self):
    method forward (line 124) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_53/module.py
  class Animegan_V2_Shinkai_53 (line 19) | class Animegan_V2_Shinkai_53:
    method __init__ (line 21) | def __init__(self, use_gpu=False, use_mkldnn=False):
    method style_transfer (line 31) | def style_transfer(self,
    method serving_method (line 60) | def serving_method(self, images, **kwargs):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_53/processor.py
  function check_dir (line 11) | def check_dir(dir_path):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 28) | def cv2_to_base64(image):
  class Processor (line 34) | class Processor():
    method __init__ (line 36) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 53) | def load_datas(self):
    method preprocess (line 70) | def preprocess(self):
    method postprocess (line 109) | def postprocess(self, outputs, visualization):

FILE: modules/image/Image_gan/style_transfer/animegan_v2_shinkai_53/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 31) | def tearDownClass(cls) -> None:
    method test_style_transfer1 (line 35) | def test_style_transfer1(self):
    method test_style_transfer2 (line 39) | def test_style_transfer2(self):
    method test_style_transfer3 (line 43) | def test_style_transfer3(self):
    method test_style_transfer4 (line 47) | def test_style_transfer4(self):
    method test_style_transfer5 (line 51) | def test_style_transfer5(self):
    method test_style_transfer6 (line 54) | def test_style_transfer6(self):

FILE: modules/image/Image_gan/style_transfer/face_parse/model.py
  class FaceParsePredictor (line 28) | class FaceParsePredictor:
    method __init__ (line 29) | def __init__(self):
    method run (line 36) | def run(self, image):

FILE: modules/image/Image_gan/style_transfer/face_parse/module.py
  class Face_parse (line 35) | class Face_parse:
    method __init__ (line 36) | def __init__(self):
    method style_transfer (line 41) | def style_transfer(self,
    method run_cmd (line 86) | def run_cmd(self, argvs: list):
    method serving_method (line 110) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 119) | def add_module_config_arg(self):
    method add_module_input_arg (line 129) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/face_parse/util.py
  function base64_to_cv2 (line 6) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/style_transfer/lapstyle_circuit/model.py
  function img (line 29) | def img(img):
  function img_totensor (line 37) | def img_totensor(content_img, style_img):
  function tensor_resample (line 61) | def tensor_resample(tensor, dst_size, mode='bilinear'):
  function laplacian (line 65) | def laplacian(x):
  function make_laplace_pyramid (line 75) | def make_laplace_pyramid(x, levels):
  function fold_laplace_pyramid (line 88) | def fold_laplace_pyramid(pyramid):
  class LapStylePredictor (line 99) | class LapStylePredictor:
    method __init__ (line 100) | def __init__(self, weight_path=None):
    method run (line 116) | def run(self, content_img, style_image):

FILE: modules/image/Image_gan/style_transfer/lapstyle_circuit/module.py
  class Lapstyle_circuit (line 40) | class Lapstyle_circuit:
    method __init__ (line 41) | def __init__(self):
    method style_transfer (line 46) | def style_transfer(self,
    method run_cmd (line 96) | def run_cmd(self, argvs: list):
    method serving_method (line 123) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 135) | def add_module_config_arg(self):
    method add_module_input_arg (line 145) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/lapstyle_circuit/util.py
  function base64_to_cv2 (line 7) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/style_transfer/lapstyle_ocean/model.py
  function img (line 29) | def img(img):
  function img_totensor (line 37) | def img_totensor(content_img, style_img):
  function tensor_resample (line 61) | def tensor_resample(tensor, dst_size, mode='bilinear'):
  function laplacian (line 65) | def laplacian(x):
  function make_laplace_pyramid (line 75) | def make_laplace_pyramid(x, levels):
  function fold_laplace_pyramid (line 88) | def fold_laplace_pyramid(pyramid):
  class LapStylePredictor (line 99) | class LapStylePredictor:
    method __init__ (line 100) | def __init__(self, weight_path=None):
    method run (line 116) | def run(self, content_img, style_image):

FILE: modules/image/Image_gan/style_transfer/lapstyle_ocean/module.py
  class Lapstyle_ocean (line 40) | class Lapstyle_ocean:
    method __init__ (line 41) | def __init__(self):
    method style_transfer (line 46) | def style_transfer(self,
    method run_cmd (line 95) | def run_cmd(self, argvs: list):
    method serving_method (line 122) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 134) | def add_module_config_arg(self):
    method add_module_input_arg (line 144) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/lapstyle_ocean/util.py
  function base64_to_cv2 (line 7) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/style_transfer/lapstyle_starrynew/model.py
  function img (line 29) | def img(img):
  function img_totensor (line 37) | def img_totensor(content_img, style_img):
  function tensor_resample (line 61) | def tensor_resample(tensor, dst_size, mode='bilinear'):
  function laplacian (line 65) | def laplacian(x):
  function make_laplace_pyramid (line 75) | def make_laplace_pyramid(x, levels):
  function fold_laplace_pyramid (line 88) | def fold_laplace_pyramid(pyramid):
  class LapStylePredictor (line 99) | class LapStylePredictor:
    method __init__ (line 100) | def __init__(self, weight_path=None):
    method run (line 116) | def run(self, content_img, style_image):

FILE: modules/image/Image_gan/style_transfer/lapstyle_starrynew/module.py
  class Lapstyle_starrynew (line 40) | class Lapstyle_starrynew:
    method __init__ (line 41) | def __init__(self):
    method style_transfer (line 46) | def style_transfer(self,
    method run_cmd (line 94) | def run_cmd(self, argvs: list):
    method serving_method (line 121) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 133) | def add_module_config_arg(self):
    method add_module_input_arg (line 143) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/lapstyle_starrynew/util.py
  function base64_to_cv2 (line 7) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/style_transfer/lapstyle_stars/model.py
  function img (line 29) | def img(img):
  function img_totensor (line 37) | def img_totensor(content_img, style_img):
  function tensor_resample (line 61) | def tensor_resample(tensor, dst_size, mode='bilinear'):
  function laplacian (line 65) | def laplacian(x):
  function make_laplace_pyramid (line 75) | def make_laplace_pyramid(x, levels):
  function fold_laplace_pyramid (line 88) | def fold_laplace_pyramid(pyramid):
  class LapStylePredictor (line 99) | class LapStylePredictor:
    method __init__ (line 100) | def __init__(self, weight_path=None):
    method run (line 116) | def run(self, content_img, style_image):

FILE: modules/image/Image_gan/style_transfer/lapstyle_stars/module.py
  class Lapstyle_stars (line 40) | class Lapstyle_stars:
    method __init__ (line 41) | def __init__(self):
    method style_transfer (line 46) | def style_transfer(self,
    method run_cmd (line 95) | def run_cmd(self, argvs: list):
    method serving_method (line 122) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 134) | def add_module_config_arg(self):
    method add_module_input_arg (line 144) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/lapstyle_stars/util.py
  function base64_to_cv2 (line 7) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/style_transfer/msgnet/module.py
  class GramMatrix (line 15) | class GramMatrix(nn.Layer):
    method forward (line 18) | def forward(self, y):
  class ConvLayer (line 26) | class ConvLayer(nn.Layer):
    method __init__ (line 29) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 35) | def forward(self, x: paddle.Tensor):
  class UpsampleConvLayer (line 41) | class UpsampleConvLayer(nn.Layer):
    method __init__ (line 57) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 67) | def forward(self, x):
  class Bottleneck (line 76) | class Bottleneck(nn.Layer):
    method __init__ (line 92) | def __init__(self,
    method forward (line 109) | def forward(self, x: paddle.Tensor):
  class UpBottleneck (line 118) | class UpBottleneck(nn.Layer):
    method __init__ (line 133) | def __init__(self, inplanes: int, planes: int, stride: int = 2, norm_l...
    method forward (line 152) | def forward(self, x: paddle.Tensor):
  class Inspiration (line 156) | class Inspiration(nn.Layer):
    method __init__ (line 169) | def __init__(self, C: int, B: int = 1):
    method setTarget (line 177) | def setTarget(self, target: paddle.Tensor):
    method forward (line 180) | def forward(self, X: paddle.Tensor):
    method __repr__ (line 189) | def __repr__(self):
  class Vgg16 (line 194) | class Vgg16(nn.Layer):
    method __init__ (line 197) | def __init__(self):
    method forward (line 222) | def forward(self, X):
  class MSGNet (line 255) | class MSGNet(nn.Layer):
    method __init__ (line 272) | def __init__(self, input_nc=3, output_nc=3, ngf=128, n_blocks=6, norm_...
    method transform (line 328) | def transform(self, path: str):
    method setTarget (line 332) | def setTarget(self, Xs: paddle.Tensor):
    method getFeature (line 338) | def getFeature(self, input: paddle.Tensor):
    method forward (line 343) | def forward(self, input: paddle.Tensor):

FILE: modules/image/Image_gan/style_transfer/paint_transformer/inference.py
  function main (line 15) | def main(input_path, model_path, output_dir, need_animation=False, resiz...

FILE: modules/image/Image_gan/style_transfer/paint_transformer/model.py
  class Painter (line 6) | class Painter(nn.Layer):
    method __init__ (line 11) | def __init__(self, param_per_stroke, total_strokes, hidden_dim, n_head...
    method forward (line 46) | def forward(self, img, canvas):

FILE: modules/image/Image_gan/style_transfer/paint_transformer/module.py
  class paint_transformer (line 40) | class paint_transformer:
    method __init__ (line 41) | def __init__(self):
    method style_transfer (line 54) | def style_transfer(self,
    method run_cmd (line 110) | def run_cmd(self, argvs: list):
    method serving_method (line 135) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 144) | def add_module_config_arg(self):
    method add_module_input_arg (line 156) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/paint_transformer/render_parallel.py
  function crop (line 9) | def crop(img, h, w):
  function stroke_net_predict (line 19) | def stroke_net_predict(img_patch, result_patch, patch_size, net_g, strok...
  function param2img_parallel (line 44) | def param2img_parallel(param, decision, meta_brushes, cur_canvas, stroke...
  function render_parallel (line 201) | def render_parallel(original_img, net_g, meta_brushes):

FILE: modules/image/Image_gan/style_transfer/paint_transformer/render_serial.py
  function get_single_layer_lists (line 16) | def get_single_layer_lists(param, decision, ori_img, render_size_x, rend...
  function get_single_stroke_on_full_image_A (line 85) | def get_single_stroke_on_full_image_A(x_id, y_id, valid_foregrounds, val...
  function get_single_stroke_on_full_image_B (line 114) | def get_single_stroke_on_full_image_B(x_id, y_id, valid_foregrounds, val...
  function stroke_net_predict (line 141) | def stroke_net_predict(img_patch, result_patch, patch_size, net_g, strok...
  function sort_strokes (line 165) | def sort_strokes(params, decision, scores):
  function render_serial (line 179) | def render_serial(original_img, net_g, meta_brushes):

FILE: modules/image/Image_gan/style_transfer/paint_transformer/render_utils.py
  class Erosion2d (line 10) | class Erosion2d(nn.Layer):
    method __init__ (line 15) | def __init__(self, m=1):
    method forward (line 20) | def forward(self, x):
  class Dilation2d (line 28) | class Dilation2d(nn.Layer):
    method __init__ (line 33) | def __init__(self, m=1):
    method forward (line 38) | def forward(self, x):
  function param2stroke (line 46) | def param2stroke(param, H, W, meta_brushes):
  function read_img (line 76) | def read_img(img_path, img_type='RGB', h=None, w=None):
  function preprocess (line 91) | def preprocess(img, w=512, h=512):
  function totensor (line 98) | def totensor(img):
  function pad (line 104) | def pad(img, H, W):

FILE: modules/image/Image_gan/style_transfer/paint_transformer/util.py
  function base64_to_cv2 (line 6) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/style_transfer/psgan/model.py
  function toImage (line 32) | def toImage(net_output):
  class PreProcess (line 43) | class PreProcess:
    method __init__ (line 44) | def __init__(self, config, need_parser=True):
    method __call__ (line 57) | def __call__(self, image):
  class PostProcess (line 85) | class PostProcess:
    method __init__ (line 86) | def __init__(self, config):
    method __call__ (line 90) | def __call__(self, source: Image, result: Image):
  class Inference (line 105) | class Inference:
    method __init__ (line 106) | def __init__(self, config, model_path=''):
    method transfer (line 111) | def transfer(self, source, reference, with_face=False):
  class PSGANPredictor (line 154) | class PSGANPredictor:
    method __init__ (line 155) | def __init__(self, cfg, weight_path):
    method run (line 159) | def run(self, source, reference):

FILE: modules/image/Image_gan/style_transfer/psgan/module.py
  class psgan (line 35) | class psgan:
    method __init__ (line 36) | def __init__(self):
    method makeup_transfer (line 41) | def makeup_transfer(self,
    method run_cmd (line 90) | def run_cmd(self, argvs: list):
    method serving_method (line 117) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 129) | def add_module_config_arg(self):
    method add_module_input_arg (line 139) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/psgan/util.py
  function base64_to_cv2 (line 7) | def base64_to_cv2(b64str):

FILE: modules/image/Image_gan/style_transfer/stylepro_artistic/data_feed.py
  function reader (line 13) | def reader(images=None, paths=None):
  function _handle_single (line 61) | def _handle_single(im_path=None, im_arr=None):

FILE: modules/image/Image_gan/style_transfer/stylepro_artistic/module.py
  class StyleProjection (line 35) | class StyleProjection(hub.Module):
    method _initialize (line 37) | def _initialize(self):
    method _set_config (line 42) | def _set_config(self):
    method style_transfer (line 75) | def style_transfer(self,
    method save_inference_model (line 147) | def save_inference_model(self, dirname, model_filename=None, params_fi...
    method _save_encode_model (line 153) | def _save_encode_model(self, dirname, model_filename=None, params_file...
    method _save_decode_model (line 171) | def _save_decode_model(self, dirname, model_filename=None, params_file...
    method serving_method (line 190) | def serving_method(self, images, **kwargs):
    method run_cmd (line 203) | def run_cmd(self, argvs):
    method add_module_config_arg (line 229) | def add_module_config_arg(self):
    method add_module_input_arg (line 246) | def add_module_input_arg(self):

FILE: modules/image/Image_gan/style_transfer/stylepro_artistic/processor.py
  function cv2_to_base64 (line 15) | def cv2_to_base64(image):
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function postprocess (line 27) | def postprocess(im, output_dir, save_im_name, visualization, size):
  function fr (line 52) | def fr(content_feat, style_feat, alpha):
  function scatter_numpy (line 65) | def scatter_numpy(dim, index, src):

FILE: modules/image/classification/DriverStatusRecognition/module.py
  function base64_to_cv2 (line 15) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 22) | def cv2_to_base64(image):
  function read_images (line 28) | def read_images(paths):
  class MODULE (line 42) | class MODULE(hub.Module):
    method _initialize (line 43) | def _initialize(self, **kwargs):
    method predict (line 47) | def predict(self, images=None, paths=None, data=None, batch_size=1, us...
    method serving_method (line 67) | def serving_method(self, images, **kwargs):
    method run_cmd (line 96) | def run_cmd(self, argvs):
    method add_module_config_arg (line 114) | def add_module_config_arg(self):
    method add_module_input_arg (line 120) | def add_module_input_arg(self):

FILE: modules/image/classification/DriverStatusRecognition/serving_client_demo.py
  function cv2_to_base64 (line 8) | def cv2_to_base64(image):

FILE: modules/image/classification/SnakeIdentification/module.py
  function base64_to_cv2 (line 15) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 22) | def cv2_to_base64(image):
  function read_images (line 28) | def read_images(paths):
  class MODULE (line 42) | class MODULE(hub.Module):
    method _initialize (line 43) | def _initialize(self, **kwargs):
    method predict (line 47) | def predict(self, images=None, paths=None, data=None, batch_size=1, us...
    method serving_method (line 67) | def serving_method(self, images, **kwargs):
    method run_cmd (line 96) | def run_cmd(self, argvs):
    method add_module_config_arg (line 114) | def add_module_config_arg(self):
    method add_module_input_arg (line 120) | def add_module_input_arg(self):

FILE: modules/image/classification/SnakeIdentification/serving_client_demo.py
  function cv2_to_base64 (line 8) | def cv2_to_base64(image):

FILE: modules/image/classification/SpinalNet_Gemstones/gem_dataset.py
  class GemStones (line 7) | class GemStones(paddle.io.Dataset):
    method __init__ (line 12) | def __init__(self, transforms: Callable, mode: str = 'train'):
    method __getitem__ (line 38) | def __getitem__(self, index):
    method __len__ (line 50) | def __len__(self):

FILE: modules/image/classification/SpinalNet_Gemstones/spinalnet_res101_gemstone/module.py
  class BottleneckBlock (line 25) | class BottleneckBlock(nn.Layer):
    method __init__ (line 29) | def __init__(self,
    method forward (line 56) | def forward(self, x):
  class ResNet (line 79) | class ResNet(nn.Layer):
    method __init__ (line 80) | def __init__(self, block=BottleneckBlock, depth=101, with_pool=True):
    method _make_layer (line 101) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method forward (line 122) | def forward(self, x):
  class SpinalNet_ResNet101 (line 147) | class SpinalNet_ResNet101(nn.Layer):
    method __init__ (line 148) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 198) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 207) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/SpinalNet_Gemstones/spinalnet_res50_gemstone/module.py
  class BottleneckBlock (line 25) | class BottleneckBlock(nn.Layer):
    method __init__ (line 29) | def __init__(self,
    method forward (line 56) | def forward(self, x):
  class ResNet (line 79) | class ResNet(nn.Layer):
    method __init__ (line 80) | def __init__(self, block=BottleneckBlock, depth=50, with_pool=True):
    method _make_layer (line 101) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method forward (line 122) | def forward(self, x):
  class SpinalNet_ResNet50 (line 147) | class SpinalNet_ResNet50(nn.Layer):
    method __init__ (line 148) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 198) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 207) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/SpinalNet_Gemstones/spinalnet_vgg16_gemstone/module.py
  class VGG (line 28) | class VGG(nn.Layer):
    method __init__ (line 29) | def __init__(self, features, with_pool=True):
    method forward (line 37) | def forward(self, x):
  function make_layers (line 46) | def make_layers(cfg, batch_norm=False):
  function _vgg (line 70) | def _vgg(arch, cfg, batch_norm, **kwargs):
  function vgg16 (line 75) | def vgg16(batch_norm=False, **kwargs):
  class SpinalNet_VGG16 (line 91) | class SpinalNet_VGG16(nn.Layer):
    method __init__ (line 92) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 152) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 161) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/darknet53_imagenet/darknet.py
  class DarkNet (line 16) | class DarkNet(object):
    method __init__ (line 26) | def __init__(self,
    method _conv_norm (line 42) | def _conv_norm(self, input, ch_out, filter_size, stride, padding, act=...
    method _downsample (line 72) | def _downsample(self, input, ch_out, filter_size=3, stride=2, padding=...
    method basicblock (line 75) | def basicblock(self, input, ch_out, name=None):
    method layer_warp (line 81) | def layer_warp(self, block_func, input, ch_out, count, name=None):
    method __call__ (line 87) | def __call__(self, input):

FILE: modules/image/classification/darknet53_imagenet/data_feed.py
  function resize_short (line 19) | def resize_short(img, target_size):
  function crop_image (line 27) | def crop_image(img, target_size, center):
  function process_image (line 42) | def process_image(img):
  function test_reader (line 54) | def test_reader(paths=None, images=None):

FILE: modules/image/classification/darknet53_imagenet/module.py
  class DarkNet53 (line 25) | class DarkNet53(hub.Module):
    method _initialize (line 26) | def _initialize(self):
    method get_expected_image_width (line 33) | def get_expected_image_width(self):
    method get_expected_image_height (line 36) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 39) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 43) | def get_pretrained_images_std(self):
    method _set_config (line 47) | def _set_config(self):
    method context (line 68) | def context(self, input_image=None, trainable=True, pretrained=True, p...
    method classification (line 111) | def classification(self, paths=None, images=None, use_gpu=False, batch...
    method add_module_config_arg (line 164) | def add_module_config_arg(self):
    method add_module_input_arg (line 173) | def add_module_input_arg(self):
    method check_input_data (line 181) | def check_input_data(self, args):
    method run_cmd (line 193) | def run_cmd(self, argvs):

FILE: modules/image/classification/darknet53_imagenet/processor.py
  function load_label_info (line 2) | def load_label_info(file_path):

FILE: modules/image/classification/efficientnetb0_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb0_imagenet/module.py
  class EfficientNetB0ImageNet (line 39) | class EfficientNetB0ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb0_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 47) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb0_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb0_small_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb0_small_imagenet/module.py
  class EfficientNetB0SmallImageNet (line 39) | class EfficientNetB0SmallImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb0_small_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 48) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb0_small_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb1_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb1_imagenet/module.py
  class EfficientNetB1ImageNet (line 39) | class EfficientNetB1ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb1_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 47) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb1_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb2_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb2_imagenet/module.py
  class EfficientNetB2ImageNet (line 39) | class EfficientNetB2ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 140) | def serving_method(self, images, **kwargs):
    method run_cmd (line 149) | def run_cmd(self, argvs):
    method add_module_config_arg (line 166) | def add_module_config_arg(self):
    method add_module_input_arg (line 177) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb2_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 47) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb2_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb3_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb3_imagenet/module.py
  class EfficientNetB3ImageNet (line 39) | class EfficientNetB3ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 142) | def serving_method(self, images, **kwargs):
    method run_cmd (line 151) | def run_cmd(self, argvs):
    method add_module_config_arg (line 168) | def add_module_config_arg(self):
    method add_module_input_arg (line 179) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb3_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 47) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb3_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb4_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb4_imagenet/module.py
  class EfficientNetB4ImageNet (line 39) | class EfficientNetB4ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb4_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 47) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb4_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb5_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb5_imagenet/module.py
  class EfficientNetB5ImageNet (line 39) | class EfficientNetB5ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb5_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 47) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb5_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb6_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb6_imagenet/module.py
  class EfficientNetB6ImageNet (line 39) | class EfficientNetB6ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb6_imagenet/processor.py
  function base64_to_cv2 (line 25) | def base64_to_cv2(b64str):
  function softmax (line 32) | def softmax(x):
  function postprocess (line 48) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb6_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/efficientnetb7_imagenet/data_feed.py
  function resize_short (line 28) | def resize_short(img, target_size):
  function crop_image (line 36) | def crop_image(img, target_size, center):
  function process_image (line 51) | def process_image(img):
  function reader (line 62) | def reader(images=None, paths=None):

FILE: modules/image/classification/efficientnetb7_imagenet/module.py
  class EfficientNetB7ImageNet (line 39) | class EfficientNetB7ImageNet:
    method __init__ (line 41) | def __init__(self):
    method get_expected_image_width (line 49) | def get_expected_image_width(self):
    method get_expected_image_height (line 52) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 55) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 59) | def get_pretrained_images_std(self):
    method _set_config (line 63) | def _set_config(self):
    method classification (line 86) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/classification/efficientnetb7_imagenet/processor.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  function softmax (line 31) | def softmax(x):
  function postprocess (line 47) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/efficientnetb7_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/esnet_x0_25_imagenet/model.py
  class Identity (line 41) | class Identity(nn.Layer):
    method __init__ (line 43) | def __init__(self):
    method forward (line 46) | def forward(self, inputs):
  class TheseusLayer (line 50) | class TheseusLayer(nn.Layer):
    method __init__ (line 52) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 59) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 67) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 86) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 90) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 146) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 170) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 208) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 212) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 244) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function channel_shuffle (line 294) | def channel_shuffle(x, groups):
  function make_divisible (line 303) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 312) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 314) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, g...
    method forward (line 331) | def forward(self, x):
  class SEModule (line 339) | class SEModule(TheseusLayer):
    method __init__ (line 341) | def __init__(self, channel, reduction=4):
    method forward (line 349) | def forward(self, x):
  class ESBlock1 (line 360) | class ESBlock1(TheseusLayer):
    method __init__ (line 362) | def __init__(self, in_channels, out_channels):
    method forward (line 375) | def forward(self, x):
  class ESBlock2 (line 386) | class ESBlock2(TheseusLayer):
    method __init__ (line 388) | def __init__(self, in_channels, out_channels):
    method forward (line 415) | def forward(self, x):
  class ESNet (line 428) | class ESNet(TheseusLayer):
    method __init__ (line 430) | def __init__(self,
    method forward (line 481) | def forward(self, x):
  function ESNet_x0_25 (line 495) | def ESNet_x0_25(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/esnet_x0_25_imagenet/module.py
  class Esnet_x0_25_Imagenet (line 42) | class Esnet_x0_25_Imagenet:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/esnet_x0_25_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/esnet_x0_25_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/esnet_x0_5_imagenet/model.py
  class Identity (line 41) | class Identity(nn.Layer):
    method __init__ (line 43) | def __init__(self):
    method forward (line 46) | def forward(self, inputs):
  class TheseusLayer (line 50) | class TheseusLayer(nn.Layer):
    method __init__ (line 52) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 59) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 67) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 86) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 90) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 146) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 170) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 208) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 212) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 244) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function channel_shuffle (line 294) | def channel_shuffle(x, groups):
  function make_divisible (line 303) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 312) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 314) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, g...
    method forward (line 331) | def forward(self, x):
  class SEModule (line 339) | class SEModule(TheseusLayer):
    method __init__ (line 341) | def __init__(self, channel, reduction=4):
    method forward (line 349) | def forward(self, x):
  class ESBlock1 (line 360) | class ESBlock1(TheseusLayer):
    method __init__ (line 362) | def __init__(self, in_channels, out_channels):
    method forward (line 375) | def forward(self, x):
  class ESBlock2 (line 386) | class ESBlock2(TheseusLayer):
    method __init__ (line 388) | def __init__(self, in_channels, out_channels):
    method forward (line 415) | def forward(self, x):
  class ESNet (line 428) | class ESNet(TheseusLayer):
    method __init__ (line 430) | def __init__(self,
    method forward (line 481) | def forward(self, x):
  function ESNet_x0_5 (line 495) | def ESNet_x0_5(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/esnet_x0_5_imagenet/module.py
  class Esnet_x0_5_Imagenet (line 42) | class Esnet_x0_5_Imagenet:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/esnet_x0_5_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/esnet_x0_5_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/data_feed.py
  function resize_short (line 15) | def resize_short(img, target_size):
  function crop_image (line 23) | def crop_image(img, target_size, center):
  function process_image (line 38) | def process_image(img):
  function reader (line 49) | def reader(images=None, paths=None):

FILE: modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/module.py
  class FixResnext10132x48dwslImagenet (line 27) | class FixResnext10132x48dwslImagenet:
    method __init__ (line 29) | def __init__(self):
    method get_expected_image_width (line 36) | def get_expected_image_width(self):
    method get_expected_image_height (line 39) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 42) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 46) | def get_pretrained_images_std(self):
    method _set_config (line 50) | def _set_config(self):
    method classification (line 73) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 132) | def serving_method(self, images, **kwargs):
    method run_cmd (line 141) | def run_cmd(self, argvs):
    method add_module_config_arg (line 158) | def add_module_config_arg(self):
    method add_module_input_arg (line 169) | def add_module_input_arg(self):

FILE: modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/processor.py
  function base64_to_cv2 (line 11) | def base64_to_cv2(b64str):
  function softmax (line 18) | def softmax(x):
  function postprocess (line 34) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/food_classification/module.py
  function base64_to_cv2 (line 15) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 22) | def cv2_to_base64(image):
  function read_images (line 28) | def read_images(paths):
  class MODULE (line 42) | class MODULE(hub.Module):
    method _initialize (line 43) | def _initialize(self, **kwargs):
    method predict (line 47) | def predict(self, images=None, paths=None, data=None, batch_size=1, us...
    method serving_method (line 67) | def serving_method(self, images, **kwargs):
    method run_cmd (line 96) | def run_cmd(self, argvs):
    method add_module_config_arg (line 114) | def add_module_config_arg(self):
    method add_module_input_arg (line 120) | def add_module_input_arg(self):

FILE: modules/image/classification/ghostnet_x0_5_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 30) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, g...
    method forward (line 51) | def forward(self, inputs):
  class SEBlock (line 57) | class SEBlock(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_channels, reduction_ratio=4, name=None):
    method forward (line 76) | def forward(self, inputs):
  class GhostModule (line 88) | class GhostModule(nn.Layer):
    method __init__ (line 89) | def __init__(self, in_channels, output_channels, kernel_size=1, ratio=...
    method forward (line 110) | def forward(self, inputs):
  class GhostBottleneck (line 117) | class GhostBottleneck(nn.Layer):
    method __init__ (line 118) | def __init__(self, in_channels, hidden_dim, output_channels, kernel_si...
    method forward (line 168) | def forward(self, inputs):
  class GhostNet (line 192) | class GhostNet(nn.Layer):
    method __init__ (line 193) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 290) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 299) | def forward(self, inputs):
    method _make_divisible (line 311) | def _make_divisible(self, v, divisor, min_value=None):

FILE: modules/image/classification/ghostnet_x1_0_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 30) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, g...
    method forward (line 51) | def forward(self, inputs):
  class SEBlock (line 57) | class SEBlock(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_channels, reduction_ratio=4, name=None):
    method forward (line 76) | def forward(self, inputs):
  class GhostModule (line 88) | class GhostModule(nn.Layer):
    method __init__ (line 89) | def __init__(self, in_channels, output_channels, kernel_size=1, ratio=...
    method forward (line 110) | def forward(self, inputs):
  class GhostBottleneck (line 117) | class GhostBottleneck(nn.Layer):
    method __init__ (line 118) | def __init__(self, in_channels, hidden_dim, output_channels, kernel_si...
    method forward (line 168) | def forward(self, inputs):
  class GhostNet (line 192) | class GhostNet(nn.Layer):
    method __init__ (line 193) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 290) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 299) | def forward(self, inputs):
    method _make_divisible (line 311) | def _make_divisible(self, v, divisor, min_value=None):

FILE: modules/image/classification/ghostnet_x1_3_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 30) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, g...
    method forward (line 51) | def forward(self, inputs):
  class SEBlock (line 57) | class SEBlock(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_channels, reduction_ratio=4, name=None):
    method forward (line 76) | def forward(self, inputs):
  class GhostModule (line 88) | class GhostModule(nn.Layer):
    method __init__ (line 89) | def __init__(self, in_channels, output_channels, kernel_size=1, ratio=...
    method forward (line 110) | def forward(self, inputs):
  class GhostBottleneck (line 117) | class GhostBottleneck(nn.Layer):
    method __init__ (line 118) | def __init__(self, in_channels, hidden_dim, output_channels, kernel_si...
    method forward (line 168) | def forward(self, inputs):
  class GhostNet (line 192) | class GhostNet(nn.Layer):
    method __init__ (line 193) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 290) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 299) | def forward(self, inputs):
    method _make_divisible (line 311) | def _make_divisible(self, v, divisor, min_value=None):

FILE: modules/image/classification/ghostnet_x1_3_imagenet_ssld/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 30) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, g...
    method forward (line 51) | def forward(self, inputs):
  class SEBlock (line 57) | class SEBlock(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_channels, reduction_ratio=4, name=None):
    method forward (line 76) | def forward(self, inputs):
  class GhostModule (line 88) | class GhostModule(nn.Layer):
    method __init__ (line 89) | def __init__(self, in_channels, output_channels, kernel_size=1, ratio=...
    method forward (line 110) | def forward(self, inputs):
  class GhostBottleneck (line 117) | class GhostBottleneck(nn.Layer):
    method __init__ (line 118) | def __init__(self, in_channels, hidden_dim, output_channels, kernel_si...
    method forward (line 168) | def forward(self, inputs):
  class GhostNet (line 192) | class GhostNet(nn.Layer):
    method __init__ (line 193) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 290) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 299) | def forward(self, inputs):
    method _make_divisible (line 311) | def _make_divisible(self, v, divisor, min_value=None):

FILE: modules/image/classification/googlenet_imagenet/module.py
  function xavier (line 28) | def xavier(channels: int, filter_size: int, name: str):
  class ConvLayer (line 35) | class ConvLayer(nn.Layer):
    method __init__ (line 38) | def __init__(self,
    method forward (line 57) | def forward(self, inputs: paddle.Tensor):
  class Inception (line 62) | class Inception(nn.Layer):
    method __init__ (line 65) | def __init__(self,
    method forward (line 86) | def forward(self, inputs: paddle.Tensor):
  class GoogleNet (line 112) | class GoogleNet(nn.Layer):
    method __init__ (line 115) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 155) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/hrnet18_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet18 (line 445) | class HRNet18(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet18_imagenet_ssld/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet18 (line 445) | class HRNet18(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet30_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet30 (line 445) | class HRNet30(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet32_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet32 (line 445) | class HRNet32(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet40_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet40 (line 445) | class HRNet40(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet44_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet44 (line 445) | class HRNet44(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet48_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet48 (line 445) | class HRNet48(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet48_imagenet_ssld/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet48 (line 445) | class HRNet48(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/hrnet64_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class HRNet64 (line 445) | class HRNet64(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/inceptionv4_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self,
    method forward (line 60) | def forward(self, inputs: paddle.Tensor):
  class InceptionStem (line 66) | class InceptionStem(nn.Layer):
    method __init__ (line 69) | def __init__(self):
    method forward (line 84) | def forward(self, inputs: paddle.Tensor):
  class InceptionA (line 110) | class InceptionA(nn.Layer):
    method __init__ (line 113) | def __init__(self, name: str):
    method forward (line 124) | def forward(self, inputs: paddle.Tensor):
  class ReductionA (line 141) | class ReductionA(nn.Layer):
    method __init__ (line 144) | def __init__(self):
    method forward (line 152) | def forward(self, inputs: paddle.Tensor):
  class InceptionB (line 162) | class InceptionB(nn.Layer):
    method __init__ (line 165) | def __init__(self, name: str = None):
    method forward (line 179) | def forward(self, inputs: paddle.Tensor):
  class ReductionB (line 199) | class ReductionB(nn.Layer):
    method __init__ (line 202) | def __init__(self):
    method forward (line 212) | def forward(self, inputs: paddle.Tensor):
  class InceptionC (line 228) | class InceptionC(nn.Layer):
    method __init__ (line 231) | def __init__(self, name: str = None):
    method forward (line 246) | def forward(self, inputs: paddle.Tensor):
  class InceptionV4 (line 276) | class InceptionV4(nn.Layer):
    method __init__ (line 279) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 326) | def forward(self, inputs):

FILE: modules/image/classification/levit_128_imagenet/model.py
  function cal_attention_biases (line 32) | def cal_attention_biases(attention_biases, attention_bias_idxs):
  class Conv2d_BN (line 44) | class Conv2d_BN(nn.Sequential):
    method __init__ (line 46) | def __init__(self, a, b, ks=1, stride=1, pad=0, dilation=1, groups=1, ...
  class Linear_BN (line 55) | class Linear_BN(nn.Sequential):
    method __init__ (line 57) | def __init__(self, a, b, bn_weight_init=1):
    method forward (line 68) | def forward(self, x):
  class BN_Linear (line 74) | class BN_Linear(nn.Sequential):
    method __init__ (line 76) | def __init__(self, a, b, bias=True, std=0.02):
  function b16 (line 86) | def b16(n, activation, resolution=224):
  class Residual (line 93) | class Residual(nn.Layer):
    method __init__ (line 95) | def __init__(self, m, drop):
    method forward (line 100) | def forward(self, x):
  class Attention (line 109) | class Attention(nn.Layer):
    method __init__ (line 111) | def __init__(self, dim, key_dim, num_heads=8, attn_ratio=4, activation...
    method train (line 140) | def train(self, mode=True):
    method forward (line 150) | def forward(self, x):
  class Subsample (line 173) | class Subsample(nn.Layer):
    method __init__ (line 175) | def __init__(self, stride, resolution):
    method forward (line 180) | def forward(self, x):
  class AttentionSubsample (line 189) | class AttentionSubsample(nn.Layer):
    method __init__ (line 191) | def __init__(self,
    method train (line 246) | def train(self, mode=True):
    method forward (line 256) | def forward(self, x):
  class LeViT (line 280) | class LeViT(nn.Layer):
    method __init__ (line 284) | def __init__(self,
    method forward (line 364) | def forward(self, x):
  function model_factory (line 381) | def model_factory(C, D, X, N, drop_path, class_num, distillation):
  function LeViT_128 (line 448) | def LeViT_128(**kwargs):

FILE: modules/image/classification/levit_128_imagenet/module.py
  class LeViT_128_ImageNet (line 42) | class LeViT_128_ImageNet:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/levit_128_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/levit_128_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/levit_128s_imagenet/model.py
  function cal_attention_biases (line 32) | def cal_attention_biases(attention_biases, attention_bias_idxs):
  class Conv2d_BN (line 44) | class Conv2d_BN(nn.Sequential):
    method __init__ (line 46) | def __init__(self, a, b, ks=1, stride=1, pad=0, dilation=1, groups=1, ...
  class Linear_BN (line 55) | class Linear_BN(nn.Sequential):
    method __init__ (line 57) | def __init__(self, a, b, bn_weight_init=1):
    method forward (line 68) | def forward(self, x):
  class BN_Linear (line 74) | class BN_Linear(nn.Sequential):
    method __init__ (line 76) | def __init__(self, a, b, bias=True, std=0.02):
  function b16 (line 86) | def b16(n, activation, resolution=224):
  class Residual (line 93) | class Residual(nn.Layer):
    method __init__ (line 95) | def __init__(self, m, drop):
    method forward (line 100) | def forward(self, x):
  class Attention (line 109) | class Attention(nn.Layer):
    method __init__ (line 111) | def __init__(self, dim, key_dim, num_heads=8, attn_ratio=4, activation...
    method train (line 140) | def train(self, mode=True):
    method forward (line 150) | def forward(self, x):
  class Subsample (line 173) | class Subsample(nn.Layer):
    method __init__ (line 175) | def __init__(self, stride, resolution):
    method forward (line 180) | def forward(self, x):
  class AttentionSubsample (line 189) | class AttentionSubsample(nn.Layer):
    method __init__ (line 191) | def __init__(self,
    method train (line 246) | def train(self, mode=True):
    method forward (line 256) | def forward(self, x):
  class LeViT (line 280) | class LeViT(nn.Layer):
    method __init__ (line 284) | def __init__(self,
    method forward (line 364) | def forward(self, x):
  function model_factory (line 381) | def model_factory(C, D, X, N, drop_path, class_num, distillation):
  function LeViT_128S (line 448) | def LeViT_128S(**kwargs):

FILE: modules/image/classification/levit_128s_imagenet/module.py
  class LeViT_128S_ImageNet (line 42) | class LeViT_128S_ImageNet:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/levit_128s_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/levit_128s_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/levit_192_imagenet/model.py
  function cal_attention_biases (line 32) | def cal_attention_biases(attention_biases, attention_bias_idxs):
  class Conv2d_BN (line 44) | class Conv2d_BN(nn.Sequential):
    method __init__ (line 46) | def __init__(self, a, b, ks=1, stride=1, pad=0, dilation=1, groups=1, ...
  class Linear_BN (line 55) | class Linear_BN(nn.Sequential):
    method __init__ (line 57) | def __init__(self, a, b, bn_weight_init=1):
    method forward (line 68) | def forward(self, x):
  class BN_Linear (line 74) | class BN_Linear(nn.Sequential):
    method __init__ (line 76) | def __init__(self, a, b, bias=True, std=0.02):
  function b16 (line 86) | def b16(n, activation, resolution=224):
  class Residual (line 93) | class Residual(nn.Layer):
    method __init__ (line 95) | def __init__(self, m, drop):
    method forward (line 100) | def forward(self, x):
  class Attention (line 109) | class Attention(nn.Layer):
    method __init__ (line 111) | def __init__(self, dim, key_dim, num_heads=8, attn_ratio=4, activation...
    method train (line 140) | def train(self, mode=True):
    method forward (line 150) | def forward(self, x):
  class Subsample (line 173) | class Subsample(nn.Layer):
    method __init__ (line 175) | def __init__(self, stride, resolution):
    method forward (line 180) | def forward(self, x):
  class AttentionSubsample (line 189) | class AttentionSubsample(nn.Layer):
    method __init__ (line 191) | def __init__(self,
    method train (line 246) | def train(self, mode=True):
    method forward (line 256) | def forward(self, x):
  class LeViT (line 280) | class LeViT(nn.Layer):
    method __init__ (line 284) | def __init__(self,
    method forward (line 364) | def forward(self, x):
  function model_factory (line 381) | def model_factory(C, D, X, N, drop_path, class_num, distillation):
  function LeViT_192 (line 448) | def LeViT_192(**kwargs):

FILE: modules/image/classification/levit_192_imagenet/module.py
  class LeViT_192_ImageNet (line 42) | class LeViT_192_ImageNet:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/levit_192_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/levit_192_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/levit_256_imagenet/model.py
  function cal_attention_biases (line 32) | def cal_attention_biases(attention_biases, attention_bias_idxs):
  class Conv2d_BN (line 44) | class Conv2d_BN(nn.Sequential):
    method __init__ (line 46) | def __init__(self, a, b, ks=1, stride=1, pad=0, dilation=1, groups=1, ...
  class Linear_BN (line 55) | class Linear_BN(nn.Sequential):
    method __init__ (line 57) | def __init__(self, a, b, bn_weight_init=1):
    method forward (line 68) | def forward(self, x):
  class BN_Linear (line 74) | class BN_Linear(nn.Sequential):
    method __init__ (line 76) | def __init__(self, a, b, bias=True, std=0.02):
  function b16 (line 86) | def b16(n, activation, resolution=224):
  class Residual (line 93) | class Residual(nn.Layer):
    method __init__ (line 95) | def __init__(self, m, drop):
    method forward (line 100) | def forward(self, x):
  class Attention (line 109) | class Attention(nn.Layer):
    method __init__ (line 111) | def __init__(self, dim, key_dim, num_heads=8, attn_ratio=4, activation...
    method train (line 140) | def train(self, mode=True):
    method forward (line 150) | def forward(self, x):
  class Subsample (line 173) | class Subsample(nn.Layer):
    method __init__ (line 175) | def __init__(self, stride, resolution):
    method forward (line 180) | def forward(self, x):
  class AttentionSubsample (line 189) | class AttentionSubsample(nn.Layer):
    method __init__ (line 191) | def __init__(self,
    method train (line 246) | def train(self, mode=True):
    method forward (line 256) | def forward(self, x):
  class LeViT (line 280) | class LeViT(nn.Layer):
    method __init__ (line 284) | def __init__(self,
    method forward (line 364) | def forward(self, x):
  function model_factory (line 381) | def model_factory(C, D, X, N, drop_path, class_num, distillation):
  function LeViT_256 (line 448) | def LeViT_256(**kwargs):

FILE: modules/image/classification/levit_256_imagenet/module.py
  class LeViT_256_ImageNet (line 42) | class LeViT_256_ImageNet:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/levit_256_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/levit_256_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/levit_384_imagenet/model.py
  function cal_attention_biases (line 32) | def cal_attention_biases(attention_biases, attention_bias_idxs):
  class Conv2d_BN (line 44) | class Conv2d_BN(nn.Sequential):
    method __init__ (line 46) | def __init__(self, a, b, ks=1, stride=1, pad=0, dilation=1, groups=1, ...
  class Linear_BN (line 55) | class Linear_BN(nn.Sequential):
    method __init__ (line 57) | def __init__(self, a, b, bn_weight_init=1):
    method forward (line 68) | def forward(self, x):
  class BN_Linear (line 74) | class BN_Linear(nn.Sequential):
    method __init__ (line 76) | def __init__(self, a, b, bias=True, std=0.02):
  function b16 (line 86) | def b16(n, activation, resolution=224):
  class Residual (line 93) | class Residual(nn.Layer):
    method __init__ (line 95) | def __init__(self, m, drop):
    method forward (line 100) | def forward(self, x):
  class Attention (line 109) | class Attention(nn.Layer):
    method __init__ (line 111) | def __init__(self, dim, key_dim, num_heads=8, attn_ratio=4, activation...
    method train (line 140) | def train(self, mode=True):
    method forward (line 150) | def forward(self, x):
  class Subsample (line 173) | class Subsample(nn.Layer):
    method __init__ (line 175) | def __init__(self, stride, resolution):
    method forward (line 180) | def forward(self, x):
  class AttentionSubsample (line 189) | class AttentionSubsample(nn.Layer):
    method __init__ (line 191) | def __init__(self,
    method train (line 246) | def train(self, mode=True):
    method forward (line 256) | def forward(self, x):
  class LeViT (line 280) | class LeViT(nn.Layer):
    method __init__ (line 284) | def __init__(self,
    method forward (line 364) | def forward(self, x):
  function model_factory (line 381) | def model_factory(C, D, X, N, drop_path, class_num, distillation):
  function LeViT_384 (line 448) | def LeViT_384(**kwargs):

FILE: modules/image/classification/levit_384_imagenet/module.py
  class LeViT_384_ImageNet (line 42) | class LeViT_384_ImageNet:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/levit_384_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/levit_384_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/marine_biometrics/module.py
  function base64_to_cv2 (line 15) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 22) | def cv2_to_base64(image):
  function read_images (line 28) | def read_images(paths):
  class MODULE (line 43) | class MODULE(hub.Module):
    method _initialize (line 44) | def _initialize(self, **kwargs):
    method predict (line 48) | def predict(self, images=None, paths=None, data=None, batch_size=1, us...
    method serving_method (line 68) | def serving_method(self, images, **kwargs):
    method run_cmd (line 97) | def run_cmd(self, argvs):
    method add_module_config_arg (line 115) | def add_module_config_arg(self):
    method add_module_input_arg (line 121) | def add_module_input_arg(self):

FILE: modules/image/classification/marine_biometrics/serving_client_demo.py
  function cv2_to_base64 (line 8) | def cv2_to_base64(image):

FILE: modules/image/classification/mobilenet_v1_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 63) | def forward(self, inputs: paddle.Tensor):
  class DepthwiseSeparable (line 69) | class DepthwiseSeparable(nn.Layer):
    method __init__ (line 72) | def __init__(self,
    method forward (line 99) | def forward(self, inputs: paddle.Tensor):
  class MobileNetV1 (line 114) | class MobileNetV1(nn.Layer):
    method __init__ (line 117) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 256) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/mobilenet_v1_imagenet_ssld/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 63) | def forward(self, inputs: paddle.Tensor):
  class DepthwiseSeparable (line 69) | class DepthwiseSeparable(nn.Layer):
    method __init__ (line 72) | def __init__(self,
    method forward (line 99) | def forward(self, inputs: paddle.Tensor):
  class MobileNetV1 (line 114) | class MobileNetV1(nn.Layer):
    method __init__ (line 117) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 256) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/mobilenet_v2_animals/data_feed.py
  function resize_short (line 16) | def resize_short(img, target_size):
  function crop_image (line 24) | def crop_image(img, target_size, center):
  function process_image (line 39) | def process_image(img):
  function reader (line 50) | def reader(images=None, paths=None):

FILE: modules/image/classification/mobilenet_v2_animals/module.py
  class MobileNetV2Animals (line 27) | class MobileNetV2Animals:
    method __init__ (line 28) | def __init__(self):
    method get_expected_image_width (line 35) | def get_expected_image_width(self):
    method get_expected_image_height (line 38) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 41) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 45) | def get_pretrained_images_std(self):
    method _set_config (line 49) | def _set_config(self):
    method classification (line 72) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 126) | def serving_method(self, images, **kwargs):
    method run_cmd (line 135) | def run_cmd(self, argvs):
    method add_module_config_arg (line 153) | def add_module_config_arg(self):
    method add_module_input_arg (line 162) | def add_module_input_arg(self):

FILE: modules/image/classification/mobilenet_v2_animals/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function softmax (line 19) | def softmax(x):
  function postprocess (line 36) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/mobilenet_v2_animals/test.py
  class TestHubModule (line 12) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 14) | def setUpClass(cls) -> None:
    method tearDownClass (line 25) | def tearDownClass(cls) -> None:
    method test_classification1 (line 29) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 45) | def test_classification3(self):
    method test_classification4 (line 54) | def test_classification4(self):
    method test_classification5 (line 61) | def test_classification5(self):
    method test_save_inference_model (line 68) | def test_save_inference_model(self):

FILE: modules/image/classification/mobilenet_v2_dishes/data_feed.py
  function resize_short (line 16) | def resize_short(img, target_size):
  function crop_image (line 24) | def crop_image(img, target_size, center):
  function process_image (line 39) | def process_image(img):
  function reader (line 50) | def reader(images=None, paths=None):

FILE: modules/image/classification/mobilenet_v2_dishes/module.py
  class MobileNetV2Dishes (line 25) | class MobileNetV2Dishes:
    method __init__ (line 26) | def __init__(self):
    method get_expected_image_width (line 34) | def get_expected_image_width(self):
    method get_expected_image_height (line 37) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 40) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 44) | def get_pretrained_images_std(self):
    method _set_config (line 48) | def _set_config(self):
    method classification (line 72) | def classification(self,
    method serving_method (line 134) | def serving_method(self, images, **kwargs):
    method run_cmd (line 143) | def run_cmd(self, argvs):
    method add_module_config_arg (line 167) | def add_module_config_arg(self):
    method add_module_input_arg (line 187) | def add_module_input_arg(self):

FILE: modules/image/classification/mobilenet_v2_dishes/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function softmax (line 19) | def softmax(x):
  function postprocess (line 36) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/mobilenet_v2_dishes/test.py
  class TestHubModule (line 12) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 14) | def setUpClass(cls) -> None:
    method tearDownClass (line 25) | def tearDownClass(cls) -> None:
    method test_classification1 (line 29) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 45) | def test_classification3(self):
    method test_classification4 (line 54) | def test_classification4(self):
    method test_classification5 (line 61) | def test_classification5(self):
    method test_save_inference_model (line 68) | def test_save_inference_model(self):

FILE: modules/image/classification/mobilenet_v2_imagenet/module.py
  class ConvBNLayer (line 26) | class ConvBNLayer(nn.Layer):
    method __init__ (line 29) | def __init__(self,
    method forward (line 56) | def forward(self, inputs: paddle.Tensor, if_act: bool = True):
  class InvertedResidualUnit (line 64) | class InvertedResidualUnit(nn.Layer):
    method __init__ (line 67) | def __init__(self, num_channels: int, num_in_filter: int, num_filters:...
    method forward (line 99) | def forward(self, inputs: paddle.Tensor, ifshortcut: bool):
  class InversiBlocks (line 108) | class InversiBlocks(nn.Layer):
    method __init__ (line 111) | def __init__(self, in_c: int, t: int, c: int, n: int, s: int, name: str):
    method forward (line 139) | def forward(self, inputs: paddle.Tensor):
  class MobileNet (line 155) | class MobileNet(nn.Layer):
    method __init__ (line 158) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 204) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/mobilenet_v2_imagenet_ssld/module.py
  class ConvBNLayer (line 26) | class ConvBNLayer(nn.Layer):
    method __init__ (line 29) | def __init__(self,
    method forward (line 56) | def forward(self, inputs: paddle.Tensor, if_act: bool = True):
  class InvertedResidualUnit (line 64) | class InvertedResidualUnit(nn.Layer):
    method __init__ (line 67) | def __init__(self, num_channels: int, num_in_filter: int, num_filters:...
    method forward (line 99) | def forward(self, inputs: paddle.Tensor, ifshortcut: bool):
  class InversiBlocks (line 108) | class InversiBlocks(nn.Layer):
    method __init__ (line 111) | def __init__(self, in_c: int, t: int, c: int, n: int, s: int, name: str):
    method forward (line 139) | def forward(self, inputs: paddle.Tensor):
  class MobileNet (line 155) | class MobileNet(nn.Layer):
    method __init__ (line 158) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 204) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/mobilenet_v3_large_imagenet_ssld/module.py
  function make_divisible (line 27) | def make_divisible(v: int, divisor: int = 8, min_value: int = None):
  class MobileNetV3Large (line 51) | class MobileNetV3Large(nn.Layer):
    method __init__ (line 54) | def __init__(self, dropout_prob: float = 0.2, class_dim: int = 1000, l...
    method forward (line 150) | def forward(self, inputs: paddle.Tensor):
  class ConvBNLayer (line 166) | class ConvBNLayer(nn.Layer):
    method __init__ (line 169) | def __init__(self,
    method forward (line 199) | def forward(self, x: paddle.Tensor):
  class ResidualUnit (line 213) | class ResidualUnit(nn.Layer):
    method __init__ (line 216) | def __init__(self,
    method forward (line 246) | def forward(self, inputs: paddle.Tensor):
  class SEModule (line 257) | class SEModule(nn.Layer):
    method __init__ (line 260) | def __init__(self, channel: int, reduction: int = 4, name: str = ""):
    method forward (line 280) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/mobilenet_v3_small_imagenet_ssld/module.py
  function make_divisible (line 27) | def make_divisible(v, divisor=8, min_value=None):
  class MobileNetV3Small (line 45) | class MobileNetV3Small(nn.Layer):
    method __init__ (line 48) | def __init__(self, dropout_prob: float = 0.2, class_dim: int = 1000, l...
    method forward (line 140) | def forward(self, inputs: paddle.Tensor):
  class ConvBNLayer (line 156) | class ConvBNLayer(nn.Layer):
    method __init__ (line 159) | def __init__(self,
    method forward (line 189) | def forward(self, x):
  class ResidualUnit (line 203) | class ResidualUnit(nn.Layer):
    method __init__ (line 206) | def __init__(self,
    method forward (line 236) | def forward(self, inputs: paddle.Tensor):
  class SEModule (line 247) | class SEModule(nn.Layer):
    method __init__ (line 250) | def __init__(self, channel: int, reduction: int = 4, name: str = ""):
    method forward (line 270) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/pplcnet_x0_25_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x0_25 (line 476) | def PPLCNet_x0_25(**kwargs):

FILE: modules/image/classification/pplcnet_x0_25_imagenet/module.py
  class PPLcNet_x0_5 (line 42) | class PPLcNet_x0_5:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x0_25_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x0_25_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/pplcnet_x0_35_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x0_35 (line 476) | def PPLCNet_x0_35(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/pplcnet_x0_35_imagenet/module.py
  class PPLcNet_x0_35 (line 42) | class PPLcNet_x0_35:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x0_35_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x0_35_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/pplcnet_x0_5_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x0_5 (line 476) | def PPLCNet_x0_5(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/pplcnet_x0_5_imagenet/module.py
  class PPLcNet_x0_5 (line 42) | class PPLcNet_x0_5:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x0_5_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x0_5_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/pplcnet_x0_75_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x0_75 (line 476) | def PPLCNet_x0_75(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/pplcnet_x0_75_imagenet/module.py
  class PPLcNet_x0_75 (line 42) | class PPLcNet_x0_75:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x0_75_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x0_75_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/pplcnet_x1_0_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x1_0 (line 476) | def PPLCNet_x1_0(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/pplcnet_x1_0_imagenet/module.py
  class PPLcNet_x1_0 (line 42) | class PPLcNet_x1_0:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x1_0_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x1_0_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/pplcnet_x1_5_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x1_5 (line 476) | def PPLCNet_x1_5(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/pplcnet_x1_5_imagenet/module.py
  class PPLcNet_x1_5 (line 42) | class PPLcNet_x1_5:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x1_5_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x1_5_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/pplcnet_x2_0_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x2_0 (line 476) | def PPLCNet_x2_0(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/pplcnet_x2_0_imagenet/module.py
  class PPLcNet_x2_0 (line 42) | class PPLcNet_x2_0:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x2_0_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x2_0_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/pplcnet_x2_5_imagenet/model.py
  class Identity (line 33) | class Identity(nn.Layer):
    method __init__ (line 35) | def __init__(self):
    method forward (line 38) | def forward(self, inputs):
  class TheseusLayer (line 42) | class TheseusLayer(nn.Layer):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method _return_dict_hook (line 51) | def _return_dict_hook(self, layer, input, output):
    method init_res (line 59) | def init_res(self, stages_pattern, return_patterns=None, return_stages...
    method replace_sub (line 78) | def replace_sub(self, *args, **kwargs) -> None:
    method upgrade_sublayer (line 82) | def upgrade_sublayer(self, layer_name_pattern: Union[str, List[str]],
    method stop_after (line 138) | def stop_after(self, stop_layer_name: str) -> bool:
    method update_res (line 162) | def update_res(self, return_patterns: Union[str, List[str]]) -> Dict[s...
  function save_sub_res_hook (line 200) | def save_sub_res_hook(layer, input, output):
  function set_identity (line 204) | def set_identity(parent_layer: nn.Layer, layer_name: str, layer_index: s...
  function parse_pattern_str (line 236) | def parse_pattern_str(pattern: str, parent_layer: nn.Layer) -> Union[Non...
  function make_divisible (line 307) | def make_divisible(v, divisor=8, min_value=None):
  class ConvBNLayer (line 316) | class ConvBNLayer(TheseusLayer):
    method __init__ (line 318) | def __init__(self, num_channels, filter_size, num_filters, stride, num...
    method forward (line 335) | def forward(self, x):
  class DepthwiseSeparable (line 342) | class DepthwiseSeparable(TheseusLayer):
    method __init__ (line 344) | def __init__(self, num_channels, num_filters, stride, dw_size=3, use_s...
    method forward (line 356) | def forward(self, x):
  class SEModule (line 364) | class SEModule(TheseusLayer):
    method __init__ (line 366) | def __init__(self, channel, reduction=4):
    method forward (line 374) | def forward(self, x):
  class PPLCNet (line 385) | class PPLCNet(TheseusLayer):
    method __init__ (line 387) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  function PPLCNet_x2_5 (line 476) | def PPLCNet_x2_5(pretrained=False, use_ssld=False, **kwargs):

FILE: modules/image/classification/pplcnet_x2_5_imagenet/module.py
  class PPLcNet_x2_5 (line 42) | class PPLcNet_x2_5:
    method __init__ (line 44) | def __init__(self):
    method classification (line 54) | def classification(self,
    method run_cmd (line 111) | def run_cmd(self, argvs: list):
    method serving_method (line 133) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 141) | def add_module_config_arg(self):
    method add_module_input_arg (line 150) | def add_module_input_arg(self):

FILE: modules/image/classification/pplcnet_x2_5_imagenet/processor.py
  function create_operators (line 36) | def create_operators(params, class_num=None):
  class UnifiedResize (line 59) | class UnifiedResize(object):
    method __init__ (line 61) | def __init__(self, interpolation=None, backend="cv2"):
    method __call__ (line 97) | def __call__(self, src, size):
  class OperatorParamError (line 101) | class OperatorParamError(ValueError):
  class DecodeImage (line 107) | class DecodeImage(object):
    method __init__ (line 110) | def __init__(self, to_rgb=True, to_np=False, channel_first=False):
    method __call__ (line 115) | def __call__(self, img):
  class ResizeImage (line 132) | class ResizeImage(object):
    method __init__ (line 135) | def __init__(self, size=None, resize_short=None, interpolation=None, b...
    method __call__ (line 150) | def __call__(self, img):
  class CropImage (line 162) | class CropImage(object):
    method __init__ (line 165) | def __init__(self, size):
    method __call__ (line 171) | def __call__(self, img):
  class RandCropImage (line 182) | class RandCropImage(object):
    method __init__ (line 185) | def __init__(self, size, scale=None, ratio=None, interpolation=None, b...
    method __call__ (line 196) | def __call__(self, img):
  class RandFlipImage (line 224) | class RandFlipImage(object):
    method __init__ (line 232) | def __init__(self, flip_code=1):
    method __call__ (line 236) | def __call__(self, img):
  class NormalizeImage (line 243) | class NormalizeImage(object):
    method __init__ (line 247) | def __init__(self, scale=None, mean=None, std=None, order='chw', outpu...
    method __call__ (line 262) | def __call__(self, img):
  class ToCHWImage (line 280) | class ToCHWImage(object):
    method __init__ (line 284) | def __init__(self):
    method __call__ (line 287) | def __call__(self, img):
  class ColorJitter (line 295) | class ColorJitter(RawColorJitter):
    method __init__ (line 299) | def __init__(self, *args, **kwargs):
    method __call__ (line 302) | def __call__(self, img):
  function base64_to_cv2 (line 312) | def base64_to_cv2(b64str):
  class Topk (line 319) | class Topk(object):
    method __init__ (line 321) | def __init__(self, topk=1, class_id_map_file=None):
    method parse_class_id_map (line 326) | def parse_class_id_map(self, class_id_map_file):
    method __call__ (line 347) | def __call__(self, x, file_names=None, multilabel=False):

FILE: modules/image/classification/pplcnet_x2_5_imagenet/utils.py
  class AttrDict (line 23) | class AttrDict(dict):
    method __getattr__ (line 25) | def __getattr__(self, key):
    method __setattr__ (line 28) | def __setattr__(self, key, value):
    method __deepcopy__ (line 34) | def __deepcopy__(self, content):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function parse_config (line 54) | def parse_config(cfg_file):
  function override (line 62) | def override(dl, ks, v):
  function override_config (line 96) | def override_config(config, options=None):
  function get_config (line 122) | def get_config(fname, overrides=None, show=False):

FILE: modules/image/classification/repvgg_a0_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_A0 (line 167) | class RepVGG_A0(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 211) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 228) | def eval(self):
    method transforms (line 234) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 243) | def forward(self, x):

FILE: modules/image/classification/repvgg_a1_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_A1 (line 167) | class RepVGG_A1(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 211) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 228) | def eval(self):
    method transforms (line 234) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 243) | def forward(self, x):

FILE: modules/image/classification/repvgg_a2_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_A2 (line 167) | class RepVGG_A2(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 211) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 228) | def eval(self):
    method transforms (line 234) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 243) | def forward(self, x):

FILE: modules/image/classification/repvgg_b0_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_B0 (line 167) | class RepVGG_B0(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 211) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 228) | def eval(self):
    method transforms (line 234) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 243) | def forward(self, x):

FILE: modules/image/classification/repvgg_b1_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_B1 (line 167) | class RepVGG_B1(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 211) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 228) | def eval(self):
    method transforms (line 234) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 243) | def forward(self, x):

FILE: modules/image/classification/repvgg_b1g2_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_B1G2 (line 167) | class RepVGG_B1G2(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 212) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 229) | def eval(self):
    method transforms (line 235) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 244) | def forward(self, x):

FILE: modules/image/classification/repvgg_b1g4_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_B1G4 (line 167) | class RepVGG_B1G4(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 212) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 229) | def eval(self):
    method transforms (line 235) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 244) | def forward(self, x):

FILE: modules/image/classification/repvgg_b2_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_B2 (line 167) | class RepVGG_B2(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 211) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 228) | def eval(self):
    method transforms (line 234) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 243) | def forward(self, x):

FILE: modules/image/classification/repvgg_b2g4_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_B2G4 (line 167) | class RepVGG_B2G4(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 212) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 229) | def eval(self):
    method transforms (line 235) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 244) | def forward(self, x):

FILE: modules/image/classification/repvgg_b3g4_imagenet/module.py
  class ConvBN (line 26) | class ConvBN(nn.Layer):
    method __init__ (line 27) | def __init__(self, in_channels, out_channels, kernel_size, stride, pad...
    method forward (line 39) | def forward(self, x):
  class RepVGGBlock (line 45) | class RepVGGBlock(nn.Layer):
    method __init__ (line 46) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):
    method eval (line 99) | def eval(self):
    method get_equivalent_kernel_bias (line 117) | def get_equivalent_kernel_bias(self):
    method _pad_1x1_to_3x3_tensor (line 123) | def _pad_1x1_to_3x3_tensor(self, kernel1x1):
    method _fuse_bn_tensor (line 129) | def _fuse_bn_tensor(self, branch):
  class RepVGG_B3G4 (line 167) | class RepVGG_B3G4(nn.Layer):
    method __init__ (line 168) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method _make_stage (line 212) | def _make_stage(self, planes, num_blocks, stride):
    method eval (line 229) | def eval(self):
    method transforms (line 235) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 244) | def forward(self, x):

FILE: modules/image/classification/res2net101_vd_26w_4s_imagenet/data_feed.py
  function resize_short (line 15) | def resize_short(img, target_size):
  function crop_image (line 23) | def crop_image(img, target_size, center):
  function process_image (line 38) | def process_image(img):
  function reader (line 49) | def reader(images=None, paths=None):

FILE: modules/image/classification/res2net101_vd_26w_4s_imagenet/module.py
  class Res2Net101vd26w4sImagenet (line 27) | class Res2Net101vd26w4sImagenet:
    method __init__ (line 29) | def __init__(self):
    method get_expected_image_width (line 37) | def get_expected_image_width(self):
    method get_expected_image_height (line 40) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 43) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 47) | def get_pretrained_images_std(self):
    method _set_config (line 51) | def _set_config(self):
    method classification (line 74) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 124) | def serving_method(self, images, **kwargs):
    method run_cmd (line 133) | def run_cmd(self, argvs):
    method add_module_config_arg (line 150) | def add_module_config_arg(self):
    method add_module_input_arg (line 161) | def add_module_input_arg(self):

FILE: modules/image/classification/res2net101_vd_26w_4s_imagenet/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function softmax (line 19) | def softmax(x):
  function postprocess (line 35) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/res2net101_vd_26w_4s_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/resnet101_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 63) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 99) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 113) | class BasicBlock(nn.Layer):
    method __init__ (line 116) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 139) | def forward(self, inputs: paddle.Tensor):
  class ResNet101 (line 160) | class ResNet101(nn.Layer):
    method __init__ (line 163) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 224) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet101_vd_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet101_vd (line 177) | class ResNet101_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 244) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet101_vd_imagenet_ssld/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet101_vd (line 177) | class ResNet101_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 244) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet152_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 63) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 99) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 113) | class BasicBlock(nn.Layer):
    method __init__ (line 116) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 139) | def forward(self, inputs: paddle.Tensor):
  class ResNet152 (line 160) | class ResNet152(nn.Layer):
    method __init__ (line 163) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 225) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet152_vd_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet152_vd (line 177) | class ResNet152_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 244) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet18_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 63) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 99) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 113) | class BasicBlock(nn.Layer):
    method __init__ (line 116) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 139) | def forward(self, inputs: paddle.Tensor):
  class ResNet18 (line 160) | class ResNet18(nn.Layer):
    method __init__ (line 163) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 218) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet18_vd_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet18_vd (line 177) | class ResNet18_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 236) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet200_vd_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet200_vd (line 177) | class ResNet200_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 244) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet34_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 63) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 99) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 113) | class BasicBlock(nn.Layer):
    method __init__ (line 116) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 139) | def forward(self, inputs: paddle.Tensor):
  class ResNet34 (line 160) | class ResNet34(nn.Layer):
    method __init__ (line 163) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 218) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet34_v2_imagenet/data_feed.py
  function resize_short (line 19) | def resize_short(img, target_size):
  function crop_image (line 27) | def crop_image(img, target_size, center):
  function process_image (line 42) | def process_image(img):
  function test_reader (line 54) | def test_reader(paths=None, images=None):

FILE: modules/image/classification/resnet34_v2_imagenet/module.py
  class ResNet34 (line 24) | class ResNet34(hub.Module):
    method _initialize (line 25) | def _initialize(self):
    method get_expected_image_width (line 32) | def get_expected_image_width(self):
    method get_expected_image_height (line 35) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 38) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 42) | def get_pretrained_images_std(self):
    method _set_config (line 46) | def _set_config(self):
    method context (line 67) | def context(self,
    method classification (line 131) | def classification(self, paths=None, images=None, use_gpu=False, batch...
    method add_module_config_arg (line 184) | def add_module_config_arg(self):
    method add_module_input_arg (line 193) | def add_module_input_arg(self):
    method check_input_data (line 200) | def check_input_data(self, args):
    method run_cmd (line 212) | def run_cmd(self, argvs):

FILE: modules/image/classification/resnet34_v2_imagenet/name_adapter.py
  class NameAdapter (line 4) | class NameAdapter(object):
    method __init__ (line 7) | def __init__(self, model):
    method model_type (line 12) | def model_type(self):
    method variant (line 16) | def variant(self):
    method fix_conv_norm_name (line 19) | def fix_conv_norm_name(self, name):
    method fix_shortcut_name (line 29) | def fix_shortcut_name(self, name):
    method fix_bottleneck_name (line 34) | def fix_bottleneck_name(self, name):
    method fix_layer_warp_name (line 47) | def fix_layer_warp_name(self, stage_num, count, i):
    method fix_c1_stage_name (line 60) | def fix_c1_stage_name(self):

FILE: modules/image/classification/resnet34_v2_imagenet/nonlocal_helper.py
  function space_nonlocal (line 25) | def space_nonlocal(input, dim_in, dim_out, prefix, dim_inner, max_pool_s...
  function add_space_nonlocal (line 144) | def add_space_nonlocal(input, dim_in, dim_out, prefix, dim_inner):

FILE: modules/image/classification/resnet34_v2_imagenet/processor.py
  function load_label_info (line 2) | def load_label_info(file_path):

FILE: modules/image/classification/resnet34_v2_imagenet/resnet.py
  class ResNet (line 22) | class ResNet(object):
    method __init__ (line 38) | def __init__(self,
    method _conv_offset (line 93) | def _conv_offset(self, input, filter_size, stride, padding, act=None, ...
    method _conv_norm (line 107) | def _conv_norm(self, input, num_filters, filter_size, stride=1, groups...
    method _shortcut (line 181) | def _shortcut(self, input, ch_out, stride, is_first, name):
    method bottleneck (line 201) | def bottleneck(self, input, num_filters, stride, is_first, name, dcn_v...
    method basicblock (line 247) | def basicblock(self, input, num_filters, stride, is_first, name, dcn_v...
    method layer_warp (line 255) | def layer_warp(self, input, stage_num):
    method c1_stage (line 299) | def c1_stage(self, input):
    method __call__ (line 319) | def __call__(self, input):
  class ResNetC5 (line 353) | class ResNetC5(ResNet):
    method __init__ (line 354) | def __init__(self,

FILE: modules/image/classification/resnet34_vd_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet34_vd (line 177) | class ResNet34_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 236) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet34_vd_imagenet_ssld/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet34_vd (line 177) | class ResNet34_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 236) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet50_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 63) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 99) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 113) | class BasicBlock(nn.Layer):
    method __init__ (line 116) | def __init__(self, num_channels: int, num_filters: int, stride: int, s...
    method forward (line 139) | def forward(self, inputs: paddle.Tensor):
  class ResNet50 (line 160) | class ResNet50(nn.Layer):
    method __init__ (line 163) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 218) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet50_v2_imagenet/data_feed.py
  function resize_short (line 19) | def resize_short(img, target_size):
  function crop_image (line 27) | def crop_image(img, target_size, center):
  function process_image (line 42) | def process_image(img):
  function test_reader (line 54) | def test_reader(paths=None, images=None):

FILE: modules/image/classification/resnet50_v2_imagenet/module.py
  class ResNet50 (line 24) | class ResNet50(hub.Module):
    method _initialize (line 25) | def _initialize(self):
    method get_expected_image_width (line 32) | def get_expected_image_width(self):
    method get_expected_image_height (line 35) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 38) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 42) | def get_pretrained_images_std(self):
    method _set_config (line 46) | def _set_config(self):
    method context (line 67) | def context(self,
    method classification (line 131) | def classification(self, paths=None, images=None, use_gpu=False, batch...
    method add_module_config_arg (line 184) | def add_module_config_arg(self):
    method add_module_input_arg (line 193) | def add_module_input_arg(self):
    method check_input_data (line 200) | def check_input_data(self, args):
    method run_cmd (line 212) | def run_cmd(self, argvs):

FILE: modules/image/classification/resnet50_v2_imagenet/name_adapter.py
  class NameAdapter (line 4) | class NameAdapter(object):
    method __init__ (line 7) | def __init__(self, model):
    method model_type (line 12) | def model_type(self):
    method variant (line 16) | def variant(self):
    method fix_conv_norm_name (line 19) | def fix_conv_norm_name(self, name):
    method fix_shortcut_name (line 29) | def fix_shortcut_name(self, name):
    method fix_bottleneck_name (line 34) | def fix_bottleneck_name(self, name):
    method fix_layer_warp_name (line 47) | def fix_layer_warp_name(self, stage_num, count, i):
    method fix_c1_stage_name (line 60) | def fix_c1_stage_name(self):

FILE: modules/image/classification/resnet50_v2_imagenet/nonlocal_helper.py
  function space_nonlocal (line 25) | def space_nonlocal(input, dim_in, dim_out, prefix, dim_inner, max_pool_s...
  function add_space_nonlocal (line 144) | def add_space_nonlocal(input, dim_in, dim_out, prefix, dim_inner):

FILE: modules/image/classification/resnet50_v2_imagenet/processor.py
  function load_label_info (line 2) | def load_label_info(file_path):

FILE: modules/image/classification/resnet50_v2_imagenet/resnet.py
  class ResNet (line 22) | class ResNet(object):
    method __init__ (line 38) | def __init__(self,
    method _conv_offset (line 93) | def _conv_offset(self, input, filter_size, stride, padding, act=None, ...
    method _conv_norm (line 107) | def _conv_norm(self, input, num_filters, filter_size, stride=1, groups...
    method _shortcut (line 181) | def _shortcut(self, input, ch_out, stride, is_first, name):
    method bottleneck (line 201) | def bottleneck(self, input, num_filters, stride, is_first, name, dcn_v...
    method basicblock (line 247) | def basicblock(self, input, num_filters, stride, is_first, name, dcn_v...
    method layer_warp (line 255) | def layer_warp(self, input, stage_num):
    method c1_stage (line 299) | def c1_stage(self, input):
    method __call__ (line 319) | def __call__(self, input):
  class ResNetC5 (line 353) | class ResNetC5(ResNet):
    method __init__ (line 354) | def __init__(self,

FILE: modules/image/classification/resnet50_vd_10w/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet50_vd (line 177) | class ResNet50_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 236) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet50_vd_animals/data_feed.py
  function resize_short (line 16) | def resize_short(img, target_size):
  function crop_image (line 24) | def crop_image(img, target_size, center):
  function process_image (line 39) | def process_image(img):
  function reader (line 50) | def reader(images=None, paths=None):

FILE: modules/image/classification/resnet50_vd_animals/module.py
  class ResNet50vdAnimals (line 28) | class ResNet50vdAnimals:
    method __init__ (line 30) | def __init__(self):
    method get_expected_image_width (line 37) | def get_expected_image_width(self):
    method get_expected_image_height (line 40) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 43) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 47) | def get_pretrained_images_std(self):
    method _get_device_id (line 51) | def _get_device_id(self, places):
    method _set_config (line 59) | def _set_config(self):
    method classification (line 101) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 168) | def serving_method(self, images, **kwargs):
    method run_cmd (line 177) | def run_cmd(self, argvs):
    method add_module_config_arg (line 198) | def add_module_config_arg(self):
    method add_module_input_arg (line 212) | def add_module_input_arg(self):

FILE: modules/image/classification/resnet50_vd_animals/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function softmax (line 19) | def softmax(x):
  function postprocess (line 35) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/resnet50_vd_animals/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/resnet50_vd_dishes/data_feed.py
  function resize_short (line 16) | def resize_short(img, target_size):
  function crop_image (line 24) | def crop_image(img, target_size, center):
  function process_image (line 39) | def process_image(img):
  function reader (line 50) | def reader(images=None, paths=None):

FILE: modules/image/classification/resnet50_vd_dishes/module.py
  class ResNet50vdDishes (line 28) | class ResNet50vdDishes:
    method __init__ (line 30) | def __init__(self):
    method get_expected_image_width (line 37) | def get_expected_image_width(self):
    method get_expected_image_height (line 40) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 43) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 47) | def get_pretrained_images_std(self):
    method _set_config (line 51) | def _set_config(self):
    method classification (line 74) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 120) | def serving_method(self, images, **kwargs):
    method run_cmd (line 129) | def run_cmd(self, argvs):
    method add_module_config_arg (line 146) | def add_module_config_arg(self):
    method add_module_input_arg (line 157) | def add_module_input_arg(self):

FILE: modules/image/classification/resnet50_vd_dishes/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function softmax (line 19) | def softmax(x):
  function postprocess (line 35) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/resnet50_vd_dishes/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/resnet50_vd_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(
    method forward (line 67) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 75) | class BottleneckBlock(nn.Layer):
    method __init__ (line 78) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 123) | class BasicBlock(nn.Layer):
    method __init__ (line 126) | def __init__(self,
    method forward (line 156) | def forward(self, inputs: paddle.Tensor):
  class ResNet50_vd (line 177) | class ResNet50_vd(nn.Layer):
    method __init__ (line 180) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 237) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet50_vd_imagenet_ssld/module.py
  class ConvBNLayer (line 31) | class ConvBNLayer(nn.Layer):
    method __init__ (line 34) | def __init__(
    method forward (line 70) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 78) | class BottleneckBlock(nn.Layer):
    method __init__ (line 81) | def __init__(self,
    method forward (line 113) | def forward(self, inputs: paddle.Tensor):
  class BasicBlock (line 127) | class BasicBlock(nn.Layer):
    method __init__ (line 130) | def __init__(self,
    method forward (line 160) | def forward(self, inputs: paddle.Tensor):
  class ResNet50_vd (line 182) | class ResNet50_vd(nn.Layer):
    method __init__ (line 185) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 250) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 259) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnet50_vd_wildanimals/data_feed.py
  function resize_short (line 15) | def resize_short(img, target_size):
  function crop_image (line 23) | def crop_image(img, target_size, center):
  function process_image (line 38) | def process_image(img):
  function reader (line 49) | def reader(images=None, paths=None):

FILE: modules/image/classification/resnet50_vd_wildanimals/module.py
  class ResNet50vdWildAnimals (line 29) | class ResNet50vdWildAnimals:
    method __init__ (line 31) | def __init__(self):
    method get_expected_image_width (line 38) | def get_expected_image_width(self):
    method get_expected_image_height (line 41) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 44) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 48) | def get_pretrained_images_std(self):
    method _set_config (line 52) | def _set_config(self):
    method classification (line 75) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 121) | def serving_method(self, images, **kwargs):
    method run_cmd (line 130) | def run_cmd(self, argvs):
    method add_module_config_arg (line 147) | def add_module_config_arg(self):
    method add_module_input_arg (line 158) | def add_module_input_arg(self):

FILE: modules/image/classification/resnet50_vd_wildanimals/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function softmax (line 19) | def softmax(x):
  function postprocess (line 35) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/resnet50_vd_wildanimals/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/resnext101_32x4d_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt101_32x4d (line 130) | class ResNeXt101_32x4d(nn.Layer):
    method __init__ (line 131) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 192) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext101_64x4d_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt101_64x4d (line 130) | class ResNeXt101_64x4d(nn.Layer):
    method __init__ (line 131) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 192) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext101_vd_32x4d_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(
    method forward (line 68) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 76) | class BottleneckBlock(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 117) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt101_vd (line 140) | class ResNeXt101_vd(nn.Layer):
    method __init__ (line 143) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 210) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext101_vd_64x4d_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(
    method forward (line 68) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 76) | class BottleneckBlock(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 117) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt101_vd (line 140) | class ResNeXt101_vd(nn.Layer):
    method __init__ (line 143) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 210) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext152_32x4d_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt152_32x4d (line 130) | class ResNeXt152_32x4d(nn.Layer):
    method __init__ (line 131) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 192) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext152_64x4d_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt152_64x4d (line 130) | class ResNeXt152_64x4d(nn.Layer):
    method __init__ (line 131) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 192) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext152_vd_32x4d_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(
    method forward (line 68) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 76) | class BottleneckBlock(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 117) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt152_vd (line 140) | class ResNeXt152_vd(nn.Layer):
    method __init__ (line 143) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 210) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext152_vd_64x4d_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(
    method forward (line 68) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 76) | class BottleneckBlock(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 117) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt152_vd (line 140) | class ResNeXt152_vd(nn.Layer):
    method __init__ (line 143) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 210) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext50_32x4d_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt50_32x4d (line 130) | class ResNeXt50_32x4d(nn.Layer):
    method __init__ (line 131) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 186) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext50_64x4d_imagenet/module.py
  class ConvBNLayer (line 28) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt50_64x4d (line 130) | class ResNeXt50_64x4d(nn.Layer):
    method __init__ (line 131) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 186) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext50_vd_32x4d_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(
    method forward (line 68) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 76) | class BottleneckBlock(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 117) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt50_vd (line 140) | class ResNeXt50_vd(nn.Layer):
    method __init__ (line 143) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 204) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/resnext50_vd_64x4d_imagenet/module.py
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(
    method forward (line 68) | def forward(self, inputs: paddle.Tensor):
  class BottleneckBlock (line 76) | class BottleneckBlock(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 117) | def forward(self, inputs: paddle.Tensor):
  class ResNeXt50_vd (line 140) | class ResNeXt50_vd(nn.Layer):
    method __init__ (line 143) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 204) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/rexnet_1_0_imagenet/module.py
  function conv_bn_act (line 27) | def conv_bn_act(out, in_channels, channels, kernel=1, stride=1, pad=0, n...
  function conv_bn_swish (line 34) | def conv_bn_swish(out, in_channels, channels, kernel=1, stride=1, pad=0,...
  class SE (line 40) | class SE(nn.Layer):
    method __init__ (line 41) | def __init__(self, in_channels, channels, se_ratio=12):
    method forward (line 49) | def forward(self, x):
  class LinearBottleneck (line 55) | class LinearBottleneck(nn.Layer):
    method __init__ (line 56) | def __init__(self, in_channels, channels, t, stride, use_se=True, se_r...
    method forward (line 86) | def forward(self, x):
  class ReXNetV1 (line 103) | class ReXNetV1(nn.Layer):
    method __init__ (line 104) | def __init__(self,
    method transforms (line 184) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 193) | def forward(self, x):

FILE: modules/image/classification/rexnet_1_3_imagenet/module.py
  function conv_bn_act (line 27) | def conv_bn_act(out, in_channels, channels, kernel=1, stride=1, pad=0, n...
  function conv_bn_swish (line 34) | def conv_bn_swish(out, in_channels, channels, kernel=1, stride=1, pad=0,...
  class SE (line 40) | class SE(nn.Layer):
    method __init__ (line 41) | def __init__(self, in_channels, channels, se_ratio=12):
    method forward (line 49) | def forward(self, x):
  class LinearBottleneck (line 55) | class LinearBottleneck(nn.Layer):
    method __init__ (line 56) | def __init__(self, in_channels, channels, t, stride, use_se=True, se_r...
    method forward (line 86) | def forward(self, x):
  class ReXNetV1 (line 103) | class ReXNetV1(nn.Layer):
    method __init__ (line 104) | def __init__(self,
    method transforms (line 184) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 193) | def forward(self, x):

FILE: modules/image/classification/rexnet_1_5_imagenet/module.py
  function conv_bn_act (line 27) | def conv_bn_act(out, in_channels, channels, kernel=1, stride=1, pad=0, n...
  function conv_bn_swish (line 34) | def conv_bn_swish(out, in_channels, channels, kernel=1, stride=1, pad=0,...
  class SE (line 40) | class SE(nn.Layer):
    method __init__ (line 41) | def __init__(self, in_channels, channels, se_ratio=12):
    method forward (line 49) | def forward(self, x):
  class LinearBottleneck (line 55) | class LinearBottleneck(nn.Layer):
    method __init__ (line 56) | def __init__(self, in_channels, channels, t, stride, use_se=True, se_r...
    method forward (line 86) | def forward(self, x):
  class ReXNetV1 (line 103) | class ReXNetV1(nn.Layer):
    method __init__ (line 104) | def __init__(self,
    method transforms (line 184) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 193) | def forward(self, x):

FILE: modules/image/classification/rexnet_2_0_imagenet/module.py
  function conv_bn_act (line 27) | def conv_bn_act(out, in_channels, channels, kernel=1, stride=1, pad=0, n...
  function conv_bn_swish (line 34) | def conv_bn_swish(out, in_channels, channels, kernel=1, stride=1, pad=0,...
  class SE (line 40) | class SE(nn.Layer):
    method __init__ (line 41) | def __init__(self, in_channels, channels, se_ratio=12):
    method forward (line 49) | def forward(self, x):
  class LinearBottleneck (line 55) | class LinearBottleneck(nn.Layer):
    method __init__ (line 56) | def __init__(self, in_channels, channels, t, stride, use_se=True, se_r...
    method forward (line 86) | def forward(self, x):
  class ReXNetV1 (line 103) | class ReXNetV1(nn.Layer):
    method __init__ (line 104) | def __init__(self,
    method transforms (line 184) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 193) | def forward(self, x):

FILE: modules/image/classification/rexnet_3_0_imagenet/module.py
  function conv_bn_act (line 27) | def conv_bn_act(out, in_channels, channels, kernel=1, stride=1, pad=0, n...
  function conv_bn_swish (line 34) | def conv_bn_swish(out, in_channels, channels, kernel=1, stride=1, pad=0,...
  class SE (line 40) | class SE(nn.Layer):
    method __init__ (line 41) | def __init__(self, in_channels, channels, se_ratio=12):
    method forward (line 49) | def forward(self, x):
  class LinearBottleneck (line 55) | class LinearBottleneck(nn.Layer):
    method __init__ (line 56) | def __init__(self, in_channels, channels, t, stride, use_se=True, se_r...
    method forward (line 86) | def forward(self, x):
  class ReXNetV1 (line 103) | class ReXNetV1(nn.Layer):
    method __init__ (line 104) | def __init__(self,
    method transforms (line 184) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 193) | def forward(self, x):

FILE: modules/image/classification/se_hrnet64_imagenet_ssld/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 31) | def __init__(self, num_channels, num_filters, filter_size, stride=1, g...
    method forward (line 52) | def forward(self, input):
  class Layer1 (line 58) | class Layer1(nn.Layer):
    method __init__ (line 59) | def __init__(self, num_channels, has_se=False, name=None):
    method forward (line 76) | def forward(self, input):
  class TransitionLayer (line 83) | class TransitionLayer(nn.Layer):
    method __init__ (line 84) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 113) | def forward(self, input):
  class Branches (line 126) | class Branches(nn.Layer):
    method __init__ (line 127) | def __init__(self, block_num, in_channels, out_channels, has_se=False,...
    method forward (line 145) | def forward(self, inputs):
  class BottleneckBlock (line 156) | class BottleneckBlock(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 192) | def forward(self, input):
  class BasicBlock (line 209) | class BasicBlock(nn.Layer):
    method __init__ (line 210) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 237) | def forward(self, input):
  class SELayer (line 253) | class SELayer(nn.Layer):
    method __init__ (line 254) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 276) | def forward(self, input):
  class Stage (line 288) | class Stage(nn.Layer):
    method __init__ (line 289) | def __init__(self, num_channels, num_modules, num_filters, has_se=Fals...
    method forward (line 314) | def forward(self, input):
  class HighResolutionModule (line 321) | class HighResolutionModule(nn.Layer):
    method __init__ (line 322) | def __init__(self, num_channels, num_filters, has_se=False, multi_scal...
    method forward (line 331) | def forward(self, input):
  class FuseLayers (line 337) | class FuseLayers(nn.Layer):
    method __init__ (line 338) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 386) | def forward(self, input):
  class LastClsOut (line 412) | class LastClsOut(nn.Layer):
    method __init__ (line 413) | def __init__(self, num_channel_list, has_se, num_filters_list=[32, 64,...
    method forward (line 428) | def forward(self, inputs):
  class SE_HRNet64 (line 445) | class SE_HRNet64(nn.Layer):
    method __init__ (line 446) | def __init__(self, label_list: list = None, load_checkpoint: str = None):
    method transforms (line 545) | def transforms(self, images: Union[str, np.ndarray]):
    method forward (line 554) | def forward(self, input):

FILE: modules/image/classification/se_resnet18_vd_imagenet/data_feed.py
  function resize_short (line 15) | def resize_short(img, target_size):
  function crop_image (line 23) | def crop_image(img, target_size, center):
  function process_image (line 38) | def process_image(img):
  function reader (line 49) | def reader(images=None, paths=None):

FILE: modules/image/classification/se_resnet18_vd_imagenet/module.py
  class SEResNet18vdImageNet (line 26) | class SEResNet18vdImageNet:
    method __init__ (line 28) | def __init__(self):
    method get_expected_image_width (line 35) | def get_expected_image_width(self):
    method get_expected_image_height (line 38) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 41) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 45) | def get_pretrained_images_std(self):
    method _set_config (line 49) | def _set_config(self):
    method classification (line 72) | def classification(self, images=None, paths=None, batch_size=1, use_gp...
    method serving_method (line 131) | def serving_method(self, images, **kwargs):
    method run_cmd (line 140) | def run_cmd(self, argvs):
    method add_module_config_arg (line 157) | def add_module_config_arg(self):
    method add_module_input_arg (line 168) | def add_module_input_arg(self):

FILE: modules/image/classification/se_resnet18_vd_imagenet/processor.py
  function base64_to_cv2 (line 11) | def base64_to_cv2(b64str):
  function softmax (line 18) | def softmax(x):
  function postprocess (line 35) | def postprocess(data_out, label_list, top_k):

FILE: modules/image/classification/se_resnet18_vd_imagenet/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_classification1 (line 31) | def test_classification1(self):
    method test_classification2 (line 37) | def test_classification2(self):
    method test_classification3 (line 43) | def test_classification3(self):
    method test_classification4 (line 49) | def test_classification4(self):
    method test_classification5 (line 52) | def test_classification5(self):
    method test_save_inference_model (line 55) | def test_save_inference_model(self):

FILE: modules/image/classification/shufflenet_v2_imagenet/module.py
  function channel_shuffle (line 28) | def channel_shuffle(x: paddle.Tensor, groups: int):
  class ConvBNLayer (line 42) | class ConvBNLayer(nn.Layer):
    method __init__ (line 45) | def __init__(self,
    method forward (line 79) | def forward(self, inputs: paddle.Tensor, if_act: bool = True):
  class InvertedResidualUnit (line 87) | class InvertedResidualUnit(nn.Layer):
    method __init__ (line 90) | def __init__(self,
    method forward (line 188) | def forward(self, inputs: paddle.Tensor):
  class ShuffleNet (line 216) | class ShuffleNet(nn.Layer):
    method __init__ (line 219) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 304) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/vgg16_imagenet/data_feed.py
  function resize_short (line 19) | def resize_short(img, target_size):
  function crop_image (line 27) | def crop_image(img, target_size, center):
  function process_image (line 42) | def process_image(img):
  function test_reader (line 54) | def test_reader(paths=None, images=None):

FILE: modules/image/classification/vgg16_imagenet/module.py
  class VGG16 (line 25) | class VGG16(hub.Module):
    method _initialize (line 26) | def _initialize(self):
    method get_expected_image_width (line 33) | def get_expected_image_width(self):
    method get_expected_image_height (line 36) | def get_expected_image_height(self):
    method get_pretrained_images_mean (line 39) | def get_pretrained_images_mean(self):
    method get_pretrained_images_std (line 43) | def get_pretrained_images_std(self):
    method _set_config (line 47) | def _set_config(self):
    method context (line 69) | def context(self,
    method classification (line 130) | def classification(self, paths=None, images=None, use_gpu=False, batch...
    method add_module_config_arg (line 182) | def add_module_config_arg(self):
    method add_module_input_arg (line 191) | def add_module_input_arg(self):
    method check_input_data (line 199) | def check_input_data(self, args):
    method run_cmd (line 211) | def run_cmd(self, argvs):

FILE: modules/image/classification/vgg16_imagenet/processor.py
  function load_label_info (line 2) | def load_label_info(file_path):

FILE: modules/image/classification/vgg16_imagenet/vgg.py
  class VGG (line 12) | class VGG(object):
    method __init__ (line 26) | def __init__(self,
    method __call__ (line 41) | def __call__(self, input):
    method _vgg_block (line 56) | def _vgg_block(self, input):
    method _add_extras_block (line 100) | def _add_extras_block(self, input):
    method _conv_block (line 111) | def _conv_block(self, input, num_filter, groups, name=None):
    method _extra_block (line 124) | def _extra_block(self, input, num_filters1, num_filters2, padding_size...
    method _conv_layer (line 140) | def _conv_layer(self,
    method _pooling_block (line 164) | def _pooling_block(self, conv, pool_size, pool_stride, pool_padding=0,...
    method _l2_norm_scale (line 174) | def _l2_norm_scale(self, input, init_scale=1.0, channel_shared=False):

FILE: modules/image/classification/xception41_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 61) | def forward(self, inputs: paddle.Tensor):
  class SeparableConv (line 67) | class SeparableConv(nn.Layer):
    method __init__ (line 70) | def __init__(self, input_channels: int, output_channels: int, stride: ...
    method forward (line 77) | def forward(self, inputs: paddle.Tensor):
  class EntryFlowBottleneckBlock (line 83) | class EntryFlowBottleneckBlock(nn.Layer):
    method __init__ (line 86) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class EntryFlow (line 119) | class EntryFlow(nn.Layer):
    method __init__ (line 122) | def __init__(self, block_num: int = 3):
    method forward (line 142) | def forward(self, inputs: paddle.Tensor):
  class MiddleFlowBottleneckBlock (line 159) | class MiddleFlowBottleneckBlock(nn.Layer):
    method __init__ (line 162) | def __init__(self, input_channels: int, output_channels: int, name: str):
    method forward (line 169) | def forward(self, inputs: paddle.Tensor):
  class MiddleFlow (line 179) | class MiddleFlow(nn.Layer):
    method __init__ (line 182) | def __init__(self, block_num: int = 8):
    method forward (line 204) | def forward(self, inputs: paddle.Tensor):
  class ExitFlowBottleneckBlock (line 225) | class ExitFlowBottleneckBlock(nn.Layer):
    method __init__ (line 228) | def __init__(self, input_channels: int, output_channels1: int, output_...
    method forward (line 243) | def forward(self, inputs: paddle.Tensor):
  class ExitFlow (line 253) | class ExitFlow(nn.Layer):
    method __init__ (line 256) | def __init__(self, class_dim: int):
    method forward (line 272) | def forward(self, inputs: paddle.Tensor):
  class Xception41 (line 293) | class Xception41(nn.Layer):
    method __init__ (line 296) | def __init__(self, class_dim: int = 1000, load_checkpoint: str = None):
    method forward (line 319) | def forward(self, inputs: paddle.Tensor):

FILE: modules/image/classification/xception65_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 61) | def forward(self, inputs: paddle.Tensor):
  class SeparableConv (line 67) | class SeparableConv(nn.Layer):
    method __init__ (line 70) | def __init__(self, input_channels: int, output_channels: int, stride: ...
    method forward (line 77) | def forward(self, inputs: paddle.Tensor):
  class EntryFlowBottleneckBlock (line 83) | class EntryFlowBottleneckBlock(nn.Layer):
    method __init__ (line 86) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class EntryFlow (line 119) | class EntryFlow(nn.Layer):
    method __init__ (line 122) | def __init__(self, block_num: int = 3):
    method forward (line 142) | def forward(self, inputs: paddle.Tensor):
  class MiddleFlowBottleneckBlock (line 159) | class MiddleFlowBottleneckBlock(nn.Layer):
    method __init__ (line 162) | def __init__(self, input_channels: int, output_channels: int, name: str):
    method forward (line 169) | def forward(self, inputs: paddle.Tensor):
  class MiddleFlow (line 179) | class MiddleFlow(nn.Layer):
    method __init__ (line 182) | def __init__(self, block_num: int = 8):
    method forward (line 204) | def forward(self, inputs: paddle.Tensor):
  class ExitFlowBottleneckBlock (line 225) | class ExitFlowBottleneckBlock(nn.Layer):
    method __init__ (line 228) | def __init__(self, input_channels, output_channels1, output_channels2,...
    method forward (line 243) | def forward(self, inputs: paddle.Tensor):
  class ExitFlow (line 253) | class ExitFlow(nn.Layer):
    method __init__ (line 256) | def __init__(self, class_dim):
    method forward (line 272) | def forward(self, inputs: paddle.Tensor):
  class Xception65 (line 293) | class Xception65(nn.Layer):
    method __init__ (line 294) | def __init__(self, class_dim=1000, load_checkpoint: str = None):
    method forward (line 317) | def forward(self, inputs):

FILE: modules/image/classification/xception71_imagenet/module.py
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 61) | def forward(self, inputs: paddle.Tensor):
  class SeparableConv (line 67) | class SeparableConv(nn.Layer):
    method __init__ (line 70) | def __init__(self, input_channels: int, output_channels: int, stride: ...
    method forward (line 77) | def forward(self, inputs: paddle.Tensor):
  class EntryFlowBottleneckBlock (line 83) | class EntryFlowBottleneckBlock(nn.Layer):
    method __init__ (line 86) | def __init__(self,
    method forward (line 107) | def forward(self, inputs: paddle.Tensor):
  class EntryFlow (line 119) | class EntryFlow(nn.Layer):
    method __init__ (line 122) | def __init__(self, block_num: int = 3):
    method forward (line 142) | def forward(self, inputs: paddle.Tensor):
  class MiddleFlowBottleneckBlock (line 159) | class MiddleFlowBottleneckBlock(nn.Layer):
    method __init__ (line 162) | def __init__(self, input_channels: int, output_channels: int, name: str):
    method forward (line 169) | def forward(self, inputs: paddle.Tensor):
  class MiddleFlow (line 179) | class MiddleFlow(nn.Layer):
    method __init__ (line 182) | def __init__(self, block_num: int = 8):
    method forward (line 204) | def forward(self, inputs: paddle.Tensor):
  class ExitFlowBottleneckBlock (line 225) | class ExitFlowBottleneckBlock(nn.Layer):
    method __init__ (line 228) | def __init__(self, input_channels: int, output_channels1: int, output_...
    method forward (line 243) | def forward(self, inputs: paddle.Tensor):
  class ExitFlow (line 253) | class ExitFlow(nn.Layer):
    method __init__ (line 254) | def __init__(self, class_dim: int):
    method forward (line 270) | def forward(self, inputs: paddle.Tensor):
  class Xception71 (line 291) | class Xception71(nn.Layer):
    method __init__ (line 292) | def __init__(self, class_dim=1000, load_checkpoint: str = None):
    method forward (line 315) | def forward(self, inputs):

FILE: modules/image/depth_estimation/MiDaS_Large/inference.py
  class InferenceModel (line 9) | class InferenceModel():
    method __init__ (line 11) | def __init__(self, modelpath, use_gpu=False, use_mkldnn=False, combine...
    method __repr__ (line 27) | def __repr__(self):
    method __call__ (line 35) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 42) | def load_config(self, modelpath, use_gpu, use_mkldnn, combined):
    method eval (line 84) | def eval(self):
    method forward (line 106) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/depth_estimation/MiDaS_Large/module.py
  class MiDaS_Large (line 22) | class MiDaS_Large(Module):
    method __init__ (line 24) | def __init__(self, name=None, directory=None, use_gpu=False):
    method load_datas (line 50) | def load_datas(paths, images):
    method preprocess (line 67) | def preprocess(self, datas):
    method postprocess (line 89) | def postprocess(datas, results, output_dir='output', visualization=Fal...
    method depth_estimation (line 110) | def depth_estimation(self, images=None, paths=None, batch_size=1, outp...

FILE: modules/image/depth_estimation/MiDaS_Large/transforms.py
  class Resize (line 7) | class Resize(object):
    method __init__ (line 11) | def __init__(self,
    method constrain_to_multiple_of (line 51) | def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
    method get_size (line 62) | def get_size(self, width, height):
    method __call__ (line 109) | def __call__(self, sample):
  class NormalizeImage (line 140) | class NormalizeImage(object):
    method __init__ (line 144) | def __init__(self, mean, std):
    method __call__ (line 148) | def __call__(self, sample):
  class PrepareForNet (line 154) | class PrepareForNet(object):
    method __init__ (line 158) | def __init__(self):
    method __call__ (line 161) | def __call__(self, sample):

FILE: modules/image/depth_estimation/MiDaS_Large/utils.py
  function write_pfm (line 9) | def write_pfm(path, image, scale=1):
  function read_image (line 46) | def read_image(path):
  function write_depth (line 62) | def write_depth(path, depth, bits=1):

FILE: modules/image/depth_estimation/MiDaS_Small/inference.py
  class InferenceModel (line 9) | class InferenceModel():
    method __init__ (line 11) | def __init__(self, modelpath, use_gpu=False, use_mkldnn=False, combine...
    method __repr__ (line 27) | def __repr__(self):
    method __call__ (line 35) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 42) | def load_config(self, modelpath, use_gpu, use_mkldnn, combined):
    method eval (line 84) | def eval(self):
    method forward (line 106) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/depth_estimation/MiDaS_Small/module.py
  class MiDaS_Small (line 22) | class MiDaS_Small(Module):
    method __init__ (line 24) | def __init__(self, name=None, directory=None, use_gpu=False):
    method load_datas (line 50) | def load_datas(paths, images):
    method preprocess (line 67) | def preprocess(self, datas):
    method postprocess (line 89) | def postprocess(datas, results, output_dir='output', visualization=Fal...
    method depth_estimation (line 110) | def depth_estimation(self, images=None, paths=None, batch_size=1, outp...

FILE: modules/image/depth_estimation/MiDaS_Small/transforms.py
  class Resize (line 7) | class Resize(object):
    method __init__ (line 11) | def __init__(self,
    method constrain_to_multiple_of (line 51) | def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
    method get_size (line 62) | def get_size(self, width, height):
    method __call__ (line 109) | def __call__(self, sample):
  class NormalizeImage (line 140) | class NormalizeImage(object):
    method __init__ (line 144) | def __init__(self, mean, std):
    method __call__ (line 148) | def __call__(self, sample):
  class PrepareForNet (line 154) | class PrepareForNet(object):
    method __init__ (line 158) | def __init__(self):
    method __call__ (line 161) | def __call__(self, sample):

FILE: modules/image/depth_estimation/MiDaS_Small/utils.py
  function write_pfm (line 9) | def write_pfm(path, image, scale=1):
  function read_image (line 46) | def read_image(path):
  function write_depth (line 62) | def write_depth(path, depth, bits=1):

FILE: modules/image/face_detection/pyramidbox_face_detection/data_feed.py
  function preprocess (line 13) | def preprocess(image):
  function to_chw_bgr (line 34) | def to_chw_bgr(image):
  function get_shrink (line 50) | def get_shrink(height, width):
  function reader (line 90) | def reader(images, paths):

FILE: modules/image/face_detection/pyramidbox_face_detection/module.py
  class PyramidBoxFaceDetection (line 27) | class PyramidBoxFaceDetection:
    method __init__ (line 28) | def __init__(self):
    method _set_config (line 32) | def _set_config(self):
    method face_detection (line 55) | def face_detection(self,
    method serving_method (line 123) | def serving_method(self, images, **kwargs):
    method run_cmd (line 132) | def run_cmd(self, argvs):
    method add_module_config_arg (line 155) | def add_module_config_arg(self):
    method add_module_input_arg (line 166) | def add_module_input_arg(self):

FILE: modules/image/face_detection/pyramidbox_face_detection/processor.py
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function check_dir (line 24) | def check_dir(dir_path):
  function get_save_image_name (line 39) | def get_save_image_name(img, org_im_path, output_dir):
  function draw_bboxes (line 58) | def draw_bboxes(image, bboxes, org_im_path, output_dir):
  function postprocess (line 74) | def postprocess(data_out, org_im, org_im_path, org_im_width, org_im_heig...

FILE: modules/image/face_detection/pyramidbox_face_detection/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_face_detection1 (line 31) | def test_face_detection1(self):
    method test_face_detection2 (line 51) | def test_face_detection2(self):
    method test_face_detection3 (line 71) | def test_face_detection3(self):
    method test_face_detection4 (line 91) | def test_face_detection4(self):
    method test_face_detection5 (line 111) | def test_face_detection5(self):
    method test_face_detection6 (line 118) | def test_face_detection6(self):
    method test_save_inference_model (line 125) | def test_save_inference_model(self):

FILE: modules/image/face_detection/pyramidbox_lite_mobile/data_feed.py
  function preprocess (line 11) | def preprocess(org_im, shrink):
  function reader (line 30) | def reader(images, paths, shrink):

FILE: modules/image/face_detection/pyramidbox_lite_mobile/module.py
  class PyramidBoxLiteMobile (line 27) | class PyramidBoxLiteMobile:
    method __init__ (line 29) | def __init__(self):
    method _set_config (line 35) | def _set_config(self):
    method face_detection (line 58) | def face_detection(self,
    method serving_method (line 130) | def serving_method(self, images, **kwargs):
    method run_cmd (line 139) | def run_cmd(self, argvs):
    method add_module_config_arg (line 161) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):
    method create_gradio_app (line 193) | def create_gradio_app(self):

FILE: modules/image/face_detection/pyramidbox_lite_mobile/processor.py
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function check_dir (line 23) | def check_dir(dir_path):
  function get_save_image_name (line 38) | def get_save_image_name(org_im, org_im_path, output_dir):
  function clip_bbox (line 59) | def clip_bbox(bbox, img_height, img_width):
  function postprocess (line 67) | def postprocess(data_out, org_im, org_im_path, image_height, image_width...

FILE: modules/image/face_detection/pyramidbox_lite_mobile/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_face_detection1 (line 31) | def test_face_detection1(self):
    method test_face_detection2 (line 51) | def test_face_detection2(self):
    method test_face_detection3 (line 71) | def test_face_detection3(self):
    method test_face_detection4 (line 91) | def test_face_detection4(self):
    method test_face_detection5 (line 111) | def test_face_detection5(self):
    method test_face_detection6 (line 118) | def test_face_detection6(self):
    method test_save_inference_model (line 125) | def test_save_inference_model(self):

FILE: modules/image/face_detection/pyramidbox_lite_mobile_mask/data_feed.py
  function bbox_vote (line 15) | def bbox_vote(det):
  function crop (line 56) | def crop(image, pts, shift=0, scale=1.5, rotate=0, res_width=128, res_he...
  function color_normalize (line 82) | def color_normalize(image, mean, std=None):
  function process_image (line 92) | def process_image(org_im, face):
  function reader (line 104) | def reader(face_detector, shrink, confs_threshold, images, paths, use_gp...

FILE: modules/image/face_detection/pyramidbox_lite_mobile_mask/module.py
  class PyramidBoxLiteMobileMask (line 30) | class PyramidBoxLiteMobileMask:
    method __init__ (line 32) | def __init__(self, face_detector_module=None):
    method _set_config (line 45) | def _set_config(self):
    method set_face_detector_module (line 68) | def set_face_detector_module(self, face_detector_module):
    method get_face_detector_module (line 76) | def get_face_detector_module(self):
    method face_detection (line 79) | def face_detection(self,
    method serving_method (line 185) | def serving_method(self, images, **kwargs):
    method run_cmd (line 194) | def run_cmd(self, argvs):
    method add_module_config_arg (line 216) | def add_module_config_arg(self):
    method add_module_input_arg (line 233) | def add_module_input_arg(self):
    method create_gradio_app (line 248) | def create_gradio_app(self):

FILE: modules/image/face_detection/pyramidbox_lite_mobile_mask/processor.py
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function check_dir (line 27) | def check_dir(dir_path):
  function get_save_image_name (line 42) | def get_save_image_name(org_im, org_im_path, output_dir):
  function draw_bounding_box_on_image (line 65) | def draw_bounding_box_on_image(save_im_path, output_data):
  function postprocess (line 97) | def postprocess(confidence_out, org_im, org_im_path, detected_faces, out...

FILE: modules/image/face_detection/pyramidbox_lite_mobile_mask/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_face_detection1 (line 32) | def test_face_detection1(self):
    method test_face_detection2 (line 50) | def test_face_detection2(self):
    method test_face_detection3 (line 68) | def test_face_detection3(self):
    method test_face_detection4 (line 86) | def test_face_detection4(self):
    method test_face_detection5 (line 104) | def test_face_detection5(self):
    method test_face_detection6 (line 107) | def test_face_detection6(self):
    method test_save_inference_model (line 110) | def test_save_inference_model(self):

FILE: modules/image/face_detection/pyramidbox_lite_server/data_feed.py
  function preprocess (line 11) | def preprocess(org_im, shrink):
  function reader (line 30) | def reader(images, paths, shrink):

FILE: modules/image/face_detection/pyramidbox_lite_server/module.py
  class PyramidBoxLiteServer (line 26) | class PyramidBoxLiteServer:
    method __init__ (line 28) | def __init__(self):
    method _set_config (line 34) | def _set_config(self):
    method face_detection (line 57) | def face_detection(self,
    method serving_method (line 129) | def serving_method(self, images, **kwargs):
    method run_cmd (line 138) | def run_cmd(self, argvs):
    method add_module_config_arg (line 160) | def add_module_config_arg(self):
    method add_module_input_arg (line 177) | def add_module_input_arg(self):
    method create_gradio_app (line 192) | def create_gradio_app(self):

FILE: modules/image/face_detection/pyramidbox_lite_server/processor.py
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function check_dir (line 23) | def check_dir(dir_path):
  function get_save_image_name (line 38) | def get_save_image_name(org_im, org_im_path, output_dir):
  function clip_bbox (line 59) | def clip_bbox(bbox, img_height, img_width):
  function postprocess (line 67) | def postprocess(data_out, org_im, org_im_path, image_height, image_width...

FILE: modules/image/face_detection/pyramidbox_lite_server/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_face_detection1 (line 31) | def test_face_detection1(self):
    method test_face_detection2 (line 51) | def test_face_detection2(self):
    method test_face_detection3 (line 71) | def test_face_detection3(self):
    method test_face_detection4 (line 91) | def test_face_detection4(self):
    method test_face_detection5 (line 111) | def test_face_detection5(self):
    method test_face_detection6 (line 118) | def test_face_detection6(self):
    method test_save_inference_model (line 125) | def test_save_inference_model(self):

FILE: modules/image/face_detection/pyramidbox_lite_server_mask/data_feed.py
  function bbox_vote (line 15) | def bbox_vote(det):
  function crop (line 56) | def crop(image, pts, shift=0, scale=1.5, rotate=0, res_width=128, res_he...
  function color_normalize (line 82) | def color_normalize(image, mean, std=None):
  function process_image (line 92) | def process_image(org_im, face):
  function reader (line 104) | def reader(face_detector, shrink, confs_threshold, images, paths, use_gp...

FILE: modules/image/face_detection/pyramidbox_lite_server_mask/module.py
  class PyramidBoxLiteServerMask (line 31) | class PyramidBoxLiteServerMask:
    method __init__ (line 33) | def __init__(self, face_detector_module=None):
    method _set_config (line 46) | def _set_config(self):
    method set_face_detector_module (line 69) | def set_face_detector_module(self, face_detector_module):
    method get_face_detector_module (line 77) | def get_face_detector_module(self):
    method face_detection (line 80) | def face_detection(self,
    method serving_method (line 185) | def serving_method(self, images, **kwargs):
    method run_cmd (line 194) | def run_cmd(self, argvs):
    method add_module_config_arg (line 216) | def add_module_config_arg(self):
    method add_module_input_arg (line 233) | def add_module_input_arg(self):
    method create_gradio_app (line 248) | def create_gradio_app(self):

FILE: modules/image/face_detection/pyramidbox_lite_server_mask/processor.py
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):
  function check_dir (line 27) | def check_dir(dir_path):
  function get_save_image_name (line 42) | def get_save_image_name(org_im, org_im_path, output_dir):
  function draw_bounding_box_on_image (line 65) | def draw_bounding_box_on_image(save_im_path, output_data):
  function postprocess (line 97) | def postprocess(confidence_out, org_im, org_im_path, detected_faces, out...

FILE: modules/image/face_detection/pyramidbox_lite_server_mask/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_face_detection1 (line 32) | def test_face_detection1(self):
    method test_face_detection2 (line 50) | def test_face_detection2(self):
    method test_face_detection3 (line 68) | def test_face_detection3(self):
    method test_face_detection4 (line 86) | def test_face_detection4(self):
    method test_face_detection5 (line 104) | def test_face_detection5(self):
    method test_face_detection6 (line 107) | def test_face_detection6(self):
    method test_save_inference_model (line 110) | def test_save_inference_model(self):

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/data_feed.py
  function preprocess (line 11) | def preprocess(orig_image):
  function reader (line 20) | def reader(images=None, paths=None):

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/module.py
  class FaceDetector320 (line 30) | class FaceDetector320:
    method __init__ (line 31) | def __init__(self):
    method _set_config (line 36) | def _set_config(self):
    method face_detection (line 59) | def face_detection(self,
    method serving_method (line 147) | def serving_method(self, images, **kwargs):
    method run_cmd (line 156) | def run_cmd(self, argvs):
    method add_module_config_arg (line 177) | def add_module_config_arg(self):
    method add_module_input_arg (line 195) | def add_module_input_arg(self):

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/processor.py
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function area_of (line 23) | def area_of(left_top, right_bottom):
  function iou_of (line 28) | def iou_of(boxes0, boxes1, eps=1e-5):
  function hard_nms (line 37) | def hard_nms(box_scores, iou_threshold, top_k=-1, candidate_size=200):
  function check_dir (line 60) | def check_dir(dir_path):
  function get_image_ext (line 68) | def get_image_ext(image):
  function postprocess (line 74) | def postprocess(confidences,

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_face_detection1 (line 31) | def test_face_detection1(self):
    method test_face_detection2 (line 51) | def test_face_detection2(self):
    method test_face_detection3 (line 71) | def test_face_detection3(self):
    method test_face_detection4 (line 91) | def test_face_detection4(self):
    method test_face_detection5 (line 111) | def test_face_detection5(self):
    method test_face_detection6 (line 118) | def test_face_detection6(self):
    method test_save_inference_model (line 125) | def test_save_inference_model(self):

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/data_feed.py
  function preprocess (line 11) | def preprocess(orig_image):
  function reader (line 20) | def reader(images=None, paths=None):

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/module.py
  class FaceDetector640 (line 31) | class FaceDetector640:
    method __init__ (line 32) | def __init__(self):
    method _set_config (line 37) | def _set_config(self):
    method face_detection (line 60) | def face_detection(self,
    method serving_method (line 147) | def serving_method(self, images, **kwargs):
    method run_cmd (line 156) | def run_cmd(self, argvs):
    method add_module_config_arg (line 177) | def add_module_config_arg(self):
    method add_module_input_arg (line 195) | def add_module_input_arg(self):

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/processor.py
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function area_of (line 23) | def area_of(left_top, right_bottom):
  function iou_of (line 28) | def iou_of(boxes0, boxes1, eps=1e-5):
  function hard_nms (line 37) | def hard_nms(box_scores, iou_threshold, top_k=-1, candidate_size=200):
  function check_dir (line 60) | def check_dir(dir_path):
  function get_image_ext (line 68) | def get_image_ext(image):
  function postprocess (line 74) | def postprocess(confidences,

FILE: modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_face_detection1 (line 31) | def test_face_detection1(self):
    method test_face_detection2 (line 51) | def test_face_detection2(self):
    method test_face_detection3 (line 71) | def test_face_detection3(self):
    method test_face_detection4 (line 91) | def test_face_detection4(self):
    method test_face_detection5 (line 111) | def test_face_detection5(self):
    method test_face_detection6 (line 118) | def test_face_detection6(self):
    method test_save_inference_model (line 125) | def test_save_inference_model(self):

FILE: modules/image/image_processing/enlightengan/enlighten_inference/pd_model/x2paddle_code.py
  class ONNXModel (line 5) | class ONNXModel(paddle.nn.Layer):
    method __init__ (line 6) | def __init__(self):
    method forward (line 93) | def forward(self, x2paddle_input):

FILE: modules/image/image_processing/enlightengan/module.py
  class EnlightenGAN (line 35) | class EnlightenGAN:
    method __init__ (line 37) | def __init__(self):
    method enlightening (line 43) | def enlightening(self,
    method run_cmd (line 100) | def run_cmd(self, argvs: list):
    method serving_method (line 122) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 131) | def add_module_config_arg(self):
    method add_module_input_arg (line 143) | def add_module_input_arg(self):

FILE: modules/image/image_processing/enlightengan/util.py
  function base64_to_cv2 (line 7) | def base64_to_cv2(b64str):

FILE: modules/image/image_processing/prnet/api.py
  class PRN (line 27) | class PRN:
    method __init__ (line 34) | def __init__(self, is_dlib=False, prefix='.'):
    method generate_uv_coords (line 59) | def generate_uv_coords(self):
    method dlib_detect (line 68) | def dlib_detect(self, image):
    method net_forward (line 71) | def net_forward(self, image):
    method process (line 80) | def process(self, input, image_info=None):
    method get_landmarks (line 156) | def get_landmarks(self, pos):
    method get_vertices (line 166) | def get_vertices(self, pos):
    method get_colors_from_texture (line 178) | def get_colors_from_texture(self, texture):
    method get_colors (line 190) | def get_colors(self, image, vertices):

FILE: modules/image/image_processing/prnet/module.py
  class PRNet (line 36) | class PRNet:
    method __init__ (line 37) | def __init__(self):
    method face_swap (line 41) | def face_swap(self,
    method texture_editing (line 90) | def texture_editing(self, source_img, ref_img, mode):
    method run_cmd (line 171) | def run_cmd(self, argvs: list):
    method serving_method (line 199) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 211) | def add_module_config_arg(self):
    method add_module_input_arg (line 223) | def add_module_input_arg(self):

FILE: modules/image/image_processing/prnet/pd_model/x2paddle_code.py
  class TFModel (line 5) | class TFModel(paddle.nn.Layer):
    method __init__ (line 6) | def __init__(self):
    method forward (line 862) | def forward(self, Placeholder):
  function main (line 1532) | def main(Placeholder):

FILE: modules/image/image_processing/prnet/predictor.py
  class PosPrediction (line 20) | class PosPrediction():
    method __init__ (line 21) | def __init__(self, params, resolution_inp=256, resolution_op=256):
    method predict (line 32) | def predict(self, image):
    method predict_batch (line 40) | def predict_batch(self, images):

FILE: modules/image/image_processing/prnet/util.py
  function base64_to_cv2 (line 20) | def base64_to_cv2(b64str):

FILE: modules/image/image_processing/prnet/utils/cv_plot.py
  function plot_kpt (line 20) | def plot_kpt(image, kpt):
  function plot_vertices (line 38) | def plot_vertices(image, vertices):
  function plot_pose_box (line 47) | def plot_pose_box(image, P, kpt, color=(0, 255, 0), line_width=2):

FILE: modules/image/image_processing/prnet/utils/estimate_pose.py
  function isRotationMatrix (line 22) | def isRotationMatrix(R):
  function matrix2angle (line 32) | def matrix2angle(R):
  function P2sRt (line 60) | def P2sRt(P):
  function compute_similarity_transform (line 81) | def compute_similarity_transform(points_static, points_to_transform):
  function estimate_pose (line 107) | def estimate_pose(vertices):

FILE: modules/image/image_processing/prnet/utils/render.py
  function isPointInTri (line 8) | def isPointInTri(point, tri_points):
  function get_point_weight (line 45) | def get_point_weight(point, tri_points):
  function render_texture (line 87) | def render_texture(vertices, colors, triangles, h, w, c=3):
  function map_texture (line 125) | def map_texture(src_image,
  function get_depth_buffer (line 200) | def get_depth_buffer(vertices, triangles, h, w):
  function get_triangle_buffer (line 250) | def get_triangle_buffer(vertices, triangles, h, w):
  function vis_of_vertices (line 302) | def vis_of_vertices(vertices, triangles, h, w, depth_buffer=None):

FILE: modules/image/image_processing/prnet/utils/render_app.py
  function get_visibility (line 20) | def get_visibility(vertices, triangles, h, w):
  function get_uv_mask (line 36) | def get_uv_mask(vertices_vis, triangles, uv_coords, h, w, resolution):
  function get_depth_image (line 52) | def get_depth_image(vertices, triangles, h, w, isShow=False):

FILE: modules/image/image_processing/prnet/utils/rotate_vertices.py
  function frontalize (line 18) | def frontalize(vertices):

FILE: modules/image/image_processing/prnet/utils/write.py
  function write_asc (line 20) | def write_asc(path, vertices):
  function write_obj_with_colors (line 31) | def write_obj_with_colors(obj_name, vertices, triangles, colors):
  function write_obj_with_texture (line 63) | def write_obj_with_texture(obj_name, vertices, triangles, texture, uv_co...
  function write_obj_with_colors_texture (line 116) | def write_obj_with_colors_texture(obj_name, vertices, colors, triangles,...

FILE: modules/image/image_processing/seeinthedark/module.py
  function pack_raw (line 28) | def pack_raw(raw):
  class LearningToSeeInDark (line 46) | class LearningToSeeInDark:
    method __init__ (line 47) | def __init__(self):
    method set_device (line 52) | def set_device(self, use_gpu=False):
    method denoising (line 79) | def denoising(self,
    method run_cmd (line 147) | def run_cmd(self, argvs: list):
    method serving_method (line 170) | def serving_method(self, images, **kwargs):
    method add_module_config_arg (line 179) | def add_module_config_arg(self):
    method add_module_input_arg (line 189) | def add_module_input_arg(self):

FILE: modules/image/industrial_application/meter_readings/barometer_reader/module.py
  function base64_to_cv2 (line 33) | def base64_to_cv2(b64str: str):
  function cv2_to_base64 (line 40) | def cv2_to_base64(image: np.ndarray):
  class BarometerReader (line 54) | class BarometerReader(nn.Layer):
    method __init__ (line 55) | def __init__(self):
    method read_process (line 61) | def read_process(self, label_maps: np.ndarray):
    method creat_line_image (line 68) | def creat_line_image(self, meter_image: np.ndarray):
    method convert_1d_data (line 79) | def convert_1d_data(self, meter_image: np.ndarray):
    method scale_mean_filtration (line 90) | def scale_mean_filtration(self, scale_data: np.ndarray):
    method get_meter_reader (line 96) | def get_meter_reader(self, scale_data: np.ndarray, pointer_data: np.nd...
    method predict (line 142) | def predict(self,
    method serving_method (line 220) | def serving_method(self, image: str, **kwargs):
    method run_cmd (line 235) | def run_cmd(self, argvs: list):
    method add_module_input_arg (line 252) | def add_module_input_arg(self):

FILE: modules/image/instance_segmentation/solov2/data_feed.py
  function create_inputs (line 12) | def create_inputs(im, im_info):
  function visualize_box_mask (line 34) | def visualize_box_mask(im, results, labels=None, mask_resolution=14, thr...
  function get_color_map_list (line 74) | def get_color_map_list(num_classes):
  function expand_boxes (line 95) | def expand_boxes(boxes, scale=0.0):
  function draw_mask (line 118) | def draw_mask(im, np_boxes, np_masks, labels, resolution=14, threshold=0...
  function draw_box (line 172) | def draw_box(im, np_boxes, labels):
  function draw_segm (line 209) | def draw_segm(im, np_segms, np_label, np_score, labels, threshold=0.5, a...
  function load_predictor (line 248) | def load_predictor(model_dir, run_mode='paddle', batch_size=1, use_gpu=F...
  function cv2_to_base64 (line 292) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 297) | def base64_to_cv2(b64str: str):

FILE: modules/image/instance_segmentation/solov2/module.py
  class Detector (line 28) | class Detector:
    method __init__ (line 36) | def __init__(self, min_subgraph_size: int = 60, use_gpu=False):
    method transform (line 49) | def transform(self, im: Union[str, np.ndarray]):
    method postprocess (line 54) | def postprocess(self, np_boxes: np.ndarray, np_masks: np.ndarray, thre...
    method predict (line 69) | def predict(self, image: Union[str, np.ndarray], threshold: float = 0.5):
  class DetectorSOLOv2 (line 108) | class DetectorSOLOv2(Detector):
    method __init__ (line 115) | def __init__(self, use_gpu: bool = False):
    method predict (line 118) | def predict(self,
    method serving_method (line 157) | def serving_method(self, images: list, **kwargs):
    method create_gradio_app (line 169) | def create_gradio_app(self):

FILE: modules/image/instance_segmentation/solov2/processor.py
  function decode_image (line 19) | def decode_image(im_file, im_info):
  class Resize (line 44) | class Resize(object):
    method __init__ (line 55) | def __init__(self,
    method __call__ (line 68) | def __call__(self, im, im_info):
    method generate_scale (line 103) | def generate_scale(self, im):
  class Normalize (line 127) | class Normalize(object):
    method __init__ (line 136) | def __init__(self, mean, std, is_scale=True, is_channel_first=False):
    method __call__ (line 142) | def __call__(self, im, im_info):
  class Permute (line 165) | class Permute(object):
    method __init__ (line 172) | def __init__(self, to_bgr=False, channel_first=True):
    method __call__ (line 176) | def __call__(self, im, im_info):
  class PadStride (line 192) | class PadStride(object):
    method __init__ (line 198) | def __init__(self, stride=0):
    method __call__ (line 201) | def __call__(self, im, im_info):
  function preprocess (line 222) | def preprocess(im, preprocess_ops):

FILE: modules/image/instance_segmentation/solov2/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_predict1 (line 33) | def test_predict1(self):
    method test_predict2 (line 42) | def test_predict2(self):
    method test_predict3 (line 51) | def test_predict3(self):
    method test_predict4 (line 60) | def test_predict4(self):
    method test_predict5 (line 70) | def test_predict5(self):
    method test_save_inference_model (line 73) | def test_save_inference_model(self):

FILE: modules/image/keypoint_detection/face_landmark_localization/data_feed.py
  function reader (line 11) | def reader(face_detector, images=None, paths=None, use_gpu=False):

FILE: modules/image/keypoint_detection/face_landmark_localization/module.py
  class FaceLandmarkLocalization (line 33) | class FaceLandmarkLocalization:
    method __init__ (line 34) | def __init__(self, face_detector_module=None):
    method _set_config (line 46) | def _set_config(self):
    method set_face_detector_module (line 69) | def set_face_detector_module(self, face_detector_module):
    method get_face_detector_module (line 78) | def get_face_detector_module(self):
    method keypoint_detection (line 81) | def keypoint_detection(self,
    method serving_method (line 148) | def serving_method(self, images, **kwargs):
    method run_cmd (line 157) | def run_cmd(self, argvs):
    method add_module_config_arg (line 178) | def add_module_config_arg(self):
    method add_module_input_arg (line 195) | def add_module_input_arg(self):

FILE: modules/image/keypoint_detection/face_landmark_localization/processor.py
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function check_dir (line 23) | def check_dir(dir_path):
  function get_image_ext (line 31) | def get_image_ext(image):
  function postprocess (line 37) | def postprocess(res, output_dir, visualization):

FILE: modules/image/keypoint_detection/face_landmark_localization/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_keypoint_detection1 (line 31) | def test_keypoint_detection1(self):
    method test_keypoint_detection2 (line 40) | def test_keypoint_detection2(self):
    method test_keypoint_detection3 (line 49) | def test_keypoint_detection3(self):
    method test_keypoint_detection4 (line 58) | def test_keypoint_detection4(self):
    method test_keypoint_detection5 (line 67) | def test_keypoint_detection5(self):
    method test_keypoint_detection6 (line 74) | def test_keypoint_detection6(self):
    method test_save_inference_model (line 81) | def test_save_inference_model(self):

FILE: modules/image/keypoint_detection/hand_pose_localization/model.py
  class InferenceModel (line 9) | class InferenceModel:
    method __init__ (line 11) | def __init__(self,
    method __repr__ (line 27) | def __repr__(self):
    method __call__ (line 39) | def __call__(self, *input_datas, batch_size=1):
    method load_config (line 46) | def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_thre...
    method eval (line 105) | def eval(self):
    method forward (line 133) | def forward(self, *input_datas, batch_size=1):

FILE: modules/image/keypoint_detection/hand_pose_localization/module.py
  class Hand_Pose_Localization (line 19) | class Hand_Pose_Localization:
    method __init__ (line 21) | def __init__(self, use_gpu=False):
    method keypoint_detection (line 31) | def keypoint_detection(self, images=None, paths=None, batch_size=1, ou...
    method serving_method (line 50) | def serving_method(self, images, **kwargs):

FILE: modules/image/keypoint_detection/hand_pose_localization/processor.py
  function check_dir (line 10) | def check_dir(dir_path):
  function base64_to_cv2 (line 19) | def base64_to_cv2(b64str):
  class Processor (line 27) | class Processor():
    method __init__ (line 29) | def __init__(self, images=None, paths=None, batch_size=1, output_dir='...
    method load_datas (line 49) | def load_datas(self):
    method preprocess (line 66) | def preprocess(self):
    method postprocess (line 88) | def postprocess(self, outputs, visualization):
    method vis_pose (line 118) | def vis_pose(self, img, points, im_id):

FILE: modules/image/keypoint_detection/hand_pose_localization/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_keypoint_detection1 (line 30) | def test_keypoint_detection1(self):
    method test_keypoint_detection2 (line 38) | def test_keypoint_detection2(self):
    method test_keypoint_detection3 (line 46) | def test_keypoint_detection3(self):
    method test_keypoint_detection4 (line 54) | def test_keypoint_detection4(self):
    method test_keypoint_detection5 (line 63) | def test_keypoint_detection5(self):
    method test_keypoint_detection6 (line 70) | def test_keypoint_detection6(self):

FILE: modules/image/keypoint_detection/human_pose_estimation_resnet50_mpii/data_feed.py
  function reader (line 12) | def reader(images=None, paths=None):

FILE: modules/image/keypoint_detection/human_pose_estimation_resnet50_mpii/module.py
  class HumanPoseEstimation (line 28) | class HumanPoseEstimation:
    method __init__ (line 29) | def __init__(self):
    method _set_config (line 33) | def _set_config(self):
    method keypoint_detection (line 56) | def keypoint_detection(self,
    method serving_method (line 117) | def serving_method(self, images, **kwargs):
    method run_cmd (line 126) | def run_cmd(self, argvs):
    method add_module_config_arg (line 150) | def add_module_config_arg(self):
    method add_module_input_arg (line 162) | def add_module_input_arg(self):

FILE: modules/image/keypoint_detection/human_pose_estimation_resnet50_mpii/processor.py
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function get_max_preds (line 24) | def get_max_preds(batch_heatmaps):
  function predict_results (line 52) | def predict_results(batch_heatmaps):
  function postprocess (line 58) | def postprocess(out_heatmaps, org_im, org_im_shape, org_im_path, output_...
  function check_dir (line 117) | def check_dir(dir_path):
  function get_save_image_name (line 131) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/keypoint_detection/human_pose_estimation_resnet50_mpii/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_keypoint_detection1 (line 31) | def test_keypoint_detection1(self):
    method test_keypoint_detection2 (line 38) | def test_keypoint_detection2(self):
    method test_keypoint_detection3 (line 45) | def test_keypoint_detection3(self):
    method test_keypoint_detection4 (line 53) | def test_keypoint_detection4(self):
    method test_keypoint_detection5 (line 61) | def test_keypoint_detection5(self):
    method test_keypoint_detection6 (line 68) | def test_keypoint_detection6(self):
    method test_save_inference_model (line 75) | def test_save_inference_model(self):

FILE: modules/image/keypoint_detection/openpose_body_estimation/module.py
  class BodyPoseModel (line 39) | class BodyPoseModel(nn.Layer):
    method __init__ (line 47) | def __init__(self, load_checkpoint: str = None):
    method make_layers (line 130) | def make_layers(self, block: dict, no_relu_layers: list):
    method transform (line 144) | def transform(self, orgimg: np.ndarray, scale_search: float = 0.5):
    method forward (line 152) | def forward(self, x: paddle.Tensor):
    method predict (line 181) | def predict(self, img: Union[str, np.ndarray], save_path: str = "openp...
    method serving_method (line 214) | def serving_method(self, images: list, **kwargs):
    method run_cmd (line 228) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 247) | def add_module_config_arg(self):
    method add_module_input_arg (line 257) | def add_module_input_arg(self):

FILE: modules/image/keypoint_detection/openpose_body_estimation/processor.py
  class PadDownRight (line 10) | class PadDownRight:
    method __init__ (line 19) | def __init__(self, stride: int = 8, padValue: int = 128):
    method __call__ (line 23) | def __call__(self, img: np.ndarray):
  class RemovePadding (line 42) | class RemovePadding:
    method __init__ (line 51) | def __init__(self, stride: int = 8):
    method __call__ (line 54) | def __call__(self, data: np.ndarray, imageToTest_padded: np.ndarray, o...
  class GetPeak (line 63) | class GetPeak:
    method __init__ (line 71) | def __init__(self, thresh=0.1):
    method __call__ (line 74) | def __call__(self, heatmap: np.ndarray):
  class Connection (line 104) | class Connection:
    method __init__ (line 114) | def __init__(self, mapIdx: list = None, limbSeq: list = None):
    method __call__ (line 128) | def __call__(self, all_peaks: list, paf_avg: np.ndarray, orgimg: np.nd...
  class CalculateVector (line 156) | class CalculateVector:
    method __init__ (line 165) | def __init__(self, thresh: float = 0.05):
    method __call__ (line 168) | def __call__(self, candA: list, candB: list, nA: int, nB: int, score_m...
  class DrawPose (line 194) | class DrawPose:
    method __init__ (line 203) | def __init__(self, stickwidth: int = 4):
    method __call__ (line 214) | def __call__(self, canvas: np.ndarray, candidate: np.ndarray, subset: ...
  class Candidate (line 241) | class Candidate:
    method __init__ (line 250) | def __init__(self, mapIdx: list = None, limbSeq: list = None):
    method __call__ (line 262) | def __call__(self, all_peaks: list, connection_all: list, special_k: l...
  class ResizeScaling (line 316) | class ResizeScaling:
    method __init__ (line 324) | def __init__(self, target: int = 368, interpolation: Callable = cv2.IN...
    method __call__ (line 328) | def __call__(self, img, scale_search):
  function cv2_to_base64 (line 334) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 339) | def base64_to_cv2(b64str: str):

FILE: modules/image/keypoint_detection/openpose_body_estimation/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_predict1 (line 31) | def test_predict1(self):
    method test_predict2 (line 39) | def test_predict2(self):
    method test_predict3 (line 47) | def test_predict3(self):
    method test_predict4 (line 55) | def test_predict4(self):
    method test_predict5 (line 62) | def test_predict5(self):
    method test_save_inference_model (line 69) | def test_save_inference_model(self):

FILE: modules/image/keypoint_detection/openpose_hands_estimation/module.py
  class HandPoseModel (line 43) | class HandPoseModel(nn.Layer):
    method __init__ (line 51) | def __init__(self, load_checkpoint: str = None):
    method make_layers (line 113) | def make_layers(self, block: dict, no_relu_layers: list):
    method forward (line 127) | def forward(self, x: paddle.Tensor):
    method hand_estimation (line 142) | def hand_estimation(self, handimg: np.ndarray, scale_search: list):
    method predict (line 172) | def predict(self,
    method serving_method (line 217) | def serving_method(self, images: list, **kwargs):
    method run_cmd (line 229) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 249) | def add_module_config_arg(self):
    method add_module_input_arg (line 261) | def add_module_input_arg(self):

FILE: modules/image/keypoint_detection/openpose_hands_estimation/processor.py
  class HandDetect (line 15) | class HandDetect:
    method __init__ (line 23) | def __init__(self, ratioWristElbow: float = 0.33):
    method __call__ (line 26) | def __call__(self, candidate: np.ndarray, subset: np.ndarray, oriImg: ...
  class PadDownRight (line 75) | class PadDownRight:
    method __init__ (line 84) | def __init__(self, stride: int = 8, padValue: int = 128):
    method __call__ (line 88) | def __call__(self, img: np.ndarray):
  class RemovePadding (line 107) | class RemovePadding:
    method __init__ (line 116) | def __init__(self, stride: int = 8):
    method __call__ (line 119) | def __call__(self, data: np.ndarray, imageToTest_padded: np.ndarray, o...
  class DrawPose (line 128) | class DrawPose:
    method __init__ (line 137) | def __init__(self, stickwidth: int = 4):
    method __call__ (line 148) | def __call__(self, canvas: np.ndarray, candidate: np.ndarray, subset: ...
  class DrawHandPose (line 175) | class DrawHandPose:
    method __init__ (line 183) | def __init__(self, show_number: bool = False):
    method __call__ (line 188) | def __call__(self, canvas: np.ndarray, all_hand_peaks: list):
  class ResizeScaling (line 218) | class ResizeScaling:
    method __init__ (line 226) | def __init__(self, target: int = 368, interpolation: Callable = cv2.IN...
    method __call__ (line 230) | def __call__(self, img, scale_search):
  function npmax (line 236) | def npmax(array: np.ndarray):
  function cv2_to_base64 (line 245) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 250) | def base64_to_cv2(b64str: str):

FILE: modules/image/keypoint_detection/openpose_hands_estimation/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_predict1 (line 32) | def test_predict1(self):
    method test_predict2 (line 40) | def test_predict2(self):
    method test_predict3 (line 48) | def test_predict3(self):
    method test_predict4 (line 56) | def test_predict4(self):
    method test_predict5 (line 63) | def test_predict5(self):
    method test_save_inference_model (line 70) | def test_save_inference_model(self):

FILE: modules/image/keypoint_detection/pp-tinypose/det_keypoint_unite_infer.py
  function predict_with_given_det (line 21) | def predict_with_given_det(image, det_res, keypoint_detector, keypoint_b...

FILE: modules/image/keypoint_detection/pp-tinypose/infer.py
  class Detector (line 64) | class Detector(object):
    method __init__ (line 86) | def __init__(self,
    method set_config (line 122) | def set_config(self, model_dir):
    method preprocess (line 125) | def preprocess(self, image_list):
    method postprocess (line 146) | def postprocess(self, inputs, result):
    method filter_box (line 155) | def filter_box(self, result, threshold):
    method predict (line 174) | def predict(self, repeats=1):
    method merge_batch_result (line 199) | def merge_batch_result(self, batch_result):
    method predict_image (line 212) | def predict_image(self, image_list, run_benchmark=False, repeats=1, vi...
    method predict_video (line 247) | def predict_video(self, video_file, camera_id):
    method format_coco_results (line 285) | def format_coco_results(image_list, results, save_file=None):
  function create_inputs (line 342) | def create_inputs(imgs, im_info):
  class PredictConfig (line 380) | class PredictConfig():
    method __init__ (line 386) | def __init__(self, model_dir):
    method check_model (line 411) | def check_model(self, yml_conf):
    method print_config (line 421) | def print_config(self):
  function load_predictor (line 430) | def load_predictor(model_dir,
  function get_test_images (line 520) | def get_test_images(infer_dir, infer_img):
  function visualize (line 551) | def visualize(image_list, result, labels, output_dir='output/', threshol...

FILE: modules/image/keypoint_detection/pp-tinypose/keypoint_infer.py
  class KeyPointDetector (line 30) | class KeyPointDetector(Detector):
    method __init__ (line 47) | def __init__(self,
    method set_config (line 77) | def set_config(self, model_dir):
    method get_person_from_rect (line 80) | def get_person_from_rect(self, image, results):
    method postprocess (line 95) | def postprocess(self, inputs, result):
    method predict (line 124) | def predict(self, repeats=1):
    method predict_image (line 149) | def predict_image(self, image_list, run_benchmark=False, repeats=1, vi...
    method predict_video (line 175) | def predict_video(self, video_file, camera_id):
  function create_inputs (line 213) | def create_inputs(imgs, im_info):
  class PredictConfig_KeyPoint (line 230) | class PredictConfig_KeyPoint():
    method __init__ (line 236) | def __init__(self, model_dir):
    method check_model (line 253) | def check_model(self, yml_conf):
    method print_config (line 263) | def print_config(self):
  function visualize (line 272) | def visualize(image_list, results, visual_thresh=0.6, save_dir='output'):

FILE: modules/image/keypoint_detection/pp-tinypose/keypoint_postprocess.py
  class HRNetPostProcess (line 22) | class HRNetPostProcess(object):
    method __init__ (line 24) | def __init__(self, use_dark=True):
    method flip_back (line 27) | def flip_back(self, output_flipped, matched_parts):
    method get_max_preds (line 40) | def get_max_preds(self, heatmaps):
    method gaussian_blur (line 75) | def gaussian_blur(self, heatmap, kernel):
    method dark_parse (line 91) | def dark_parse(self, hm, coord):
    method dark_postprocess (line 112) | def dark_postprocess(self, hm, coords, kernelsize):
    method get_final_preds (line 125) | def get_final_preds(self, heatmaps, center, scale, kernelsize=3):
    method __call__ (line 163) | def __call__(self, output, center, scale):
  function transform_preds (line 168) | def transform_preds(coords, center, scale, output_size):
  function affine_transform (line 176) | def affine_transform(pt, t):
  function translate_to_ori_images (line 182) | def translate_to_ori_images(keypoint_result, batch_records):

FILE: modules/image/keypoint_detection/pp-tinypose/keypoint_preprocess.py
  class EvalAffine (line 21) | class EvalAffine(object):
    method __init__ (line 23) | def __init__(self, size, stride=64):
    method __call__ (line 28) | def __call__(self, image, im_info):
  function get_affine_mat_kernel (line 36) | def get_affine_mat_kernel(h, w, s, inv=False):
  function get_affine_transform (line 57) | def get_affine_transform(center, input_size, rot, output_size, shift=(0....
  function get_warp_matrix (line 108) | def get_warp_matrix(theta, size_input, size_dst, size_target):
  function rotate_point (line 140) | def rotate_point(pt, angle_rad):
  function _get_3rd_point (line 159) | def _get_3rd_point(a, b):
  class TopDownEvalAffine (line 181) | class TopDownEvalAffine(object):
    method __init__ (line 194) | def __init__(self, trainsize, use_udp=False):
    method __call__ (line 198) | def __call__(self, image, im_info):
  function expand_crop (line 217) | def expand_crop(images, rect, expand_ratio=0.3):

FILE: modules/image/keypoint_detection/pp-tinypose/module.py
  class PP_TinyPose (line 41) | class PP_TinyPose:
    method __init__ (line 46) | def __init__(self):
    method predict (line 52) | def predict(self,
    method serving_method (line 86) | def serving_method(self, images: list, **kwargs):
    method run_cmd (line 96) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 117) | def add_module_config_arg(self):
    method add_module_input_arg (line 133) | def add_module_input_arg(self):
    method create_gradio_app (line 139) | def create_gradio_app(self):

FILE: modules/image/keypoint_detection/pp-tinypose/preprocess.py
  function decode_image (line 22) | def decode_image(im_file, im_info):
  class Resize (line 44) | class Resize(object):
    method __init__ (line 52) | def __init__(self, target_size, keep_ratio=True, interp=cv2.INTER_LINE...
    method __call__ (line 59) | def __call__(self, im, im_info):
    method generate_scale (line 77) | def generate_scale(self, im):
  class NormalizeImage (line 104) | class NormalizeImage(object):
    method __init__ (line 113) | def __init__(self, mean, std, is_scale=True):
    method __call__ (line 118) | def __call__(self, im, im_info):
  class Permute (line 138) | class Permute(object):
    method __init__ (line 145) | def __init__(self, ):
    method __call__ (line 148) | def __call__(self, im, im_info):
  class PadStride (line 161) | class PadStride(object):
    method __init__ (line 167) | def __init__(self, stride=0):
    method __call__ (line 170) | def __call__(self, im, im_info):
  class LetterBoxResize (line 190) | class LetterBoxResize(object):
    method __init__ (line 192) | def __init__(self, target_size):
    method letterbox (line 204) | def letterbox(self, img, height, width, color=(127.5, 127.5, 127.5)):
    method __call__ (line 220) | def __call__(self, im, im_info):
  class Pad (line 241) | class Pad(object):
    method __init__ (line 243) | def __init__(self, size, fill_value=[114.0, 114.0, 114.0]):
    method __call__ (line 256) | def __call__(self, im, im_info):
  class WarpAffine (line 270) | class WarpAffine(object):
    method __init__ (line 274) | def __init__(self, keep_res=False, pad=31, input_h=512, input_w=512, s...
    method __call__ (line 282) | def __call__(self, im, im_info):
  function preprocess (line 312) | def preprocess(im, preprocess_ops):
  function cv2_to_base64 (line 324) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 329) | def base64_to_cv2(b64str: str):

FILE: modules/image/keypoint_detection/pp-tinypose/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_predict1 (line 31) | def test_predict1(self):
    method test_predict2 (line 36) | def test_predict2(self):
    method test_predict3 (line 41) | def test_predict3(self):
    method test_predict4 (line 46) | def test_predict4(self):
    method test_predict5 (line 49) | def test_predict5(self):

FILE: modules/image/keypoint_detection/pp-tinypose/visualize.py
  function visualize_box (line 28) | def visualize_box(im, results, labels, threshold=0.5):
  function get_color_map_list (line 50) | def get_color_map_list(num_classes):
  function draw_box (line 71) | def draw_box(im, np_boxes, labels, threshold=0.5):
  function get_color (line 117) | def get_color(idx):
  function visualize_pose (line 123) | def visualize_pose(imgfile,

FILE: modules/image/matting/dim_vgg16_matting/module.py
  class DIMVGG16 (line 42) | class DIMVGG16(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method preprocess (line 91) | def preprocess(self, img: Union[str, np.ndarray] , transforms: Callabl...
    method forward (line 107) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
    method predict (line 138) | def predict(self, image_list: list, trimap_list: list, visualization: ...
    method serving_method (line 161) | def serving_method(self, images: list, trimaps:list, **kwargs) -> dict:
    method run_cmd (line 180) | def run_cmd(self, argvs: list) -> list:
    method add_module_config_arg (line 204) | def add_module_config_arg(self):
    method add_module_input_arg (line 214) | def add_module_input_arg(self):
  class Up (line 222) | class Up(nn.Layer):
    method __init__ (line 223) | def __init__(self, input_channels: int, output_channels: int):
    method forward (line 232) | def forward(self, x: paddle.Tensor, skip: paddle.Tensor, output_shape:...
  class Decoder (line 242) | class Decoder(nn.Layer):
    method __init__ (line 243) | def __init__(self, input_channels: int, output_channels: list = [64, 1...
    method forward (line 256) | def forward(self, fea_list: list, shape_list: list) -> paddle.Tensor:
  class Refine (line 270) | class Refine(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 282) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/matting/dim_vgg16_matting/processor.py
  class Compose (line 27) | class Compose:
    method __init__ (line 33) | def __init__(self, transforms: Callable, to_rgb: bool = True):
    method __call__ (line 39) | def __call__(self, data: dict) -> dict:
  class LoadImages (line 57) | class LoadImages:
    method __init__ (line 64) | def __init__(self, to_rgb: bool = True):
    method __call__ (line 67) | def __call__(self, data: dict) -> dict:
  class LimitLong (line 90) | class LimitLong:
    method __init__ (line 107) | def __init__(self, max_long=None, min_long=None):
    method __call__ (line 126) | def __call__(self, data):
  class Normalize (line 144) | class Normalize:
    method __init__ (line 156) | def __init__(self, mean: Union[List[float], Tuple[float]] = (0.5, 0.5,...
    method __call__ (line 168) | def __call__(self, data: dict) -> dict:
  function reverse_transform (line 180) | def reverse_transform(alpha: paddle.Tensor, trans_info: List[str]):
  function save_alpha_pred (line 193) | def save_alpha_pred(alpha: np.ndarray, trimap: np.ndarray = None):
  function cv2_to_base64 (line 205) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 213) | def base64_to_cv2(b64str: str):

FILE: modules/image/matting/dim_vgg16_matting/vgg.py
  class ConvBlock (line 27) | class ConvBlock(nn.Layer):
    method __init__ (line 28) | def __init__(self, input_channels: int, output_channels: int, groups: ...
    method forward (line 71) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  class VGGNet (line 88) | class VGGNet(nn.Layer):
    method __init__ (line 89) | def __init__(self, input_channels: int = 4, layers: int = 11, pretrain...
    method forward (line 117) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  function VGG16 (line 140) | def VGG16(**args):

FILE: modules/image/matting/gfm_resnet34_matting/gfm.py
  function conv3x3 (line 23) | def conv3x3(in_planes: int, out_planes: int, stride: int = 1) -> Callable:
  function conv_up_psp (line 28) | def conv_up_psp(in_channels: int, out_channels: int, up_sample: float) -...
  function build_bb (line 33) | def build_bb(in_channels: int, mid_channels: int, out_channels: int) -> ...
  function build_decoder (line 41) | def build_decoder(in_channels: int, mid_channels_1: int, mid_channels_2:...
  class BasicBlock (line 63) | class BasicBlock(nn.Layer):
    method __init__ (line 66) | def __init__(self, inplanes: int, planes: int, stride: int = 1, downsa...
    method forward (line 76) | def forward(self, x: paddle.Tensor) -> Callable:
  class PSPModule (line 90) | class PSPModule(nn.Layer):
    method __init__ (line 92) | def __init__(self, features: paddle.Tensor, out_features: int = 1024, ...
    method _make_stage (line 99) | def _make_stage(self, features: paddle.Tensor, size: int) -> Callable:
    method forward (line 104) | def forward(self, feats: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 112) | class SELayer(nn.Layer):
    method __init__ (line 114) | def __init__(self, channel: int, reduction: int = 4):
    method forward (line 120) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GFM (line 127) | class GFM(nn.Layer):
    method __init__ (line 142) | def __init__(self):
    method forward (line 287) | def forward(self, input: paddle.Tensor) -> List[paddle.Tensor]:
  function collaborative_matting (line 375) | def collaborative_matting(rosta, glance_sigmoid, focus_sigmoid):

FILE: modules/image/matting/gfm_resnet34_matting/module.py
  class GFMResNet34 (line 40) | class GFMResNet34(nn.Layer):
    method __init__ (line 52) | def __init__(self, pretrained: str = None):
    method preprocess (line 69) | def preprocess(self, img: Union[str, np.ndarray], h: int, w: int) -> p...
    method scale_image (line 75) | def scale_image(self, img: np.ndarray, h: int, w: int, ratio: float = ...
    method inference_img_scale (line 88) | def inference_img_scale(self, input: paddle.Tensor) -> List[paddle.Ten...
    method predict (line 95) | def predict(self, image_list: list, visualization: bool = True, save_p...
    method serving_method (line 123) | def serving_method(self, images: str, **kwargs):
    method run_cmd (line 135) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 156) | def add_module_config_arg(self):
    method add_module_input_arg (line 170) | def add_module_input_arg(self):

FILE: modules/image/matting/gfm_resnet34_matting/processor.py
  class ResizeByLong (line 22) | class ResizeByLong:
    method __init__ (line 30) | def __init__(self, long_size):
    method __call__ (line 33) | def __call__(self, data):
  class ResizeByShort (line 38) | class ResizeByShort:
    method __init__ (line 46) | def __init__(self, short_size):
    method __call__ (line 49) | def __call__(self, data):
  function gen_trimap_from_segmap_e2e (line 55) | def gen_trimap_from_segmap_e2e(segmap):
  function get_masked_local_from_global_test (line 62) | def get_masked_local_from_global_test(global_result, local_result):
  function cv2_to_base64 (line 69) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 77) | def base64_to_cv2(b64str: str):

FILE: modules/image/matting/gfm_resnet34_matting/resnet.py
  function conv3x3 (line 20) | def conv3x3(in_planes: int, out_planes: int, stride: int=1, groups: int=1,
  function conv1x1 (line 27) | def conv1x1(in_planes: int, out_planes: int, stride: int=1) ->paddle.nn....
  class BasicBlock (line 33) | class BasicBlock(nn.Layer):
    method __init__ (line 36) | def __init__(self, inplanes: int, planes: int, stride: int=1,
    method forward (line 57) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Bottleneck (line 71) | class Bottleneck(nn.Layer):
    method __init__ (line 74) | def __init__(self, inplanes: int, planes: int, stride: int=1,
    method forward (line 92) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ResNet (line 109) | class ResNet(nn.Layer):
    method __init__ (line 111) | def __init__(self, block: Type[Union[BasicBlock, Bottleneck]], layers:
    method _make_layer (line 145) | def _make_layer(self, block: Type[Union[BasicBlock, Bottleneck]],
    method _forward_impl (line 167) | def _forward_impl(self, x: paddle.Tensor) ->paddle.Tensor:
    method forward (line 181) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  function _resnet (line 185) | def _resnet(arch: str, block: Type[Union[BasicBlock, Bottleneck]], layers:
  function resnet34 (line 191) | def resnet34(pretrained: bool=False, progress: bool=True, **kwargs: Any

FILE: modules/image/matting/modnet_hrnet18_matting/hrnet.py
  class HRNet (line 28) | class HRNet(nn.Layer):
    method __init__ (line 55) | def __init__(self,
    method forward (line 163) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Layer1 (line 185) | class Layer1(nn.Layer):
    method __init__ (line 186) | def __init__(self,
    method forward (line 210) | def forward(self, x: paddle.Tensor):
  class TransitionLayer (line 217) | class TransitionLayer(nn.Layer):
    method __init__ (line 218) | def __init__(self,
    method forward (line 252) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Branches (line 265) | class Branches(nn.Layer):
    method __init__ (line 266) | def __init__(self,
    method forward (line 292) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 302) | class BottleneckBlock(nn.Layer):
    method __init__ (line 303) | def __init__(self,
    method forward (line 353) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 370) | class BasicBlock(nn.Layer):
    method __init__ (line 371) | def __init__(self,
    method forward (line 415) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 431) | class SELayer(nn.Layer):
    method __init__ (line 432) | def __init__(self, num_channels: int, num_filters: int, reduction_rati...
    method forward (line 454) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Stage (line 467) | class Stage(nn.Layer):
    method __init__ (line 468) | def __init__(self,
    method forward (line 510) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class HighResolutionModule (line 517) | class HighResolutionModule(nn.Layer):
    method __init__ (line 518) | def __init__(self,
    method forward (line 545) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FuseLayers (line 551) | class FuseLayers(nn.Layer):
    method __init__ (line 552) | def __init__(self,
    method forward (line 606) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  function HRNet_W18 (line 637) | def HRNet_W18(**kwargs):

FILE: modules/image/matting/modnet_hrnet18_matting/module.py
  class MODNetHRNet18 (line 41) | class MODNetHRNet18(nn.Layer):
    method __init__ (line 54) | def __init__(self, hr_channels:int = 32, pretrained=None):
    method preprocess (line 76) | def preprocess(self, img: Union[str, np.ndarray] , transforms: Callabl...
    method forward (line 92) | def forward(self, inputs: dict) -> paddle.Tensor:
    method predict (line 98) | def predict(self, image_list: list, trimap_list: list = None, visualiz...
    method serving_method (line 121) | def serving_method(self, images: list, trimaps:list = None, **kwargs) ...
    method run_cmd (line 138) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 162) | def add_module_config_arg(self):
    method add_module_input_arg (line 172) | def add_module_input_arg(self):
  class MODNetHead (line 181) | class MODNetHead(nn.Layer):
    method __init__ (line 185) | def __init__(self, hr_channels: int, backbone_channels: int):
    method forward (line 192) | def forward(self, inputs: paddle.Tensor, feat_list: list):
  class FusionBranch (line 209) | class FusionBranch(nn.Layer):
    method __init__ (line 210) | def __init__(self, hr_channels: int, enc_channels: int):
    method forward (line 229) | def forward(self, img: paddle.Tensor, lr8x: paddle.Tensor, hr2x: paddl...
  class HRBranch (line 245) | class HRBranch(nn.Layer):
    method __init__ (line 250) | def __init__(self, hr_channels: int, enc_channels:int):
    method forward (line 295) | def forward(self, img: paddle.Tensor, enc2x: paddle.Tensor, enc4x: pad...
  class LRBranch (line 325) | class LRBranch(nn.Layer):
    method __init__ (line 329) | def __init__(self, backbone_channels: int):
    method forward (line 345) | def forward(self, feat_list: list):
  class IBNorm (line 364) | class IBNorm(nn.Layer):
    method __init__ (line 369) | def __init__(self, in_channels: int):
    method forward (line 377) | def forward(self, x):
  class Conv2dIBNormRelu (line 384) | class Conv2dIBNormRelu(nn.Layer):
    method __init__ (line 389) | def __init__(self,
    method forward (line 423) | def forward(self, x: paddle.Tensor):
  class SEBlock (line 427) | class SEBlock(nn.Layer):
    method __init__ (line 432) | def __init__(self, num_channels: int, reduction:int = 1):
    method forward (line 447) | def forward(self, x: paddle.Tensor):
  class GaussianBlurLayer (line 453) | class GaussianBlurLayer(nn.Layer):
    method __init__ (line 459) | def __init__(self, channels: int, kernel_size: int):
    method forward (line 485) | def forward(self, x: paddle.Tensor):
    method _init_kernel (line 504) | def _init_kernel(self):

FILE: modules/image/matting/modnet_hrnet18_matting/processor.py
  class Compose (line 27) | class Compose:
    method __init__ (line 33) | def __init__(self, transforms: Callable, to_rgb: bool = True):
    method __call__ (line 39) | def __call__(self, data: dict) -> dict:
  class LoadImages (line 57) | class LoadImages:
    method __init__ (line 64) | def __init__(self, to_rgb: bool = True):
    method __call__ (line 67) | def __call__(self, data: dict) -> dict:
  class ResizeByShort (line 90) | class ResizeByShort:
    method __init__ (line 98) | def __init__(self, short_size: int =512):
    method __call__ (line 101) | def __call__(self, data: dict) -> dict:
  class ResizeToIntMult (line 110) | class ResizeToIntMult:
    method __init__ (line 115) | def __init__(self, mult_int: int = 32):
    method __call__ (line 118) | def __call__(self, data: dict) -> dict:
  class Normalize (line 131) | class Normalize:
    method __init__ (line 143) | def __init__(self, mean: Union[List[float], Tuple[float]] = (0.5, 0.5,...
    method __call__ (line 155) | def __call__(self, data: dict) -> dict:
  function reverse_transform (line 167) | def reverse_transform(alpha: paddle.Tensor, trans_info: List[str]):
  function save_alpha_pred (line 180) | def save_alpha_pred(alpha: np.ndarray, trimap:  Union[np.ndarray, str] =...
  function cv2_to_base64 (line 193) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 201) | def base64_to_cv2(b64str: str):

FILE: modules/image/matting/modnet_mobilenetv2_matting/mobilenetv2.py
  class ConvBNLayer (line 32) | class ConvBNLayer(nn.Layer):
    method __init__ (line 34) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor, if_act: bool = True) -> paddl...
  class InvertedResidualUnit (line 70) | class InvertedResidualUnit(nn.Layer):
    method __init__ (line 72) | def __init__(self, num_channels: int, num_in_filter: int, num_filters:...
    method forward (line 104) | def forward(self, inputs: paddle.Tensor, ifshortcut: bool) -> paddle.T...
  class InvresiBlocks (line 113) | class InvresiBlocks(nn.Layer):
    method __init__ (line 114) | def __init__(self, in_c: int, t: int, c: int, n: int, s: int, name: str):
    method forward (line 142) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class MobileNet (line 149) | class MobileNet(nn.Layer):
    method __init__ (line 151) | def __init__(self,
    method forward (line 207) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  function MobileNetV2 (line 222) | def MobileNetV2(**kwargs):

FILE: modules/image/matting/modnet_mobilenetv2_matting/module.py
  class MODNetMobilenetV2 (line 41) | class MODNetMobilenetV2(nn.Layer):
    method __init__ (line 55) | def __init__(self, hr_channels:int = 32, pretrained=None):
    method preprocess (line 77) | def preprocess(self, img: Union[str, np.ndarray] , transforms: Callabl...
    method forward (line 93) | def forward(self, inputs: dict):
    method predict (line 99) | def predict(self, image_list: list, trimap_list: list = None, visualiz...
    method serving_method (line 122) | def serving_method(self, images: list, trimaps:list = None, **kwargs):
    method run_cmd (line 139) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 163) | def add_module_config_arg(self):
    method add_module_input_arg (line 173) | def add_module_input_arg(self):
  class MODNetHead (line 182) | class MODNetHead(nn.Layer):
    method __init__ (line 186) | def __init__(self, hr_channels: int, backbone_channels: int):
    method forward (line 193) | def forward(self, inputs: paddle.Tensor, feat_list: list):
  class FusionBranch (line 210) | class FusionBranch(nn.Layer):
    method __init__ (line 211) | def __init__(self, hr_channels: int, enc_channels: int):
    method forward (line 230) | def forward(self, img: paddle.Tensor, lr8x: paddle.Tensor, hr2x: paddl...
  class HRBranch (line 246) | class HRBranch(nn.Layer):
    method __init__ (line 251) | def __init__(self, hr_channels: int, enc_channels:int):
    method forward (line 296) | def forward(self, img: paddle.Tensor, enc2x: paddle.Tensor, enc4x: pad...
  class LRBranch (line 326) | class LRBranch(nn.Layer):
    method __init__ (line 330) | def __init__(self, backbone_channels: int):
    method forward (line 346) | def forward(self, feat_list: list):
  class IBNorm (line 365) | class IBNorm(nn.Layer):
    method __init__ (line 370) | def __init__(self, in_channels: int):
    method forward (line 378) | def forward(self, x):
  class Conv2dIBNormRelu (line 385) | class Conv2dIBNormRelu(nn.Layer):
    method __init__ (line 390) | def __init__(self,
    method forward (line 424) | def forward(self, x: paddle.Tensor):
  class SEBlock (line 428) | class SEBlock(nn.Layer):
    method __init__ (line 433) | def __init__(self, num_channels: int, reduction:int = 1):
    method forward (line 448) | def forward(self, x: paddle.Tensor):
  class GaussianBlurLayer (line 454) | class GaussianBlurLayer(nn.Layer):
    method __init__ (line 460) | def __init__(self, channels: int, kernel_size: int):
    method forward (line 486) | def forward(self, x: paddle.Tensor):
    method _init_kernel (line 505) | def _init_kernel(self):

FILE: modules/image/matting/modnet_mobilenetv2_matting/processor.py
  class Compose (line 27) | class Compose:
    method __init__ (line 33) | def __init__(self, transforms: Callable, to_rgb: bool = True):
    method __call__ (line 39) | def __call__(self, data: dict) -> dict:
  class LoadImages (line 57) | class LoadImages:
    method __init__ (line 64) | def __init__(self, to_rgb: bool = True):
    method __call__ (line 67) | def __call__(self, data: dict) -> dict:
  class ResizeByShort (line 90) | class ResizeByShort:
    method __init__ (line 98) | def __init__(self, short_size: int =512):
    method __call__ (line 101) | def __call__(self, data: dict) -> dict:
  class ResizeToIntMult (line 110) | class ResizeToIntMult:
    method __init__ (line 115) | def __init__(self, mult_int: int = 32):
    method __call__ (line 118) | def __call__(self, data: dict) -> dict:
  class Normalize (line 131) | class Normalize:
    method __init__ (line 143) | def __init__(self, mean: Union[List[float], Tuple[float]] = (0.5, 0.5,...
    method __call__ (line 155) | def __call__(self, data: dict) -> dict:
  function reverse_transform (line 167) | def reverse_transform(alpha: paddle.Tensor, trans_info: List[str]):
  function save_alpha_pred (line 180) | def save_alpha_pred(alpha: np.ndarray, trimap: np.ndarray = None):
  function cv2_to_base64 (line 192) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 200) | def base64_to_cv2(b64str: str):

FILE: modules/image/matting/modnet_resnet50vd_matting/module.py
  class MODNetResNet50Vd (line 40) | class MODNetResNet50Vd(nn.Layer):
    method __init__ (line 53) | def __init__(self, hr_channels: int = 32, pretrained=None):
    method preprocess (line 74) | def preprocess(self, img: Union[str, np.ndarray], transforms: Callable...
    method forward (line 90) | def forward(self, inputs: dict):
    method predict (line 96) | def predict(self,
    method serving_method (line 123) | def serving_method(self, images: list, trimaps: list = None, **kwargs):
    method run_cmd (line 140) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 166) | def add_module_config_arg(self):
    method add_module_input_arg (line 180) | def add_module_input_arg(self):
  class MODNetHead (line 188) | class MODNetHead(nn.Layer):
    method __init__ (line 193) | def __init__(self, hr_channels: int, backbone_channels: int):
    method forward (line 200) | def forward(self, inputs: paddle.Tensor, feat_list: list) -> paddle.Te...
  class FusionBranch (line 207) | class FusionBranch(nn.Layer):
    method __init__ (line 209) | def __init__(self, hr_channels: int, enc_channels: int):
    method forward (line 218) | def forward(self, img: paddle.Tensor, lr8x: paddle.Tensor, hr2x: paddl...
  class HRBranch (line 231) | class HRBranch(nn.Layer):
    method __init__ (line 236) | def __init__(self, hr_channels: int, enc_channels: int):
    method forward (line 259) | def forward(self, img: paddle.Tensor, enc2x: paddle.Tensor, enc4x: pad...
  class LRBranch (line 279) | class LRBranch(nn.Layer):
    method __init__ (line 284) | def __init__(self, backbone_channels: int):
    method forward (line 297) | def forward(self, feat_list: list) -> List[paddle.Tensor]:
  class IBNorm (line 314) | class IBNorm(nn.Layer):
    method __init__ (line 319) | def __init__(self, in_channels: int):
    method forward (line 327) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Conv2dIBNormRelu (line 334) | class Conv2dIBNormRelu(nn.Layer):
    method __init__ (line 339) | def __init__(self,
    method forward (line 372) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SEBlock (line 376) | class SEBlock(nn.Layer):
    method __init__ (line 381) | def __init__(self, num_channels: int, reduction: int = 1):
    method forward (line 389) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GaussianBlurLayer (line 395) | class GaussianBlurLayer(nn.Layer):
    method __init__ (line 401) | def __init__(self, channels: int, kernel_size: int):
    method forward (line 420) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
    method _init_kernel (line 438) | def _init_kernel(self):

FILE: modules/image/matting/modnet_resnet50vd_matting/processor.py
  class Compose (line 27) | class Compose:
    method __init__ (line 33) | def __init__(self, transforms: Callable, to_rgb: bool = True):
    method __call__ (line 39) | def __call__(self, data: dict) -> dict:
  class LoadImages (line 57) | class LoadImages:
    method __init__ (line 65) | def __init__(self, to_rgb: bool = True):
    method __call__ (line 68) | def __call__(self, data: dict) -> dict:
  class ResizeByShort (line 91) | class ResizeByShort:
    method __init__ (line 99) | def __init__(self, short_size: int = 512):
    method __call__ (line 102) | def __call__(self, data: dict) -> dict:
  class ResizeToIntMult (line 111) | class ResizeToIntMult:
    method __init__ (line 116) | def __init__(self, mult_int: int = 32):
    method __call__ (line 119) | def __call__(self, data: dict) -> dict:
  class Normalize (line 132) | class Normalize:
    method __init__ (line 144) | def __init__(self,
    method __call__ (line 155) | def __call__(self, data: dict) -> dict:
  function reverse_transform (line 167) | def reverse_transform(alpha: paddle.Tensor, trans_info: List[str]):
  function save_alpha_pred (line 181) | def save_alpha_pred(alpha: np.ndarray, trimap: np.ndarray = None):
  function cv2_to_base64 (line 193) | def cv2_to_base64(image: np.ndarray):
  function base64_to_cv2 (line 201) | def base64_to_cv2(b64str: str):

FILE: modules/image/matting/modnet_resnet50vd_matting/resnet.py
  class ConvBNLayer (line 22) | class ConvBNLayer(nn.Layer):
    method __init__ (line 25) | def __init__(
    method forward (line 52) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 62) | class BottleneckBlock(nn.Layer):
    method __init__ (line 65) | def __init__(self,
    method forward (line 95) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 119) | class BasicBlock(nn.Layer):
    method __init__ (line 122) | def __init__(self, in_channels: int, out_channels: int, stride: int, s...
    method forward (line 141) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 155) | class ResNet_vd(nn.Layer):
    method __init__ (line 165) | def __init__(self,
    method forward (line 264) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  function ResNet50_vd (line 282) | def ResNet50_vd(**args):

FILE: modules/image/object_detection/faster_rcnn_resnet50_coco2017/data_feed.py
  function test_reader (line 14) | def test_reader(paths=None, images=None):
  function padding_minibatch (line 80) | def padding_minibatch(batch_data, coarsest_stride=0, use_padded_im_info=...

FILE: modules/image/object_detection/faster_rcnn_resnet50_coco2017/module.py
  class FasterRCNNResNet50 (line 29) | class FasterRCNNResNet50:
    method __init__ (line 30) | def __init__(self):
    method _set_config (line 38) | def _set_config(self):
    method object_detection (line 61) | def object_detection(self,
    method add_module_config_arg (line 149) | def add_module_config_arg(self):
    method add_module_input_arg (line 165) | def add_module_input_arg(self):
    method check_input_data (line 178) | def check_input_data(self, args):
    method serving_method (line 190) | def serving_method(self, images, **kwargs):
    method run_cmd (line 199) | def run_cmd(self, argvs):

FILE: modules/image/object_detection/faster_rcnn_resnet50_coco2017/processor.py
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function check_dir (line 22) | def check_dir(dir_path):
  function get_save_image_name (line 29) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 53) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 84) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 92) | def load_label_info(file_path):
  function postprocess (line 101) | def postprocess(paths,

FILE: modules/image/object_detection/faster_rcnn_resnet50_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/data_feed.py
  function test_reader (line 14) | def test_reader(paths=None, images=None):
  function padding_minibatch (line 81) | def padding_minibatch(batch_data, coarsest_stride=0, use_padded_im_info=...

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/module.py
  class FasterRCNNResNet50RPN (line 30) | class FasterRCNNResNet50RPN:
    method __init__ (line 31) | def __init__(self):
    method _set_config (line 39) | def _set_config(self):
    method object_detection (line 62) | def object_detection(self,
    method add_module_config_arg (line 156) | def add_module_config_arg(self):
    method add_module_input_arg (line 172) | def add_module_input_arg(self):
    method check_input_data (line 185) | def check_input_data(self, args):
    method serving_method (line 197) | def serving_method(self, images, **kwargs):
    method run_cmd (line 206) | def run_cmd(self, argvs):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/processor.py
  function base64_to_cv2 (line 15) | def base64_to_cv2(b64str):
  function check_dir (line 21) | def check_dir(dir_path):
  function get_save_image_name (line 28) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 52) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 83) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 91) | def load_label_info(file_path):
  function postprocess (line 100) | def postprocess(paths,

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/bbox_assigner.py
  class BBoxAssigner (line 1) | class BBoxAssigner(object):
    method __init__ (line 3) | def __init__(self,

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/bbox_head.py
  class MultiClassNMS (line 15) | class MultiClassNMS(object):
    method __init__ (line 17) | def __init__(self,
  class SmoothL1Loss (line 35) | class SmoothL1Loss(object):
    method __init__ (line 42) | def __init__(self, sigma=1.0):
    method __call__ (line 46) | def __call__(self, x, y, inside_weight=None, outside_weight=None):
  class BoxCoder (line 51) | class BoxCoder(object):
    method __init__ (line 52) | def __init__(self, prior_box_var=[0.1, 0.1, 0.2, 0.2], code_type='deco...
  class TwoFCHead (line 61) | class TwoFCHead(object):
    method __init__ (line 69) | def __init__(self, mlp_dim=1024):
    method __call__ (line 73) | def __call__(self, roi_feat):
  class BBoxHead (line 94) | class BBoxHead(object):
    method __init__ (line 107) | def __init__(self, head, box_coder=BoxCoder(), nms=MultiClassNMS(), bb...
    method get_head_feat (line 116) | def get_head_feat(self, input=None):
    method _get_output (line 128) | def _get_output(self, roi_feat):
    method get_loss (line 161) | def get_loss(self, roi_feat, labels_int32, bbox_targets, bbox_inside_w...
    method get_prediction (line 194) | def get_prediction(self, roi_feat, rois, im_info, im_shape, return_box...

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/data_feed.py
  function test_reader (line 17) | def test_reader(paths=None, images=None):
  function padding_minibatch (line 77) | def padding_minibatch(batch_data, coarsest_stride=0, use_padded_im_info=...

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/fpn.py
  function ConvNorm (line 30) | def ConvNorm(input,
  class FPN (line 93) | class FPN(object):
    method __init__ (line 107) | def __init__(self,
    method _add_topdown_lateral (line 123) | def _add_topdown_lateral(self, body_name, body_input, upper_output):
    method get_output (line 149) | def get_output(self, body_dict):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/module.py
  class FasterRCNNResNet50RPN (line 39) | class FasterRCNNResNet50RPN(hub.Module):
    method _initialize (line 40) | def _initialize(self):
    method context (line 44) | def context(self, num_classes=708, trainable=True, pretrained=True, ph...
    method rpn_head (line 162) | def rpn_head(self):
    method roi_extractor (line 182) | def roi_extractor(self):
    method bbox_head (line 186) | def bbox_head(self, num_classes):
    method bbox_assigner (line 192) | def bbox_assigner(self, num_classes):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/name_adapter.py
  class NameAdapter (line 4) | class NameAdapter(object):
    method __init__ (line 7) | def __init__(self, model):
    method model_type (line 12) | def model_type(self):
    method variant (line 16) | def variant(self):
    method fix_conv_norm_name (line 19) | def fix_conv_norm_name(self, name):
    method fix_shortcut_name (line 29) | def fix_shortcut_name(self, name):
    method fix_bottleneck_name (line 34) | def fix_bottleneck_name(self, name):
    method fix_layer_warp_name (line 47) | def fix_layer_warp_name(self, stage_num, count, i):
    method fix_c1_stage_name (line 60) | def fix_c1_stage_name(self):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/nonlocal_helper.py
  function space_nonlocal (line 25) | def space_nonlocal(input, dim_in, dim_out, prefix, dim_inner, max_pool_s...
  function add_space_nonlocal (line 144) | def add_space_nonlocal(input, dim_in, dim_out, prefix, dim_inner):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/processor.py
  function base64_to_cv2 (line 16) | def base64_to_cv2(b64str):
  function get_save_image_name (line 23) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 47) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 72) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 80) | def load_label_info(file_path):
  function postprocess (line 89) | def postprocess(paths, images, data_out, score_thresh, label_names, outp...

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/resnet.py
  class ResNet (line 22) | class ResNet(object):
    method __init__ (line 38) | def __init__(self,
    method _conv_offset (line 93) | def _conv_offset(self, input, filter_size, stride, padding, act=None, ...
    method _conv_norm (line 107) | def _conv_norm(self, input, num_filters, filter_size, stride=1, groups...
    method _shortcut (line 181) | def _shortcut(self, input, ch_out, stride, is_first, name):
    method bottleneck (line 201) | def bottleneck(self, input, num_filters, stride, is_first, name, dcn_v...
    method basicblock (line 247) | def basicblock(self, input, num_filters, stride, is_first, name, dcn_v...
    method layer_warp (line 255) | def layer_warp(self, input, stage_num):
    method c1_stage (line 299) | def c1_stage(self, input):
    method __call__ (line 319) | def __call__(self, input):
  class ResNetC5 (line 353) | class ResNetC5(ResNet):
    method __init__ (line 354) | def __init__(self,

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/roi_extractor.py
  class FPNRoIAlign (line 7) | class FPNRoIAlign(object):
    method __init__ (line 20) | def __init__(self,
    method __call__ (line 37) | def __call__(self, head_inputs, rois, spatial_scale, is_mask=False):

FILE: modules/image/object_detection/faster_rcnn_resnet50_fpn_venus/rpn_head.py
  class AnchorGenerator (line 14) | class AnchorGenerator(object):
    method __init__ (line 16) | def __init__(self,
  class RPNTargetAssign (line 28) | class RPNTargetAssign(object):
    method __init__ (line 30) | def __init__(self,
  class GenerateProposals (line 46) | class GenerateProposals(object):
    method __init__ (line 48) | def __init__(self, pre_nms_top_n=6000, post_nms_top_n=1000, nms_thresh...
  class RPNHead (line 57) | class RPNHead(object):
    method __init__ (line 70) | def __init__(self, anchor_generator, rpn_target_assign, train_proposal...
    method _get_output (line 78) | def _get_output(self, input):
    method get_proposals (line 133) | def get_proposals(self, body_feats, im_info, mode='train'):
    method _transform_input (line 177) | def _transform_input(self, rpn_cls_score, rpn_bbox_pred, anchor, ancho...
    method _get_loss_input (line 186) | def _get_loss_input(self):
    method get_loss (line 192) | def get_loss(self, im_info, gt_box, is_crowd, gt_label=None):
  class FPNRPNHead (line 263) | class FPNRPNHead(RPNHead):
    method __init__ (line 279) | def __init__(self,
    method _get_output (line 300) | def _get_output(self, input, feat_lvl):
    method _get_single_proposals (line 361) | def _get_single_proposals(self, body_feat, im_info, feat_lvl, mode='tr...
    method get_proposals (line 406) | def get_proposals(self, fpn_feats, im_info, mode='train'):
    method _get_loss_input (line 438) | def _get_loss_input(self):

FILE: modules/image/object_detection/ssd_mobilenet_v1_pascal/data_feed.py
  class DecodeImage (line 16) | class DecodeImage(object):
    method __init__ (line 17) | def __init__(self, to_rgb=True, with_mixup=False):
    method __call__ (line 27) | def __call__(self, im):
  class ResizeImage (line 34) | class ResizeImage(object):
    method __init__ (line 35) | def __init__(self,
    method __call__ (line 59) | def __call__(self, im):
  class NormalizeImage (line 113) | class NormalizeImage(object):
    method __init__ (line 114) | def __init__(self,
    method __call__ (line 129) | def __call__(self, im):
  class Permute (line 150) | class Permute(object):
    method __init__ (line 151) | def __init__(self, to_bgr=True, channel_first=True):
    method __call__ (line 162) | def __call__(self, im):
  function reader (line 171) | def reader(paths=[],

FILE: modules/image/object_detection/ssd_mobilenet_v1_pascal/module.py
  class SSDMobileNetv1 (line 32) | class SSDMobileNetv1:
    method __init__ (line 33) | def __init__(self):
    method _set_config (line 39) | def _set_config(self):
    method object_detection (line 70) | def object_detection(self,
    method serving_method (line 141) | def serving_method(self, images, **kwargs):
    method run_cmd (line 150) | def run_cmd(self, argvs):
    method add_module_config_arg (line 172) | def add_module_config_arg(self):
    method add_module_input_arg (line 189) | def add_module_input_arg(self):

FILE: modules/image/object_detection/ssd_mobilenet_v1_pascal/processor.py
  function base64_to_cv2 (line 13) | def base64_to_cv2(b64str):
  function check_dir (line 20) | def check_dir(dir_path):
  function get_save_image_name (line 28) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 52) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 78) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 86) | def load_label_info(file_path):
  function postprocess (line 95) | def postprocess(paths, images, data_out, score_thresh, label_names, outp...

FILE: modules/image/object_detection/ssd_mobilenet_v1_pascal/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/ssd_vgg16_300_coco2017/data_feed.py
  class DecodeImage (line 16) | class DecodeImage(object):
    method __init__ (line 17) | def __init__(self, to_rgb=True, with_mixup=False):
    method __call__ (line 27) | def __call__(self, im):
  class ResizeImage (line 34) | class ResizeImage(object):
    method __init__ (line 35) | def __init__(self, target_size=0, max_size=0, interp=cv2.INTER_LINEAR,...
    method __call__ (line 55) | def __call__(self, im):
  class NormalizeImage (line 102) | class NormalizeImage(object):
    method __init__ (line 103) | def __init__(self, mean=[0.485, 0.456, 0.406], std=[1, 1, 1], is_scale...
    method __call__ (line 114) | def __call__(self, im):
  class Permute (line 135) | class Permute(object):
    method __init__ (line 136) | def __init__(self, to_bgr=True, channel_first=True):
    method __call__ (line 147) | def __call__(self, im):
  function reader (line 156) | def reader(paths=[],

FILE: modules/image/object_detection/ssd_vgg16_300_coco2017/module.py
  class SSDVGG16 (line 27) | class SSDVGG16:
    method __init__ (line 28) | def __init__(self):
    method _set_config (line 36) | def _set_config(self):
    method object_detection (line 68) | def object_detection(self,
    method serving_method (line 126) | def serving_method(self, images, **kwargs):
    method run_cmd (line 135) | def run_cmd(self, argvs):
    method add_module_config_arg (line 162) | def add_module_config_arg(self):
    method add_module_input_arg (line 182) | def add_module_input_arg(self):

FILE: modules/image/object_detection/ssd_vgg16_300_coco2017/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function get_save_image_name (line 19) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 43) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 69) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 77) | def load_label_info(file_path):
  function postprocess (line 86) | def postprocess(paths, images, data_out, score_thresh, label_names, outp...

FILE: modules/image/object_detection/ssd_vgg16_300_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/ssd_vgg16_512_coco2017/data_feed.py
  class DecodeImage (line 16) | class DecodeImage(object):
    method __init__ (line 17) | def __init__(self, to_rgb=True, with_mixup=False):
    method __call__ (line 27) | def __call__(self, im):
  class ResizeImage (line 34) | class ResizeImage(object):
    method __init__ (line 35) | def __init__(self,
    method __call__ (line 59) | def __call__(self, im):
  class NormalizeImage (line 113) | class NormalizeImage(object):
    method __init__ (line 114) | def __init__(self,
    method __call__ (line 129) | def __call__(self, im):
  class Permute (line 150) | class Permute(object):
    method __init__ (line 151) | def __init__(self, to_bgr=True, channel_first=True):
    method __call__ (line 162) | def __call__(self, im):
  function reader (line 171) | def reader(paths=[],

FILE: modules/image/object_detection/ssd_vgg16_512_coco2017/module.py
  class SSDVGG16_512 (line 27) | class SSDVGG16_512:
    method __init__ (line 28) | def __init__(self):
    method _set_config (line 36) | def _set_config(self):
    method object_detection (line 68) | def object_detection(self,
    method serving_method (line 135) | def serving_method(self, images, **kwargs):
    method run_cmd (line 144) | def run_cmd(self, argvs):
    method add_module_config_arg (line 171) | def add_module_config_arg(self):
    method add_module_input_arg (line 191) | def add_module_input_arg(self):

FILE: modules/image/object_detection/ssd_vgg16_512_coco2017/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function check_dir (line 18) | def check_dir(dir_path):
  function get_save_image_name (line 25) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 49) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 81) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 89) | def load_label_info(file_path):
  function postprocess (line 98) | def postprocess(paths,

FILE: modules/image/object_detection/ssd_vgg16_512_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/yolov3_darknet53_coco2017/data_feed.py
  function reader (line 14) | def reader(paths=[], images=None):

FILE: modules/image/object_detection/yolov3_darknet53_coco2017/module.py
  class YOLOv3DarkNet53Coco2017 (line 27) | class YOLOv3DarkNet53Coco2017:
    method __init__ (line 28) | def __init__(self):
    method _set_config (line 33) | def _set_config(self):
    method object_detection (line 57) | def object_detection(self,
    method serving_method (line 126) | def serving_method(self, images, **kwargs):
    method run_cmd (line 135) | def run_cmd(self, argvs):
    method add_module_config_arg (line 159) | def add_module_config_arg(self):
    method add_module_input_arg (line 170) | def add_module_input_arg(self):

FILE: modules/image/object_detection/yolov3_darknet53_coco2017/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function check_dir (line 19) | def check_dir(dir_path):
  function get_save_image_name (line 27) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 49) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 72) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 80) | def load_label_info(file_path):
  function postprocess (line 89) | def postprocess(paths, images, data_out, score_thresh, label_names, outp...

FILE: modules/image/object_detection/yolov3_darknet53_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/yolov3_darknet53_pedestrian/data_feed.py
  function reader (line 14) | def reader(paths=[], images=None):

FILE: modules/image/object_detection/yolov3_darknet53_pedestrian/module.py
  class YOLOv3DarkNet53Pedestrian (line 31) | class YOLOv3DarkNet53Pedestrian:
    method __init__ (line 32) | def __init__(self):
    method _set_config (line 37) | def _set_config(self):
    method object_detection (line 61) | def object_detection(self,
    method serving_method (line 130) | def serving_method(self, images, **kwargs):
    method run_cmd (line 139) | def run_cmd(self, argvs):
    method add_module_config_arg (line 161) | def add_module_config_arg(self):
    method add_module_input_arg (line 178) | def add_module_input_arg(self):

FILE: modules/image/object_detection/yolov3_darknet53_pedestrian/processor.py
  function base64_to_cv2 (line 13) | def base64_to_cv2(b64str):
  function check_dir (line 20) | def check_dir(dir_path):
  function get_save_image_name (line 28) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 50) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 73) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 81) | def load_label_info(file_path):
  function postprocess (line 90) | def postprocess(paths, images, data_out, score_thresh, label_names, outp...

FILE: modules/image/object_detection/yolov3_darknet53_pedestrian/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/yolov3_darknet53_vehicles/data_feed.py
  function reader (line 14) | def reader(paths=[], images=None):

FILE: modules/image/object_detection/yolov3_darknet53_vehicles/module.py
  class YOLOv3DarkNet53Vehicles (line 31) | class YOLOv3DarkNet53Vehicles:
    method __init__ (line 32) | def __init__(self):
    method _get_device_id (line 37) | def _get_device_id(self, places):
    method _set_config (line 45) | def _set_config(self):
    method object_detection (line 87) | def object_detection(self,
    method serving_method (line 174) | def serving_method(self, images, **kwargs):
    method run_cmd (line 183) | def run_cmd(self, argvs):
    method add_module_config_arg (line 206) | def add_module_config_arg(self):
    method add_module_input_arg (line 226) | def add_module_input_arg(self):

FILE: modules/image/object_detection/yolov3_darknet53_vehicles/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function check_dir (line 19) | def check_dir(dir_path):
  function get_save_image_name (line 27) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 49) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 72) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 80) | def load_label_info(file_path):
  function postprocess (line 89) | def postprocess(paths, images, data_out, score_thresh, label_names, outp...

FILE: modules/image/object_detection/yolov3_darknet53_vehicles/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/yolov3_darknet53_venus/darknet.py
  class DarkNet (line 16) | class DarkNet(object):
    method __init__ (line 27) | def __init__(self,
    method _conv_norm (line 43) | def _conv_norm(self, input, ch_out, filter_size, stride, padding, act=...
    method _downsample (line 73) | def _downsample(self, input, ch_out, filter_size=3, stride=2, padding=...
    method basicblock (line 76) | def basicblock(self, input, ch_out, name=None):
    method layer_warp (line 82) | def layer_warp(self, block_func, input, ch_out, count, name=None):
    method __call__ (line 88) | def __call__(self, input):

FILE: modules/image/object_detection/yolov3_darknet53_venus/data_feed.py
  function reader (line 14) | def reader(paths=[], images=None):

FILE: modules/image/object_detection/yolov3_darknet53_venus/module.py
  class YOLOv3DarkNet53Venus (line 29) | class YOLOv3DarkNet53Venus(hub.Module):
    method _initialize (line 30) | def _initialize(self):
    method context (line 33) | def context(self, trainable=True, pretrained=True, get_prediction=False):

FILE: modules/image/object_detection/yolov3_darknet53_venus/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function check_dir (line 19) | def check_dir(dir_path):
  function get_save_image_name (line 27) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 49) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 72) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 80) | def load_label_info(file_path):
  function postprocess (line 89) | def postprocess(paths, images, data_out, score_thresh, label_names, outp...

FILE: modules/image/object_detection/yolov3_darknet53_venus/yolo_head.py
  class MultiClassNMS (line 14) | class MultiClassNMS(object):
    method __init__ (line 16) | def __init__(self, background_label, keep_top_k, nms_threshold, nms_to...
  class YOLOv3Head (line 26) | class YOLOv3Head(object):
    method __init__ (line 39) | def __init__(self,
    method _conv_bn (line 64) | def _conv_bn(self, input, ch_out, filter_size, stride, padding, act='l...
    method _detection_block (line 91) | def _detection_block(self, input, channel, is_test=True, name=None):
    method _upsample (line 108) | def _upsample(self, input, scale=2, name=None):
    method _parse_anchors (line 112) | def _parse_anchors(self, anchors):
    method _get_outputs (line 134) | def _get_outputs(self, input, is_train=True):
    method get_prediction (line 190) | def get_prediction(self, outputs, im_size):

FILE: modules/image/object_detection/yolov3_mobilenet_v1_coco2017/data_feed.py
  function reader (line 14) | def reader(paths=[], images=None):

FILE: modules/image/object_detection/yolov3_mobilenet_v1_coco2017/module.py
  class YOLOv3MobileNetV1Coco2017 (line 28) | class YOLOv3MobileNetV1Coco2017:
    method __init__ (line 29) | def __init__(self):
    method _set_config (line 36) | def _set_config(self):
    method object_detection (line 60) | def object_detection(self,
    method serving_method (line 129) | def serving_method(self, images, **kwargs):
    method run_cmd (line 138) | def run_cmd(self, argvs):
    method add_module_config_arg (line 165) | def add_module_config_arg(self):
    method add_module_input_arg (line 185) | def add_module_input_arg(self):

FILE: modules/image/object_detection/yolov3_mobilenet_v1_coco2017/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function check_dir (line 19) | def check_dir(dir_path):
  function get_save_image_name (line 27) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 49) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 78) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 86) | def load_label_info(file_path):
  function postprocess (line 95) | def postprocess(paths,

FILE: modules/image/object_detection/yolov3_mobilenet_v1_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/yolov3_resnet34_coco2017/data_feed.py
  function reader (line 14) | def reader(paths=[], images=None):

FILE: modules/image/object_detection/yolov3_resnet34_coco2017/module.py
  class YOLOv3ResNet34Coco2017 (line 29) | class YOLOv3ResNet34Coco2017:
    method __init__ (line 30) | def __init__(self):
    method _set_config (line 37) | def _set_config(self):
    method object_detection (line 61) | def object_detection(self,
    method serving_method (line 130) | def serving_method(self, images, **kwargs):
    method run_cmd (line 139) | def run_cmd(self, argvs):
    method add_module_config_arg (line 166) | def add_module_config_arg(self):
    method add_module_input_arg (line 186) | def add_module_input_arg(self):

FILE: modules/image/object_detection/yolov3_resnet34_coco2017/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function check_dir (line 19) | def check_dir(dir_path):
  function get_save_image_name (line 27) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 49) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 78) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 86) | def load_label_info(file_path):
  function postprocess (line 95) | def postprocess(paths,

FILE: modules/image/object_detection/yolov3_resnet34_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/object_detection/yolov3_resnet50_vd_coco2017/data_feed.py
  function reader (line 14) | def reader(paths=[], images=None):

FILE: modules/image/object_detection/yolov3_resnet50_vd_coco2017/module.py
  class YOLOv3ResNet50Coco2017 (line 27) | class YOLOv3ResNet50Coco2017:
    method __init__ (line 28) | def __init__(self):
    method _set_config (line 35) | def _set_config(self):
    method object_detection (line 59) | def object_detection(self,
    method serving_method (line 128) | def serving_method(self, images, **kwargs):
    method run_cmd (line 137) | def run_cmd(self, argvs):
    method add_module_config_arg (line 164) | def add_module_config_arg(self):
    method add_module_input_arg (line 184) | def add_module_input_arg(self):

FILE: modules/image/object_detection/yolov3_resnet50_vd_coco2017/processor.py
  function base64_to_cv2 (line 12) | def base64_to_cv2(b64str):
  function check_dir (line 19) | def check_dir(dir_path):
  function get_save_image_name (line 27) | def get_save_image_name(img, output_dir, image_path):
  function draw_bounding_box_on_image (line 49) | def draw_bounding_box_on_image(image_path, data_list, save_dir):
  function clip_bbox (line 78) | def clip_bbox(bbox, img_width, img_height):
  function load_label_info (line 86) | def load_label_info(file_path):
  function postprocess (line 95) | def postprocess(paths,

FILE: modules/image/object_detection/yolov3_resnet50_vd_coco2017/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 12) | def setUpClass(cls) -> None:
    method tearDownClass (line 23) | def tearDownClass(cls) -> None:
    method test_object_detection1 (line 28) | def test_object_detection1(self):
    method test_object_detection2 (line 47) | def test_object_detection2(self):
    method test_object_detection3 (line 66) | def test_object_detection3(self):
    method test_object_detection4 (line 86) | def test_object_detection4(self):
    method test_object_detection5 (line 93) | def test_object_detection5(self):
    method test_save_inference_model (line 100) | def test_save_inference_model(self):

FILE: modules/image/semantic_segmentation/Extract_Line_Draft/function.py
  function get_normal_map (line 6) | def get_normal_map(img):
  function get_gray_map (line 15) | def get_gray_map(img):
  function get_light_map (line 24) | def get_light_map(img):
  function get_light_map_single (line 34) | def get_light_map_single(img):
  function get_light_map_drawer (line 46) | def get_light_map_drawer(img):
  function get_light_map_drawer2 (line 59) | def get_light_map_drawer2(img):
  function get_light_map_drawer3 (line 69) | def get_light_map_drawer3(img):
  function normalize_pic (line 81) | def normalize_pic(img):
  function superlize_pic (line 86) | def superlize_pic(img):
  function mask_pic (line 92) | def mask_pic(img, mask):
  function resize_img_512 (line 108) | def resize_img_512(img):
  function resize_img_512_3d (line 114) | def resize_img_512_3d(img):
  function denoise_mat (line 120) | def denoise_mat(img, i):
  function show_active_img_and_save_denoise (line 124) | def show_active_img_and_save_denoise(img, path):
  function show_active_img (line 136) | def show_active_img(name, img):
  function get_active_img (line 147) | def get_active_img(img):
  function get_active_img_fil (line 157) | def get_active_img_fil(img):
  function show_double_active_img (line 168) | def show_double_active_img(name, img):
  function debug_pic_helper (line 178) | def debug_pic_helper():

FILE: modules/image/semantic_segmentation/Extract_Line_Draft/module.py
  class ExtractLineDraft (line 20) | class ExtractLineDraft:
    method __init__ (line 21) | def __init__(self):
    method _set_config (line 30) | def _set_config(self):
    method predict (line 65) | def predict(self, input_datas):
    method ExtractLine (line 81) | def ExtractLine(self, image, use_gpu=False):
    method run_cmd (line 152) | def run_cmd(self, argvs):
    method add_module_input_arg (line 181) | def add_module_input_arg(self):
    method check_input_data (line 196) | def check_input_data(self, args):

FILE: modules/image/semantic_segmentation/Extract_Line_Draft/test.py
  class TestHubModule (line 12) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 14) | def setUpClass(cls) -> None:
    method tearDownClass (line 25) | def tearDownClass(cls) -> None:
    method test_ExtractLine1 (line 30) | def test_ExtractLine1(self):
    method test_ExtractLine2 (line 37) | def test_ExtractLine2(self):
    method test_ExtractLine3 (line 44) | def test_ExtractLine3(self):
    method test_ExtractLine4 (line 51) | def test_ExtractLine4(self):
    method test_save_inference_model (line 58) | def test_save_inference_model(self):

FILE: modules/image/semantic_segmentation/ExtremeC3_Portrait_Segmentation/module.py
  class ExtremeC3_Portrait_Segmentation (line 18) | class ExtremeC3_Portrait_Segmentation(Layer):
    method __init__ (line 20) | def __init__(self, name=None, directory=None):
    method load_datas (line 35) | def load_datas(paths, images):
    method preprocess (line 52) | def preprocess(self, datas, batch_size):
    method postprocess (line 82) | def postprocess(self, outputs, datas, output_dir, visualization):
    method Segmentation (line 116) | def Segmentation(self, images=None, paths=None, batch_size=1, output_d...

FILE: modules/image/semantic_segmentation/FCN_HRNet_W18_Face_Seg/model/fcn.py
  class FCN (line 21) | class FCN(nn.Layer):
    method __init__ (line 41) | def __init__(self,
    method forward (line 58) | def forward(self, x):
  class FCNHead (line 66) | class FCNHead(nn.Layer):
    method __init__ (line 79) | def __init__(self, num_classes, backbone_indices=(-1, ), backbone_chan...
    method forward (line 91) | def forward(self, feat_list):

FILE: modules/image/semantic_segmentation/FCN_HRNet_W18_Face_Seg/model/hrnet.py
  class HRNet (line 29) | class HRNet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method forward (line 137) | def forward(self, x):
  class Layer1 (line 161) | class Layer1(nn.Layer):
    method __init__ (line 162) | def __init__(self, num_channels, num_filters, num_blocks, has_se=False...
    method forward (line 179) | def forward(self, x):
  class TransitionLayer (line 186) | class TransitionLayer(nn.Layer):
    method __init__ (line 187) | def __init__(self, in_channels, out_channels, name=None):
    method forward (line 217) | def forward(self, x):
  class Branches (line 230) | class Branches(nn.Layer):
    method __init__ (line 231) | def __init__(self, num_blocks, in_channels, out_channels, has_se=False...
    method forward (line 249) | def forward(self, x):
  class BottleneckBlock (line 259) | class BottleneckBlock(nn.Layer):
    method __init__ (line 260) | def __init__(self, num_channels, num_filters, has_se, stride=1, downsa...
    method forward (line 288) | def forward(self, x):
  class BasicBlock (line 305) | class BasicBlock(nn.Layer):
    method __init__ (line 306) | def __init__(self, num_channels, num_filters, stride=1, has_se=False, ...
    method forward (line 329) | def forward(self, x):
  class SELayer (line 345) | class SELayer(nn.Layer):
    method __init__ (line 346) | def __init__(self, num_channels, num_filters, reduction_ratio, name=No...
    method forward (line 362) | def forward(self, x):
  class Stage (line 374) | class Stage(nn.Layer):
    method __init__ (line 375) | def __init__(self,
    method forward (line 414) | def forward(self, x):
  class HighResolutionModule (line 421) | class HighResolutionModule(nn.Layer):
    method __init__ (line 422) | def __init__(self,
    method forward (line 442) | def forward(self, x):
  class FuseLayers (line 448) | class FuseLayers(nn.Layer):
    method __init__ (line 449) | def __init__(self, in_channels, out_channels, multi_scale_output=True,...
    method forward (line 496) | def forward(self, x):
  function HRNet_W18_Small_V1 (line 523) | def HRNet_W18_Small_V1(**kwargs):
  function HRNet_W18_Small_V2 (line 541) | def HRNet_W18_Small_V2(**kwargs):
  function HRNet_W18 (line 559) | def HRNet_W18(**kwargs):
  function HRNet_W30 (line 577) | def HRNet_W30(**kwargs):
  function HRNet_W32 (line 595) | def HRNet_W32(**kwargs):
  function HRNet_W40 (line 613) | def HRNet_W40(**kwargs):
  function HRNet_W44 (line 631) | def HRNet_W44(**kwargs):
  function HRNet_W48 (line 649) | def HRNet_W48(**kwargs):
  function HRNet_W60 (line 667) | def HRNet_W60(**kwargs):
  function HRNet_W64 (line 685) | def HRNet_W64(**kwargs):

FILE: modules/image/semantic_segmentation/FCN_HRNet_W18_Face_Seg/model/layers.py
  function SyncBatchNorm (line 20) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNReLU (line 28) | class ConvBNReLU(nn.Layer):
    method __init__ (line 29) | def __init__(self, in_channels, out_channels, kernel_size, padding='sa...
    method forward (line 36) | def forward(self, x):
  class ConvBN (line 43) | class ConvBN(nn.Layer):
    method __init__ (line 44) | def __init__(self, in_channels, out_channels, kernel_size, padding='sa...
    method forward (line 49) | def forward(self, x):

FILE: modules/image/semantic_segmentation/FCN_HRNet_W18_Face_Seg/module.py
  class FCN_HRNet_W18_Face_Seg (line 18) | class FCN_HRNet_W18_Face_Seg(nn.Layer):
    method __init__ (line 19) | def __init__(self):
    method load_datas (line 33) | def load_datas(paths, images):
    method preprocess (line 51) | def preprocess(images, batch_size):
    method normPRED (line 75) | def normPRED(d):
    method postprocess (line 84) | def postprocess(self, outputs, datas, output_dir, visualization):
    method predict (line 118) | def predict(self, input_datas):
    method Segmentation (line 134) | def Segmentation(self, images=None, paths=None, batch_size=1, output_d...

FILE: modules/image/semantic_segmentation/SINet_Portrait_Segmentation/module.py
  class SINet_Portrait_Segmentation (line 18) | class SINet_Portrait_Segmentation(Layer):
    method __init__ (line 20) | def __init__(self, name=None, directory=None):
    method load_datas (line 35) | def load_datas(paths, images):
    method preprocess (line 52) | def preprocess(self, datas, batch_size):
    method postprocess (line 82) | def postprocess(self, outputs, datas, output_dir, visualization):
    method Segmentation (line 116) | def Segmentation(self, images=None, paths=None, batch_size=1, output_d...

FILE: modules/image/semantic_segmentation/U2Net/module.py
  class U2Net (line 18) | class U2Net(nn.Layer):
    method __init__ (line 19) | def __init__(self):
    method predict (line 26) | def predict(self, input_datas):
    method Segmentation (line 37) | def Segmentation(self,

FILE: modules/image/semantic_segmentation/U2Net/processor.py
  class Processor (line 8) | class Processor():
    method __init__ (line 9) | def __init__(self, paths, images, batch_size, input_size):
    method load_datas (line 17) | def load_datas(self, paths, images):
    method preprocess (line 34) | def preprocess(self, imgs, batch_size=1, input_size=320):
    method normPRED (line 59) | def normPRED(self, d):
    method postprocess (line 68) | def postprocess(self, outputs, visualization=False, output_dir='output'):

FILE: modules/image/semantic_segmentation/U2Net/u2net.py
  class REBNCONV (line 8) | class REBNCONV(nn.Layer):
    method __init__ (line 9) | def __init__(self, in_ch=3, out_ch=3, dirate=1):
    method forward (line 16) | def forward(self, x):
  function _upsample_like (line 25) | def _upsample_like(src, tar):
  class RSU7 (line 33) | class RSU7(nn.Layer):  #UNet07DRES(nn.Layer):
    method __init__ (line 34) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 65) | def forward(self, x):
  class RSU6 (line 110) | class RSU6(nn.Layer):  #UNet06DRES(nn.Layer):
    method __init__ (line 111) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 138) | def forward(self, x):
  class RSU5 (line 178) | class RSU5(nn.Layer):  #UNet05DRES(nn.Layer):
    method __init__ (line 179) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 202) | def forward(self, x):
  class RSU4 (line 236) | class RSU4(nn.Layer):  #UNet04DRES(nn.Layer):
    method __init__ (line 237) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 256) | def forward(self, x):
  class RSU4F (line 284) | class RSU4F(nn.Layer):  #UNet04FRES(nn.Layer):
    method __init__ (line 285) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 300) | def forward(self, x):
  class U2NET (line 320) | class U2NET(nn.Layer):
    method __init__ (line 321) | def __init__(self, in_ch=3, out_ch=1):
    method forward (line 357) | def forward(self, x):
  class U2NETP (line 424) | class U2NETP(nn.Layer):
    method __init__ (line 425) | def __init__(self, in_ch=3, out_ch=1):
    method forward (line 461) | def forward(self, x):

FILE: modules/image/semantic_segmentation/U2Netp/module.py
  class U2Netp (line 18) | class U2Netp(nn.Layer):
    method __init__ (line 19) | def __init__(self):
    method predict (line 26) | def predict(self, input_datas):
    method Segmentation (line 37) | def Segmentation(self,

FILE: modules/image/semantic_segmentation/U2Netp/processor.py
  class Processor (line 8) | class Processor():
    method __init__ (line 9) | def __init__(self, paths, images, batch_size, input_size):
    method load_datas (line 17) | def load_datas(self, paths, images):
    method preprocess (line 34) | def preprocess(self, imgs, batch_size=1, input_size=320):
    method normPRED (line 59) | def normPRED(self, d):
    method postprocess (line 68) | def postprocess(self, outputs, visualization=False, output_dir='output'):

FILE: modules/image/semantic_segmentation/U2Netp/u2net.py
  class REBNCONV (line 8) | class REBNCONV(nn.Layer):
    method __init__ (line 9) | def __init__(self, in_ch=3, out_ch=3, dirate=1):
    method forward (line 16) | def forward(self, x):
  function _upsample_like (line 25) | def _upsample_like(src, tar):
  class RSU7 (line 33) | class RSU7(nn.Layer):  #UNet07DRES(nn.Layer):
    method __init__ (line 34) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 65) | def forward(self, x):
  class RSU6 (line 110) | class RSU6(nn.Layer):  #UNet06DRES(nn.Layer):
    method __init__ (line 111) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 138) | def forward(self, x):
  class RSU5 (line 178) | class RSU5(nn.Layer):  #UNet05DRES(nn.Layer):
    method __init__ (line 179) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 202) | def forward(self, x):
  class RSU4 (line 236) | class RSU4(nn.Layer):  #UNet04DRES(nn.Layer):
    method __init__ (line 237) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 256) | def forward(self, x):
  class RSU4F (line 284) | class RSU4F(nn.Layer):  #UNet04FRES(nn.Layer):
    method __init__ (line 285) | def __init__(self, in_ch=3, mid_ch=12, out_ch=3):
    method forward (line 300) | def forward(self, x):
  class U2NET (line 320) | class U2NET(nn.Layer):
    method __init__ (line 321) | def __init__(self, in_ch=3, out_ch=1):
    method forward (line 357) | def forward(self, x):
  class U2NETP (line 424) | class U2NETP(nn.Layer):
    method __init__ (line 425) | def __init__(self, in_ch=3, out_ch=1):
    method forward (line 461) | def forward(self, x):

FILE: modules/image/semantic_segmentation/WatermeterSegmentation/module.py
  function base64_to_cv2 (line 18) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 25) | def cv2_to_base64(image):
  function read_images (line 31) | def read_images(paths):
  function rotate (line 41) | def rotate(
  class MODULE (line 101) | class MODULE(hub.Module):
    method _initialize (line 102) | def _initialize(self, **kwargs):
    method predict (line 106) | def predict(self, images=None, paths=None, data=None, batch_size=1, us...
    method cutPic (line 125) | def cutPic(self, picUrl):
    method serving_method (line 155) | def serving_method(self, images, **kwargs):
    method run_cmd (line 184) | def run_cmd(self, argvs):
    method add_module_config_arg (line 202) | def add_module_config_arg(self):
    method add_module_input_arg (line 208) | def add_module_input_arg(self):

FILE: modules/image/semantic_segmentation/WatermeterSegmentation/serving_client_demo.py
  function cv2_to_base64 (line 8) | def cv2_to_base64(image):

FILE: modules/image/semantic_segmentation/ace2p/data_feed.py
  function _box2cs (line 14) | def _box2cs(box, aspect_ratio):
  function _xywh2cs (line 19) | def _xywh2cs(x, y, w, h, aspect_ratio, pixel_std=200):
  function preprocess (line 31) | def preprocess(org_im, scale, rotation):
  function reader (line 64) | def reader(images, paths, scale, rotation):

FILE: modules/image/semantic_segmentation/ace2p/module.py
  class ACE2P (line 27) | class ACE2P:
    method __init__ (line 28) | def __init__(self):
    method _set_config (line 40) | def _set_config(self):
    method segmentation (line 63) | def segmentation(self,
    method serving_method (line 144) | def serving_method(self, images, **kwargs):
    method run_cmd (line 154) | def run_cmd(self, argvs):
    method add_module_config_arg (line 177) | def add_module_config_arg(self):
    method add_module_input_arg (line 189) | def add_module_input_arg(self):

FILE: modules/image/semantic_segmentation/ace2p/processor.py
  function cv2_to_base64 (line 17) | def cv2_to_base64(image):
  function base64_to_cv2 (line 22) | def base64_to_cv2(b64str):
  function check_dir (line 29) | def check_dir(dir_path):
  function get_save_image_name (line 43) | def get_save_image_name(org_im, org_im_path, output_dir):
  function get_direction (line 59) | def get_direction(src_point, rot_rad):
  function get_3rd_point (line 67) | def get_3rd_point(a, b):
  function get_affine_transform (line 72) | def get_affine_transform(center, scale, rot, output_size, shift=np.array...
  function transform_logits (line 100) | def transform_logits(logits, center, scale, width, height, input_size):
  function get_palette (line 116) | def get_palette(num_cls):
  function postprocess (line 143) | def postprocess(data_out, org_im, org_im_path, image_info, output_dir, v...

FILE: modules/image/semantic_segmentation/ace2p/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 34) | def tearDownClass(cls) -> None:
    method test_segmentation1 (line 39) | def test_segmentation1(self):
    method test_segmentation2 (line 47) | def test_segmentation2(self):
    method test_segmentation3 (line 55) | def test_segmentation3(self):
    method test_segmentation4 (line 63) | def test_segmentation4(self):
    method test_segmentation5 (line 71) | def test_segmentation5(self):
    method test_segmentation6 (line 78) | def test_segmentation6(self):
    method test_save_inference_model (line 85) | def test_save_inference_model(self):

FILE: modules/image/semantic_segmentation/ann_resnet50_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 30) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 50) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 56) | class ConvBN(nn.Layer):
    method __init__ (line 59) | def __init__(self,
    method forward (line 70) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 76) | class ConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 91) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 98) | class Activation(nn.Layer):
    method __init__ (line 124) | def __init__(self, act: str = None):
    method forward (line 140) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 148) | class ASPPModule(nn.Layer):
    method __init__ (line 161) | def __init__(self,
    method forward (line 203) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 230) | class AuxLayer(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 263) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 270) | class Add(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 274) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name: str = None):

FILE: modules/image/semantic_segmentation/ann_resnet50_cityscapes/module.py
  class ANN (line 37) | class ANN(nn.Layer):
    method __init__ (line 58) | def __init__(self,
    method transform (line 89) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 92) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class ANNHead (line 105) | class ANNHead(nn.Layer):
    method __init__ (line 125) | def __init__(self,
    method forward (line 174) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class AFNB (line 190) | class AFNB(nn.Layer):
    method __init__ (line 205) | def __init__(self,
    method forward (line 228) | def forward(self, low_feats: List[paddle.Tensor], high_feats: List[pad...
  class APNB (line 240) | class APNB(nn.Layer):
    method __init__ (line 254) | def __init__(self,
    method forward (line 276) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  function _pp_module (line 288) | def _pp_module(x: paddle.Tensor, psp_size: List[int]) -> paddle.Tensor:
  class SelfAttentionBlock_AFNB (line 299) | class SelfAttentionBlock_AFNB(nn.Layer):
    method __init__ (line 313) | def __init__(self,
    method forward (line 351) | def forward(self, low_feats: List[paddle.Tensor], high_feats: List[pad...
  class SelfAttentionBlock_APNB (line 380) | class SelfAttentionBlock_APNB(nn.Layer):
    method __init__ (line 393) | def __init__(self,
    method forward (line 424) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ann_resnet50_cityscapes/resnet.py
  class ConvBNLayer (line 23) | class ConvBNLayer(nn.Layer):
    method __init__ (line 24) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 73) | def __init__(self,
    method forward (line 122) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 137) | class BasicBlock(nn.Layer):
    method __init__ (line 138) | def __init__(self,
    method forward (line 178) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 192) | class ResNet_vd(nn.Layer):
    method __init__ (line 208) | def __init__(self,
    method forward (line 342) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 359) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/ann_resnet50_voc/layers.py
  function SyncBatchNorm (line 23) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 31) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 34) | def __init__(self,
    method forward (line 51) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 57) | class ConvBN(nn.Layer):
    method __init__ (line 60) | def __init__(self,
    method forward (line 71) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 77) | class ConvBNReLU(nn.Layer):
    method __init__ (line 80) | def __init__(self,
    method forward (line 92) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 99) | class Activation(nn.Layer):
    method __init__ (line 125) | def __init__(self, act: str = None):
    method forward (line 141) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 149) | class ASPPModule(nn.Layer):
    method __init__ (line 162) | def __init__(self,
    method forward (line 204) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 231) | class AuxLayer(nn.Layer):
    method __init__ (line 242) | def __init__(self,
    method forward (line 264) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 271) | class Add(nn.Layer):
    method __init__ (line 272) | def __init__(self):
    method forward (line 275) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name: str = None...

FILE: modules/image/semantic_segmentation/ann_resnet50_voc/module.py
  class ANN (line 37) | class ANN(nn.Layer):
    method __init__ (line 58) | def __init__(self,
    method transform (line 89) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 92) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class ANNHead (line 105) | class ANNHead(nn.Layer):
    method __init__ (line 125) | def __init__(self,
    method forward (line 174) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class AFNB (line 190) | class AFNB(nn.Layer):
    method __init__ (line 205) | def __init__(self,
    method forward (line 228) | def forward(self, low_feats: List[paddle.Tensor], high_feats: List[pad...
  class APNB (line 240) | class APNB(nn.Layer):
    method __init__ (line 254) | def __init__(self,
    method forward (line 276) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  function _pp_module (line 288) | def _pp_module(x: paddle.Tensor, psp_size: List[int]) -> paddle.Tensor:
  class SelfAttentionBlock_AFNB (line 299) | class SelfAttentionBlock_AFNB(nn.Layer):
    method __init__ (line 313) | def __init__(self,
    method forward (line 351) | def forward(self, low_feats: List[paddle.Tensor], high_feats: List[pad...
  class SelfAttentionBlock_APNB (line 380) | class SelfAttentionBlock_APNB(nn.Layer):
    method __init__ (line 393) | def __init__(self,
    method forward (line 424) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ann_resnet50_voc/resnet.py
  class ConvBNLayer (line 23) | class ConvBNLayer(nn.Layer):
    method __init__ (line 24) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 73) | def __init__(self,
    method forward (line 122) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 137) | class BasicBlock(nn.Layer):
    method __init__ (line 138) | def __init__(self,
    method forward (line 178) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 192) | class ResNet_vd(nn.Layer):
    method __init__ (line 208) | def __init__(self,
    method forward (line 342) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 359) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/bisenet_lane_segmentation/lane_processor/get_lane_coords.py
  class LaneProcessor (line 21) | class LaneProcessor:
    method __init__ (line 22) | def __init__(self,
    method get_lane_coords (line 39) | def get_lane_coords(self, seg_pred):
    method process_gap (line 50) | def process_gap(self, coordinate):
    method get_coords (line 86) | def get_coords(self, heat_map):
    method fix_outliers (line 107) | def fix_outliers(self, coords):
    method heatmap2coords (line 132) | def heatmap2coords(self, seg_pred):
    method add_coords (line 150) | def add_coords(self, coordinates, coords):

FILE: modules/image/semantic_segmentation/bisenet_lane_segmentation/lane_processor/lane.py
  class LaneEval (line 21) | class LaneEval(object):
    method get_angle (line 27) | def get_angle(xs, y_samples):
    method line_accuracy (line 38) | def line_accuracy(pred, gt, thresh):
    method bench (line 44) | def bench(pred, gt, y_samples, running_time):
    method bench_one_submit (line 80) | def bench_one_submit(pred_file, gt_file):

FILE: modules/image/semantic_segmentation/bisenet_lane_segmentation/lane_processor/tusimple_processor.py
  function mkdir (line 25) | def mkdir(path):
  class TusimpleProcessor (line 31) | class TusimpleProcessor:
    method __init__ (line 32) | def __init__(self,
    method dump_data_to_json (line 56) | def dump_data_to_json(self,
    method predict (line 98) | def predict(self, output, im_path):
    method bench_one_submit (line 102) | def bench_one_submit(self):
    method draw (line 115) | def draw(self, img, coords, file_path=None):

FILE: modules/image/semantic_segmentation/bisenet_lane_segmentation/module.py
  class BiSeNetLane (line 42) | class BiSeNetLane(nn.Layer):
    method __init__ (line 52) | def __init__(self,
    method forward (line 81) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method predict (line 85) | def predict(self, image_list: list, visualization: bool = False, save_...
    method serving_method (line 118) | def serving_method(self, images: str, **kwargs) -> dict:
    method run_cmd (line 130) | def run_cmd(self, argvs: list) -> List[np.ndarray]:
    method add_module_config_arg (line 150) | def add_module_config_arg(self):
    method add_module_input_arg (line 160) | def add_module_input_arg(self):

FILE: modules/image/semantic_segmentation/bisenet_lane_segmentation/processor.py
  function get_reverse_list (line 12) | def get_reverse_list(ori_shape: list, transforms: Callable) -> list:
  function reverse_transform (line 94) | def reverse_transform(pred: paddle.Tensor, ori_shape: list, transforms: ...
  class Crop (line 122) | class Crop:
    method __init__ (line 133) | def __init__(self, up_h_off: int = 0, down_h_off: int = 0, left_w_off:...
    method __call__ (line 139) | def __call__(self, im: np.ndarray, label: np.ndarray = None) -> Tuple[...
  function cv2_to_base64 (line 170) | def cv2_to_base64(image: np.ndarray) -> str:
  function base64_to_cv2 (line 178) | def base64_to_cv2(b64str: str) -> np.ndarray:

FILE: modules/image/semantic_segmentation/bisenetv2_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNReLU (line 30) | class ConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 40) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 47) | class ConvBN(nn.Layer):
    method __init__ (line 50) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 55) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvReLUPool (line 61) | class ConvReLUPool(nn.Layer):
    method __init__ (line 64) | def __init__(self, in_channels: int, out_channels: int):
    method forward (line 68) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 75) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 78) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 89) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class DepthwiseConvBN (line 95) | class DepthwiseConvBN(nn.Layer):
    method __init__ (line 98) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 109) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 114) | class AuxLayer(nn.Layer):
    method __init__ (line 125) | def __init__(self, in_channels: int, inter_channels: int, out_channels...
    method forward (line 134) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 141) | class Activation(nn.Layer):
    method __init__ (line 167) | def __init__(self, act: str = None):
    method forward (line 182) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/bisenetv2_cityscapes/module.py
  class BiSeNetV2 (line 37) | class BiSeNetV2(nn.Layer):
    method __init__ (line 53) | def __init__(self, num_classes: int = 19, lambd: float = 0.25, align_c...
    method transform (line 86) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 89) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class StemBlock (line 111) | class StemBlock(nn.Layer):
    method __init__ (line 112) | def __init__(self, in_dim: int, out_dim: int):
    method forward (line 124) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ContextEmbeddingBlock (line 132) | class ContextEmbeddingBlock(nn.Layer):
    method __init__ (line 133) | def __init__(self, in_dim: int, out_dim: int):
    method forward (line 142) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GatherAndExpansionLayer1 (line 149) | class GatherAndExpansionLayer1(nn.Layer):
    method __init__ (line 152) | def __init__(self, in_dim: int, out_dim: int, expand: int):
    method forward (line 161) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GatherAndExpansionLayer2 (line 165) | class GatherAndExpansionLayer2(nn.Layer):
    method __init__ (line 168) | def __init__(self, in_dim: int, out_dim: int, expand: int):
    method forward (line 180) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class DetailBranch (line 184) | class DetailBranch(nn.Layer):
    method __init__ (line 187) | def __init__(self, in_channels: int):
    method forward (line 206) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SemanticBranch (line 210) | class SemanticBranch(nn.Layer):
    method __init__ (line 213) | def __init__(self, in_channels: int):
    method forward (line 229) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BGA (line 238) | class BGA(nn.Layer):
    method __init__ (line 241) | def __init__(self, out_dim: int, align_corners: bool):
    method forward (line 259) | def forward(self, dfm: int, sfm: int) -> paddle.Tensor:
  class SegHead (line 277) | class SegHead(nn.Layer):
    method __init__ (line 278) | def __init__(self, in_dim: int, mid_dim: int, num_classes: int):
    method forward (line 285) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/danet_resnet50_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 139) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 142) | def __init__(self,
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 165) | class ConvBN(nn.Layer):
    method __init__ (line 168) | def __init__(self,
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 185) | class ConvBNReLU(nn.Layer):
    method __init__ (line 188) | def __init__(self,
    method forward (line 200) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 207) | class Activation(nn.Layer):
    method __init__ (line 241) | def __init__(self, act: str = None):
    method forward (line 257) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 265) | class ASPPModule(nn.Layer):
    method __init__ (line 279) | def __init__(self,
    method forward (line 321) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/danet_resnet50_cityscapes/module.py
  class DANet (line 38) | class DANet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method forward (line 83) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method transform (line 100) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
  class DAHead (line 104) | class DAHead(nn.Layer):
    method __init__ (line 113) | def __init__(self, num_classes: int, in_channels: int):
    method forward (line 137) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class PAM (line 159) | class PAM(nn.Layer):
    method __init__ (line 162) | def __init__(self, in_channels: int):
    method forward (line 177) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class CAM (line 206) | class CAM(nn.Layer):
    method __init__ (line 209) | def __init__(self, channels: int):
    method forward (line 218) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/danet_resnet50_cityscapes/resnet.py
  class ConvBNLayer (line 21) | class ConvBNLayer(nn.Layer):
    method __init__ (line 22) | def __init__(self,
    method forward (line 60) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 70) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 135) | class BasicBlock(nn.Layer):
    method __init__ (line 136) | def __init__(self,
    method forward (line 176) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 190) | class ResNet_vd(nn.Layer):
    method __init__ (line 206) | def __init__(self,
    method forward (line 340) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 357) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/danet_resnet50_voc/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 139) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 142) | def __init__(self,
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 165) | class ConvBN(nn.Layer):
    method __init__ (line 168) | def __init__(self,
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 185) | class ConvBNReLU(nn.Layer):
    method __init__ (line 188) | def __init__(self,
    method forward (line 200) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 207) | class Activation(nn.Layer):
    method __init__ (line 241) | def __init__(self, act: str = None):
    method forward (line 257) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 265) | class ASPPModule(nn.Layer):
    method __init__ (line 279) | def __init__(self,
    method forward (line 321) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/danet_resnet50_voc/module.py
  class DANet (line 38) | class DANet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method forward (line 83) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method transform (line 100) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
  class DAHead (line 105) | class DAHead(nn.Layer):
    method __init__ (line 114) | def __init__(self, num_classes: int, in_channels: int):
    method forward (line 138) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class PAM (line 160) | class PAM(nn.Layer):
    method __init__ (line 163) | def __init__(self, in_channels: int):
    method forward (line 178) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class CAM (line 207) | class CAM(nn.Layer):
    method __init__ (line 210) | def __init__(self, channels: int):
    method forward (line 219) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/danet_resnet50_voc/resnet.py
  class ConvBNLayer (line 21) | class ConvBNLayer(nn.Layer):
    method __init__ (line 22) | def __init__(self,
    method forward (line 60) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 70) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 135) | class BasicBlock(nn.Layer):
    method __init__ (line 136) | def __init__(self,
    method forward (line 176) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 190) | class ResNet_vd(nn.Layer):
    method __init__ (line 206) | def __init__(self,
    method forward (line 340) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 357) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/deeplabv3p_resnet50_cityscapes/layers.py
  function SyncBatchNorm (line 21) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 59) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self,
    method forward (line 109) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 128) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 131) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 142) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 148) | class ConvBN(nn.Layer):
    method __init__ (line 151) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 156) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 162) | class ConvBNReLU(nn.Layer):
    method __init__ (line 165) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 171) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 178) | class Activation(nn.Layer):
    method __init__ (line 204) | def __init__(self, act: str = None):
    method forward (line 219) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 226) | class ASPPModule(nn.Layer):
    method __init__ (line 240) | def __init__(self,
    method forward (line 279) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/deeplabv3p_resnet50_cityscapes/module.py
  class DeepLabV3PResnet50 (line 38) | class DeepLabV3PResnet50(nn.Layer):
    method __init__ (line 64) | def __init__(self,
    method transform (line 90) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 93) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class DeepLabV3PHead (line 101) | class DeepLabV3PHead(nn.Layer):
    method __init__ (line 121) | def __init__(self, num_classes: int, backbone_indices: Tuple[paddle.Te...
    method forward (line 131) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class Decoder (line 141) | class Decoder(nn.Layer):
    method __init__ (line 151) | def __init__(self, num_classes: int, in_channels: int, align_corners: ...
    method forward (line 162) | def forward(self, x: paddle.Tensor, low_level_feat: paddle.Tensor) -> ...

FILE: modules/image/semantic_segmentation/deeplabv3p_resnet50_cityscapes/resnet.py
  class BasicBlock (line 22) | class BasicBlock(nn.Layer):
    method __init__ (line 23) | def __init__(self,
    method forward (line 53) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet50_vd (line 66) | class ResNet50_vd(nn.Layer):
    method __init__ (line 67) | def __init__(self, multi_grid: Tuple[int] = (1, 2, 4)):
    method forward (line 105) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/deeplabv3p_resnet50_voc/layers.py
  function SyncBatchNorm (line 21) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 59) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self,
    method forward (line 109) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 128) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 131) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 142) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 148) | class ConvBN(nn.Layer):
    method __init__ (line 151) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 156) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 162) | class ConvBNReLU(nn.Layer):
    method __init__ (line 165) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 171) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 178) | class Activation(nn.Layer):
    method __init__ (line 212) | def __init__(self, act: str = None):
    method forward (line 227) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 235) | class ASPPModule(nn.Layer):
    method __init__ (line 249) | def __init__(self,
    method forward (line 288) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/deeplabv3p_resnet50_voc/module.py
  class DeepLabV3PResnet50 (line 38) | class DeepLabV3PResnet50(nn.Layer):
    method __init__ (line 64) | def __init__(self,
    method transform (line 90) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 93) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class DeepLabV3PHead (line 101) | class DeepLabV3PHead(nn.Layer):
    method __init__ (line 121) | def __init__(self, num_classes: int, backbone_indices: Tuple[paddle.Te...
    method forward (line 131) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class Decoder (line 141) | class Decoder(nn.Layer):
    method __init__ (line 151) | def __init__(self, num_classes: int, in_channels: int, align_corners: ...
    method forward (line 162) | def forward(self, x: paddle.Tensor, low_level_feat: paddle.Tensor) -> ...

FILE: modules/image/semantic_segmentation/deeplabv3p_resnet50_voc/resnet.py
  class BasicBlock (line 21) | class BasicBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self,
    method forward (line 52) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet50_vd (line 65) | class ResNet50_vd(nn.Layer):
    method __init__ (line 66) | def __init__(self, multi_grid: tuple = (1, 2, 4)):
    method forward (line 104) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/data_feed.py
  function reader (line 12) | def reader(images=None, paths=None):

FILE: modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/module.py
  class DeeplabV3pXception65HumanSeg (line 29) | class DeeplabV3pXception65HumanSeg:
    method __init__ (line 31) | def __init__(self):
    method _set_config (line 35) | def _set_config(self):
    method segmentation (line 58) | def segmentation(self,
    method serving_method (line 139) | def serving_method(self, images, **kwargs):
    method run_cmd (line 149) | def run_cmd(self, argvs):
    method add_module_config_arg (line 171) | def add_module_config_arg(self):
    method add_module_input_arg (line 189) | def add_module_input_arg(self):

FILE: modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/processor.py
  function cv2_to_base64 (line 16) | def cv2_to_base64(image):
  function base64_to_cv2 (line 21) | def base64_to_cv2(b64str):
  function postprocess (line 28) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 64) | def check_dir(dir_path):
  function get_save_image_name (line 72) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_segmentation1 (line 32) | def test_segmentation1(self):
    method test_segmentation2 (line 40) | def test_segmentation2(self):
    method test_segmentation3 (line 48) | def test_segmentation3(self):
    method test_segmentation4 (line 56) | def test_segmentation4(self):
    method test_segmentation5 (line 64) | def test_segmentation5(self):
    method test_segmentation6 (line 71) | def test_segmentation6(self):
    method test_save_inference_model (line 78) | def test_save_inference_model(self):

FILE: modules/image/semantic_segmentation/fastscnn_cityscapes/layers.py
  function SyncBatchNorm (line 23) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNReLU (line 31) | class ConvBNReLU(nn.Layer):
    method __init__ (line 34) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 41) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 48) | class ConvBN(nn.Layer):
    method __init__ (line 51) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 56) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvReLUPool (line 62) | class ConvReLUPool(nn.Layer):
    method __init__ (line 65) | def __init__(self, in_channels: int, out_channels: int):
    method forward (line 69) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 76) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 90) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class DepthwiseConvBN (line 96) | class DepthwiseConvBN(nn.Layer):
    method __init__ (line 99) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 109) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 114) | class AuxLayer(nn.Layer):
    method __init__ (line 125) | def __init__(self, in_channels: int, inter_channels: int, out_channels...
    method forward (line 134) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 141) | class Activation(nn.Layer):
    method __init__ (line 167) | def __init__(self, act: str = None):
    method forward (line 182) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class PPModule (line 189) | class PPModule(nn.Layer):
    method __init__ (line 202) | def __init__(self, in_channels: int, out_channels: int, bin_sizes: Tup...
    method _make_stage (line 222) | def _make_stage(self, in_channels: int, out_channels: int, size: int):
    method forward (line 246) | def forward(self, input: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fastscnn_cityscapes/module.py
  class FastSCNN (line 36) | class FastSCNN(nn.Layer):
    method __init__ (line 51) | def __init__(self, num_classes: int = 19, align_corners: bool = False,...
    method transform (line 79) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 82) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class LearningToDownsample (line 95) | class LearningToDownsample(nn.Layer):
    method __init__ (line 105) | def __init__(self, dw_channels1: int = 32, dw_channels2: int = 48, out...
    method forward (line 114) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GlobalFeatureExtractor (line 121) | class GlobalFeatureExtractor(nn.Layer):
    method __init__ (line 136) | def __init__(self, in_channels: int, block_channels: int, out_channels...
    method _make_layer (line 150) | def _make_layer(self,
    method forward (line 163) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class InvertedBottleneck (line 171) | class InvertedBottleneck(nn.Layer):
    method __init__ (line 181) | def __init__(self, in_channels: int, out_channels: int, expansion: int...
    method forward (line 202) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FeatureFusionModule (line 209) | class FeatureFusionModule(nn.Layer):
    method __init__ (line 221) | def __init__(self, high_in_channels: int, low_in_channels: int, out_ch...
    method forward (line 237) | def forward(self, high_res_input: int, low_res_input: int) -> paddle.T...
  class Classifier (line 248) | class Classifier(nn.Layer):
    method __init__ (line 257) | def __init__(self, input_channels: int, num_classes: int):
    method forward (line 270) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw18_cityscapes/hrnet.py
  class HRNet_W18 (line 25) | class HRNet_W18(nn.Layer):
    method __init__ (line 51) | def __init__(self,
    method forward (line 131) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Layer1 (line 155) | class Layer1(nn.Layer):
    method __init__ (line 156) | def __init__(self, num_channels: int, num_filters: int, num_blocks: in...
    method forward (line 173) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class TransitionLayer (line 180) | class TransitionLayer(nn.Layer):
    method __init__ (line 181) | def __init__(self, in_channels: int, out_channels: int, name=None):
    method forward (line 211) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Branches (line 224) | class Branches(nn.Layer):
    method __init__ (line 225) | def __init__(self, num_blocks: int, in_channels: int, out_channels: in...
    method forward (line 243) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 253) | class BottleneckBlock(nn.Layer):
    method __init__ (line 254) | def __init__(self,
    method forward (line 288) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 305) | class BasicBlock(nn.Layer):
    method __init__ (line 306) | def __init__(self,
    method forward (line 335) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 351) | class SELayer(nn.Layer):
    method __init__ (line 352) | def __init__(self, num_channels: int, num_filters: int, reduction_rati...
    method forward (line 368) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Stage (line 380) | class Stage(nn.Layer):
    method __init__ (line 381) | def __init__(self,
    method forward (line 420) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class HighResolutionModule (line 427) | class HighResolutionModule(nn.Layer):
    method __init__ (line 428) | def __init__(self,
    method forward (line 448) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FuseLayers (line 454) | class FuseLayers(nn.Layer):
    method __init__ (line 455) | def __init__(self,
    method forward (line 507) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw18_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 60) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 70) | class BottleneckBlock(nn.Layer):
    method __init__ (line 73) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 129) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 132) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 143) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 149) | class ConvBN(nn.Layer):
    method __init__ (line 152) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 157) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 163) | class ConvBNReLU(nn.Layer):
    method __init__ (line 166) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 172) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 179) | class Activation(nn.Layer):
    method __init__ (line 205) | def __init__(self, act: str = None):
    method forward (line 220) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 227) | class ASPPModule(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 280) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw18_cityscapes/module.py
  class FCN (line 38) | class FCN(nn.Layer):
    method __init__ (line 57) | def __init__(self,
    method transform (line 84) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 87) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class FCNHead (line 96) | class FCNHead(nn.Layer):
    method __init__ (line 111) | def __init__(self,
    method forward (line 127) | def forward(self, feat_list: nn.Layer) -> List[paddle.Tensor]:

FILE: modules/image/semantic_segmentation/fcn_hrnetw18_voc/hrnet.py
  class HRNet_W18 (line 25) | class HRNet_W18(nn.Layer):
    method __init__ (line 51) | def __init__(self,
    method forward (line 131) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Layer1 (line 155) | class Layer1(nn.Layer):
    method __init__ (line 156) | def __init__(self, num_channels: int, num_filters: int, num_blocks: in...
    method forward (line 173) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class TransitionLayer (line 180) | class TransitionLayer(nn.Layer):
    method __init__ (line 181) | def __init__(self, in_channels: int, out_channels: int, name=None):
    method forward (line 211) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Branches (line 224) | class Branches(nn.Layer):
    method __init__ (line 225) | def __init__(self, num_blocks: int, in_channels: int, out_channels: in...
    method forward (line 243) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 253) | class BottleneckBlock(nn.Layer):
    method __init__ (line 254) | def __init__(self,
    method forward (line 288) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 305) | class BasicBlock(nn.Layer):
    method __init__ (line 306) | def __init__(self,
    method forward (line 335) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 351) | class SELayer(nn.Layer):
    method __init__ (line 352) | def __init__(self, num_channels: int, num_filters: int, reduction_rati...
    method forward (line 368) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Stage (line 380) | class Stage(nn.Layer):
    method __init__ (line 381) | def __init__(self,
    method forward (line 420) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class HighResolutionModule (line 427) | class HighResolutionModule(nn.Layer):
    method __init__ (line 428) | def __init__(self,
    method forward (line 448) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FuseLayers (line 454) | class FuseLayers(nn.Layer):
    method __init__ (line 455) | def __init__(self,
    method forward (line 507) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw18_voc/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 60) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 70) | class BottleneckBlock(nn.Layer):
    method __init__ (line 73) | def __init__(self,
    method forward (line 110) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 129) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 132) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 143) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 149) | class ConvBN(nn.Layer):
    method __init__ (line 152) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 157) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 163) | class ConvBNReLU(nn.Layer):
    method __init__ (line 166) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 172) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 179) | class Activation(nn.Layer):
    method __init__ (line 205) | def __init__(self, act: str = None):
    method forward (line 220) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 227) | class ASPPModule(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 280) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw18_voc/module.py
  class FCN (line 38) | class FCN(nn.Layer):
    method __init__ (line 57) | def __init__(self,
    method transform (line 84) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 87) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class FCNHead (line 96) | class FCNHead(nn.Layer):
    method __init__ (line 111) | def __init__(self,
    method forward (line 127) | def forward(self, feat_list: nn.Layer) -> List[paddle.Tensor]:

FILE: modules/image/semantic_segmentation/fcn_hrnetw48_cityscapes/hrnet.py
  class HRNet_W48 (line 25) | class HRNet_W48(nn.Layer):
    method __init__ (line 49) | def __init__(self,
    method forward (line 128) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class Layer1 (line 152) | class Layer1(nn.Layer):
    method __init__ (line 153) | def __init__(self, num_channels: int, num_filters: int, num_blocks: in...
    method forward (line 170) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class TransitionLayer (line 177) | class TransitionLayer(nn.Layer):
    method __init__ (line 178) | def __init__(self, in_channels: int, out_channels: int, name: str = No...
    method forward (line 208) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Branches (line 221) | class Branches(nn.Layer):
    method __init__ (line 222) | def __init__(self, num_blocks: int, in_channels: int, out_channels: in...
    method forward (line 240) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 250) | class BottleneckBlock(nn.Layer):
    method __init__ (line 251) | def __init__(self,
    method forward (line 285) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 302) | class BasicBlock(nn.Layer):
    method __init__ (line 303) | def __init__(self,
    method forward (line 332) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 348) | class SELayer(nn.Layer):
    method __init__ (line 349) | def __init__(self, num_channels: int, num_filters: int, reduction_rati...
    method forward (line 365) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Stage (line 377) | class Stage(nn.Layer):
    method __init__ (line 378) | def __init__(self,
    method forward (line 417) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class HighResolutionModule (line 424) | class HighResolutionModule(nn.Layer):
    method __init__ (line 425) | def __init__(self,
    method forward (line 445) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FuseLayers (line 451) | class FuseLayers(nn.Layer):
    method __init__ (line 452) | def __init__(self,
    method forward (line 504) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw48_cityscapes/layers.py
  function SyncBatchNorm (line 23) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 31) | class ConvBNLayer(nn.Layer):
    method __init__ (line 34) | def __init__(self,
    method forward (line 61) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 71) | class BottleneckBlock(nn.Layer):
    method __init__ (line 74) | def __init__(self,
    method forward (line 111) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 130) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 133) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 144) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 150) | class ConvBN(nn.Layer):
    method __init__ (line 153) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 158) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 164) | class ConvBNReLU(nn.Layer):
    method __init__ (line 167) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 173) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 180) | class Activation(nn.Layer):
    method __init__ (line 206) | def __init__(self, act: str = None):
    method forward (line 221) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 228) | class ASPPModule(nn.Layer):
    method __init__ (line 242) | def __init__(self,
    method forward (line 281) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw48_cityscapes/module.py
  class FCN (line 38) | class FCN(nn.Layer):
    method __init__ (line 57) | def __init__(self,
    method transform (line 84) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 87) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class FCNHead (line 96) | class FCNHead(nn.Layer):
    method __init__ (line 111) | def __init__(self,
    method forward (line 127) | def forward(self, feat_list: nn.Layer) -> List[paddle.Tensor]:

FILE: modules/image/semantic_segmentation/fcn_hrnetw48_voc/hrnet.py
  class HRNet_W48 (line 25) | class HRNet_W48(nn.Layer):
    method __init__ (line 49) | def __init__(self,
    method forward (line 128) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class Layer1 (line 152) | class Layer1(nn.Layer):
    method __init__ (line 153) | def __init__(self, num_channels: int, num_filters: int, num_blocks: in...
    method forward (line 170) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class TransitionLayer (line 177) | class TransitionLayer(nn.Layer):
    method __init__ (line 178) | def __init__(self, in_channels: int, out_channels: int, name: str = No...
    method forward (line 208) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Branches (line 221) | class Branches(nn.Layer):
    method __init__ (line 222) | def __init__(self, num_blocks: int, in_channels: int, out_channels: in...
    method forward (line 240) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 250) | class BottleneckBlock(nn.Layer):
    method __init__ (line 251) | def __init__(self,
    method forward (line 285) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 302) | class BasicBlock(nn.Layer):
    method __init__ (line 303) | def __init__(self,
    method forward (line 332) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 348) | class SELayer(nn.Layer):
    method __init__ (line 349) | def __init__(self, num_channels: int, num_filters: int, reduction_rati...
    method forward (line 365) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Stage (line 377) | class Stage(nn.Layer):
    method __init__ (line 378) | def __init__(self,
    method forward (line 417) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class HighResolutionModule (line 424) | class HighResolutionModule(nn.Layer):
    method __init__ (line 425) | def __init__(self,
    method forward (line 445) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FuseLayers (line 451) | class FuseLayers(nn.Layer):
    method __init__ (line 452) | def __init__(self,
    method forward (line 504) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw48_voc/layers.py
  function SyncBatchNorm (line 24) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 32) | class ConvBNLayer(nn.Layer):
    method __init__ (line 35) | def __init__(self,
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 112) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 131) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 134) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 145) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 151) | class ConvBN(nn.Layer):
    method __init__ (line 154) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 165) | class ConvBNReLU(nn.Layer):
    method __init__ (line 168) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 174) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 181) | class Activation(nn.Layer):
    method __init__ (line 207) | def __init__(self, act: str = None):
    method forward (line 222) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 229) | class ASPPModule(nn.Layer):
    method __init__ (line 243) | def __init__(self,
    method forward (line 282) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/fcn_hrnetw48_voc/module.py
  class FCN (line 38) | class FCN(nn.Layer):
    method __init__ (line 57) | def __init__(self,
    method transform (line 84) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 87) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class FCNHead (line 96) | class FCNHead(nn.Layer):
    method __init__ (line 111) | def __init__(self,
    method forward (line 127) | def forward(self, feat_list: nn.Layer) -> List[paddle.Tensor]:

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_ade20k/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 139) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 142) | def __init__(self,
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 165) | class ConvBN(nn.Layer):
    method __init__ (line 168) | def __init__(self,
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 185) | class ConvBNReLU(nn.Layer):
    method __init__ (line 188) | def __init__(self,
    method forward (line 200) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 207) | class Activation(nn.Layer):
    method __init__ (line 241) | def __init__(self, act: str = None):
    method forward (line 257) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 265) | class ASPPModule(nn.Layer):
    method __init__ (line 279) | def __init__(self,
    method forward (line 321) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_ade20k/module.py
  class GINetResNet101 (line 39) | class GINetResNet101(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 91) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method base_forward (line 94) | def base_forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method forward (line 103) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GIHead (line 124) | class GIHead(nn.Layer):
    method __init__ (line 127) | def __init__(self, in_channels: int, nclass: int):
    method forward (line 157) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GlobalReasonUnit (line 172) | class GlobalReasonUnit(nn.Layer):
    method __init__ (line 178) | def __init__(self, in_channels: int, num_state: int = 256, num_node: i...
    method forward (line 191) | def forward(self, x: paddle.Tensor, inp: paddle.Tensor) -> List[paddle...
  class GraphLayer (line 217) | class GraphLayer(nn.Layer):
    method __init__ (line 218) | def __init__(self, num_state: int, num_node: int, num_class: int):
    method forward (line 234) | def forward(self, inp: paddle.Tensor, vis_node: paddle.Tensor) -> List...
  class GCN (line 244) | class GCN(nn.Layer):
    method __init__ (line 245) | def __init__(self, num_state: int = 128, num_node: int = 64, bias=False):
    method forward (line 265) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GraphTransfer (line 273) | class GraphTransfer(nn.Layer):
    method __init__ (line 276) | def __init__(self, in_dim: int):
    method forward (line 290) | def forward(self, word: paddle.Tensor, vis_node: paddle.Tensor) -> Lis...

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_ade20k/resnet.py
  class BasicBlock (line 20) | class BasicBlock(nn.Layer):
    method __init__ (line 21) | def __init__(self,
    method forward (line 55) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet101_vd (line 68) | class ResNet101_vd(nn.Layer):
    method __init__ (line 69) | def __init__(self,
    method forward (line 126) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 139) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 142) | def __init__(self,
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 165) | class ConvBN(nn.Layer):
    method __init__ (line 168) | def __init__(self,
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 185) | class ConvBNReLU(nn.Layer):
    method __init__ (line 188) | def __init__(self,
    method forward (line 200) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 207) | class Activation(nn.Layer):
    method __init__ (line 241) | def __init__(self, act: str = None):
    method forward (line 257) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 265) | class ASPPModule(nn.Layer):
    method __init__ (line 279) | def __init__(self,
    method forward (line 321) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_cityscapes/module.py
  class GINetResNet101 (line 39) | class GINetResNet101(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 91) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method base_forward (line 94) | def base_forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method forward (line 103) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GIHead (line 124) | class GIHead(nn.Layer):
    method __init__ (line 127) | def __init__(self, in_channels: int, nclass: int):
    method forward (line 157) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GlobalReasonUnit (line 172) | class GlobalReasonUnit(nn.Layer):
    method __init__ (line 178) | def __init__(self, in_channels: int, num_state: int = 256, num_node: i...
    method forward (line 191) | def forward(self, x: paddle.Tensor, inp: paddle.Tensor) -> paddle.Tensor:
  class GraphLayer (line 217) | class GraphLayer(nn.Layer):
    method __init__ (line 218) | def __init__(self, num_state: int, num_node: int, num_class: int):
    method forward (line 234) | def forward(self, inp: paddle.Tensor, vis_node: paddle.Tensor) -> List...
  class GCN (line 244) | class GCN(nn.Layer):
    method __init__ (line 245) | def __init__(self, num_state: int = 128, num_node: int = 64, bias=False):
    method forward (line 265) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GraphTransfer (line 273) | class GraphTransfer(nn.Layer):
    method __init__ (line 276) | def __init__(self, in_dim: int):
    method forward (line 290) | def forward(self, word: paddle.Tensor, vis_node: paddle.Tensor) -> Lis...

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_cityscapes/resnet.py
  class BasicBlock (line 20) | class BasicBlock(nn.Layer):
    method __init__ (line 21) | def __init__(self,
    method forward (line 55) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet101_vd (line 68) | class ResNet101_vd(nn.Layer):
    method __init__ (line 69) | def __init__(self,
    method forward (line 126) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_voc/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 139) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 142) | def __init__(self,
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 165) | class ConvBN(nn.Layer):
    method __init__ (line 168) | def __init__(self,
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 185) | class ConvBNReLU(nn.Layer):
    method __init__ (line 188) | def __init__(self,
    method forward (line 200) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 207) | class Activation(nn.Layer):
    method __init__ (line 241) | def __init__(self, act: str = None):
    method forward (line 257) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 265) | class ASPPModule(nn.Layer):
    method __init__ (line 279) | def __init__(self,
    method forward (line 321) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_voc/module.py
  class GINetResNet101 (line 39) | class GINetResNet101(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 91) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method base_forward (line 94) | def base_forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method forward (line 103) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GIHead (line 124) | class GIHead(nn.Layer):
    method __init__ (line 127) | def __init__(self, in_channels: int, nclass: int):
    method forward (line 157) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GlobalReasonUnit (line 172) | class GlobalReasonUnit(nn.Layer):
    method __init__ (line 178) | def __init__(self, in_channels: int, num_state: int = 256, num_node: i...
    method forward (line 191) | def forward(self, x: paddle.Tensor, inp: paddle.Tensor) -> List[paddle...
  class GraphLayer (line 217) | class GraphLayer(nn.Layer):
    method __init__ (line 218) | def __init__(self, num_state: int, num_node: int, num_class: int):
    method forward (line 234) | def forward(self, inp: paddle.Tensor, vis_node: paddle.Tensor) -> List...
  class GCN (line 244) | class GCN(nn.Layer):
    method __init__ (line 245) | def __init__(self, num_state: int = 128, num_node: int = 64, bias=False):
    method forward (line 265) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GraphTransfer (line 273) | class GraphTransfer(nn.Layer):
    method __init__ (line 276) | def __init__(self, in_dim: int):
    method forward (line 290) | def forward(self, word: paddle.Tensor, vis_node: paddle.Tensor) -> Lis...

FILE: modules/image/semantic_segmentation/ginet_resnet101vd_voc/resnet.py
  class BasicBlock (line 20) | class BasicBlock(nn.Layer):
    method __init__ (line 21) | def __init__(self,
    method forward (line 55) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet101_vd (line 68) | class ResNet101_vd(nn.Layer):
    method __init__ (line 69) | def __init__(self,
    method forward (line 126) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_ade20k/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 139) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 142) | def __init__(self,
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 165) | class ConvBN(nn.Layer):
    method __init__ (line 168) | def __init__(self,
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 185) | class ConvBNReLU(nn.Layer):
    method __init__ (line 188) | def __init__(self,
    method forward (line 200) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 207) | class Activation(nn.Layer):
    method __init__ (line 241) | def __init__(self, act: str = None):
    method forward (line 257) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 265) | class ASPPModule(nn.Layer):
    method __init__ (line 279) | def __init__(self,
    method forward (line 321) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_ade20k/module.py
  class GINetResNet50 (line 39) | class GINetResNet50(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 91) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method base_forward (line 94) | def base_forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method forward (line 103) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GIHead (line 124) | class GIHead(nn.Layer):
    method __init__ (line 127) | def __init__(self, in_channels: int, nclass: int):
    method forward (line 157) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GlobalReasonUnit (line 172) | class GlobalReasonUnit(nn.Layer):
    method __init__ (line 178) | def __init__(self, in_channels: int, num_state: int = 256, num_node: i...
    method forward (line 191) | def forward(self, x: paddle.Tensor, inp:paddle.Tensor) -> List[paddle....
  class GraphLayer (line 217) | class GraphLayer(nn.Layer):
    method __init__ (line 218) | def __init__(self, num_state: int, num_node: int, num_class: int):
    method forward (line 234) | def forward(self, inp: paddle.Tensor, vis_node: paddle.Tensor) -> List...
  class GCN (line 244) | class GCN(nn.Layer):
    method __init__ (line 245) | def __init__(self, num_state: int = 128, num_node: int = 64, bias: boo...
    method forward (line 265) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GraphTransfer (line 273) | class GraphTransfer(nn.Layer):
    method __init__ (line 276) | def __init__(self, in_dim: int):
    method forward (line 290) | def forward(self, word: paddle.Tensor, vis_node: paddle.Tensor) -> Lis...

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_ade20k/resnet.py
  class BasicBlock (line 21) | class BasicBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self,
    method forward (line 56) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet50_vd (line 69) | class ResNet50_vd(nn.Layer):
    method __init__ (line 70) | def __init__(self,
    method forward (line 127) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(
    method forward (line 62) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 72) | class BottleneckBlock(nn.Layer):
    method __init__ (line 75) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 139) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 142) | def __init__(self,
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 165) | class ConvBN(nn.Layer):
    method __init__ (line 168) | def __init__(self,
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 185) | class ConvBNReLU(nn.Layer):
    method __init__ (line 188) | def __init__(self,
    method forward (line 200) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 207) | class Activation(nn.Layer):
    method __init__ (line 241) | def __init__(self, act: str = None):
    method forward (line 257) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 265) | class ASPPModule(nn.Layer):
    method __init__ (line 279) | def __init__(self,
    method forward (line 321) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_cityscapes/module.py
  class GINetResNet50 (line 39) | class GINetResNet50(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 91) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method base_forward (line 94) | def base_forward(self, x: paddle.Tensor) -> paddle.Tensor:
    method forward (line 103) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GIHead (line 124) | class GIHead(nn.Layer):
    method __init__ (line 127) | def __init__(self, in_channels: int, nclass: int):
    method forward (line 157) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GlobalReasonUnit (line 172) | class GlobalReasonUnit(nn.Layer):
    method __init__ (line 178) | def __init__(self, in_channels: int, num_state: int = 256, num_node: i...
    method forward (line 191) | def forward(self, x: paddle.Tensor, inp: paddle.Tensor) -> paddle.Tensor:
  class GraphLayer (line 217) | class GraphLayer(nn.Layer):
    method __init__ (line 218) | def __init__(self, num_state: int, num_node: int, num_class: int):
    method forward (line 234) | def forward(self, inp: paddle.Tensor, vis_node: paddle.Tensor) -> List...
  class GCN (line 244) | class GCN(nn.Layer):
    method __init__ (line 245) | def __init__(self, num_state: int = 128, num_node: int = 64, bias: boo...
    method forward (line 265) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GraphTransfer (line 273) | class GraphTransfer(nn.Layer):
    method __init__ (line 276) | def __init__(self, in_dim: int):
    method forward (line 290) | def forward(self, word: paddle.Tensor, vis_node: paddle.Tensor) -> Lis...

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_cityscapes/resnet.py
  class BasicBlock (line 21) | class BasicBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self,
    method forward (line 56) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet50_vd (line 69) | class ResNet50_vd(nn.Layer):
    method __init__ (line 70) | def __init__(self,
    method forward (line 127) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_voc/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 30) | class ConvBNLayer(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 59) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self,
    method forward (line 113) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 132) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 135) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 145) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 151) | class ConvBN(nn.Layer):
    method __init__ (line 154) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 159) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 165) | class ConvBNReLU(nn.Layer):
    method __init__ (line 168) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 174) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 181) | class Activation(nn.Layer):
    method __init__ (line 215) | def __init__(self, act: str = None):
    method forward (line 230) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 238) | class ASPPModule(nn.Layer):
    method __init__ (line 252) | def __init__(self,
    method forward (line 289) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_voc/module.py
  class GINetResNet50 (line 38) | class GINetResNet50(nn.Layer):
    method __init__ (line 55) | def __init__(self,
    method transform (line 89) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method base_forward (line 92) | def base_forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
    method forward (line 101) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GIHead (line 117) | class GIHead(nn.Layer):
    method __init__ (line 120) | def __init__(self, in_channels: int, nclass: int):
    method forward (line 136) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class GlobalReasonUnit (line 151) | class GlobalReasonUnit(nn.Layer):
    method __init__ (line 157) | def __init__(self, in_channels: int, num_state: int = 256, num_node: i...
    method forward (line 167) | def forward(self, x: paddle.Tensor, inp: paddle.Tensor) -> List[paddle...
  class GraphLayer (line 192) | class GraphLayer(nn.Layer):
    method __init__ (line 194) | def __init__(self, num_state: int, num_node: int, num_class: int):
    method forward (line 208) | def forward(self, inp: paddle.Tensor, vis_node: paddle.Tensor) -> List...
  class GCN (line 218) | class GCN(nn.Layer):
    method __init__ (line 220) | def __init__(self, num_state: int = 128, num_node: int = 64, bias: boo...
    method forward (line 233) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class GraphTransfer (line 241) | class GraphTransfer(nn.Layer):
    method __init__ (line 244) | def __init__(self, in_dim: int):
    method forward (line 254) | def forward(self, word: paddle.Tensor, vis_node: paddle.Tensor) -> Lis...

FILE: modules/image/semantic_segmentation/ginet_resnet50vd_voc/resnet.py
  class BasicBlock (line 19) | class BasicBlock(nn.Layer):
    method __init__ (line 21) | def __init__(self,
    method forward (line 52) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet50_vd (line 65) | class ResNet50_vd(nn.Layer):
    method __init__ (line 67) | def __init__(self, multi_grid: tuple = (1, 2, 4)):
    method forward (line 116) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/hardnet_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNReLU (line 30) | class ConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 40) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 47) | class ConvBN(nn.Layer):
    method __init__ (line 50) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 55) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvReLUPool (line 61) | class ConvReLUPool(nn.Layer):
    method __init__ (line 64) | def __init__(self, in_channels: int, out_channels: int):
    method forward (line 68) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 75) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 78) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 89) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class DepthwiseConvBN (line 95) | class DepthwiseConvBN(nn.Layer):
    method __init__ (line 98) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 108) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 113) | class AuxLayer(nn.Layer):
    method __init__ (line 124) | def __init__(self, in_channels: int, inter_channels: int, out_channels...
    method forward (line 133) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 140) | class Activation(nn.Layer):
    method __init__ (line 166) | def __init__(self, act: str = None):
    method forward (line 181) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/hardnet_cityscapes/module.py
  class HarDNet (line 37) | class HarDNet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 102) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 105) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class Encoder (line 115) | class Encoder(nn.Layer):
    method __init__ (line 127) | def __init__(self, n_blocks: int, in_channels: int, ch_list: List[int]...
    method forward (line 148) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
    method get_skip_channels (line 156) | def get_skip_channels(self):
    method get_out_channels (line 159) | def get_out_channels(self):
  class Decoder (line 163) | class Decoder(nn.Layer):
    method __init__ (line 175) | def __init__(self,
    method forward (line 202) | def forward(self, x: paddle.Tensor, skip_connections: List[paddle.Tens...
    method get_out_channels (line 211) | def get_out_channels(self):
  class HarDBlock (line 215) | class HarDBlock(nn.Layer):
    method __init__ (line 226) | def __init__(self,
    method forward (line 246) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
    method get_out_ch (line 270) | def get_out_ch(self):
  function get_link (line 274) | def get_link(layer: int, base_ch: int, growth_rate: List[int], grmul: fl...

FILE: modules/image/semantic_segmentation/humanseg_lite/data_feed.py
  function preprocess_v (line 12) | def preprocess_v(img, w, h):
  function reader (line 22) | def reader(images=None, paths=None):

FILE: modules/image/semantic_segmentation/humanseg_lite/module.py
  class ShufflenetHumanSeg (line 46) | class ShufflenetHumanSeg:
    method __init__ (line 48) | def __init__(self):
    method _set_config (line 52) | def _set_config(self):
    method segment (line 80) | def segment(self,
    method video_stream_segment (line 153) | def video_stream_segment(self, frame_org, frame_id, prev_gray, prev_cf...
    method video_segment (line 205) | def video_segment(self, video_path=None, use_gpu=False, save_dir='huma...
    method serving_method (line 322) | def serving_method(self, images, **kwargs):
    method run_cmd (line 332) | def run_cmd(self, argvs):
    method add_module_config_arg (line 358) | def add_module_config_arg(self):
    method add_module_input_arg (line 380) | def add_module_input_arg(self):
    method create_gradio_app (line 386) | def create_gradio_app(self):

FILE: modules/image/semantic_segmentation/humanseg_lite/optimal.py
  function human_seg_tracking (line 5) | def human_seg_tracking(pre_gray, cur_gray, prev_cfd, dl_weights, disflow):
  function human_seg_track_fuse (line 46) | def human_seg_track_fuse(track_cfd, dl_cfd, dl_weights, is_track):
  function threshold_mask (line 68) | def threshold_mask(img, thresh_bg, thresh_fg):
  function postprocess_v (line 75) | def postprocess_v(cur_gray, scoremap, prev_gray, pre_cfd, disflow, is_in...

FILE: modules/image/semantic_segmentation/humanseg_lite/processor.py
  function cv2_to_base64 (line 12) | def cv2_to_base64(image):
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function postprocess (line 24) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 56) | def check_dir(dir_path):
  function get_save_image_name (line 64) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/semantic_segmentation/humanseg_lite/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 34) | def tearDownClass(cls) -> None:
    method test_segment1 (line 40) | def test_segment1(self):
    method test_segment2 (line 44) | def test_segment2(self):
    method test_segment3 (line 48) | def test_segment3(self):
    method test_segment4 (line 52) | def test_segment4(self):
    method test_segment5 (line 56) | def test_segment5(self):
    method test_segment6 (line 59) | def test_segment6(self):
    method test_video_stream_segment1 (line 62) | def test_video_stream_segment1(self):
    method test_video_stream_segment2 (line 80) | def test_video_stream_segment2(self):
    method test_video_segment1 (line 98) | def test_video_segment1(self):
    method test_save_inference_model (line 101) | def test_save_inference_model(self):

FILE: modules/image/semantic_segmentation/humanseg_mobile/data_feed.py
  function preprocess_v (line 12) | def preprocess_v(img, w, h):
  function reader (line 22) | def reader(images=None, paths=None):

FILE: modules/image/semantic_segmentation/humanseg_mobile/module.py
  class HRNetw18samllv1humanseg (line 46) | class HRNetw18samllv1humanseg:
    method __init__ (line 48) | def __init__(self):
    method _set_config (line 52) | def _set_config(self):
    method segment (line 78) | def segment(self,
    method video_stream_segment (line 149) | def video_stream_segment(self, frame_org, frame_id, prev_gray, prev_cf...
    method video_segment (line 199) | def video_segment(self, video_path=None, use_gpu=False, save_dir='huma...
    method serving_method (line 311) | def serving_method(self, images, **kwargs):
    method run_cmd (line 321) | def run_cmd(self, argvs):
    method add_module_config_arg (line 346) | def add_module_config_arg(self):
    method add_module_input_arg (line 368) | def add_module_input_arg(self):
    method create_gradio_app (line 374) | def create_gradio_app(self):

FILE: modules/image/semantic_segmentation/humanseg_mobile/optimal.py
  function human_seg_tracking (line 5) | def human_seg_tracking(pre_gray, cur_gray, prev_cfd, dl_weights, disflow):
  function human_seg_track_fuse (line 46) | def human_seg_track_fuse(track_cfd, dl_cfd, dl_weights, is_track):
  function threshold_mask (line 68) | def threshold_mask(img, thresh_bg, thresh_fg):
  function postprocess_v (line 75) | def postprocess_v(cur_gray, scoremap, prev_gray, pre_cfd, disflow, is_in...

FILE: modules/image/semantic_segmentation/humanseg_mobile/processor.py
  function cv2_to_base64 (line 12) | def cv2_to_base64(image):
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function postprocess (line 24) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 57) | def check_dir(dir_path):
  function get_save_image_name (line 65) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/semantic_segmentation/humanseg_mobile/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 34) | def tearDownClass(cls) -> None:
    method test_segment1 (line 40) | def test_segment1(self):
    method test_segment2 (line 44) | def test_segment2(self):
    method test_segment3 (line 48) | def test_segment3(self):
    method test_segment4 (line 52) | def test_segment4(self):
    method test_segment5 (line 56) | def test_segment5(self):
    method test_segment6 (line 59) | def test_segment6(self):
    method test_video_stream_segment1 (line 62) | def test_video_stream_segment1(self):
    method test_video_stream_segment2 (line 80) | def test_video_stream_segment2(self):
    method test_video_segment1 (line 98) | def test_video_segment1(self):
    method test_save_inference_model (line 101) | def test_save_inference_model(self):

FILE: modules/image/semantic_segmentation/humanseg_server/data_feed.py
  function preprocess_v (line 12) | def preprocess_v(img, w, h):
  function reader (line 22) | def reader(images=None, paths=None):

FILE: modules/image/semantic_segmentation/humanseg_server/module.py
  class DeeplabV3pXception65HumanSeg (line 46) | class DeeplabV3pXception65HumanSeg:
    method __init__ (line 48) | def __init__(self):
    method _set_config (line 52) | def _set_config(self):
    method segment (line 78) | def segment(self,
    method video_stream_segment (line 150) | def video_stream_segment(self, frame_org, frame_id, prev_gray, prev_cf...
    method video_segment (line 200) | def video_segment(self, video_path=None, use_gpu=False, save_dir='huma...
    method serving_method (line 294) | def serving_method(self, images, **kwargs):
    method run_cmd (line 304) | def run_cmd(self, argvs):
    method add_module_config_arg (line 328) | def add_module_config_arg(self):
    method add_module_input_arg (line 350) | def add_module_input_arg(self):
    method create_gradio_app (line 356) | def create_gradio_app(self):

FILE: modules/image/semantic_segmentation/humanseg_server/optimal.py
  function human_seg_tracking (line 5) | def human_seg_tracking(pre_gray, cur_gray, prev_cfd, dl_weights, disflow):
  function human_seg_track_fuse (line 46) | def human_seg_track_fuse(track_cfd, dl_cfd, dl_weights, is_track):
  function threshold_mask (line 68) | def threshold_mask(img, thresh_bg, thresh_fg):
  function postprocess_v (line 75) | def postprocess_v(cur_gray, scoremap, prev_gray, pre_cfd, disflow, is_in...

FILE: modules/image/semantic_segmentation/humanseg_server/processor.py
  function cv2_to_base64 (line 12) | def cv2_to_base64(image):
  function base64_to_cv2 (line 17) | def base64_to_cv2(b64str):
  function postprocess (line 24) | def postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir,...
  function check_dir (line 55) | def check_dir(dir_path):
  function get_save_image_name (line 63) | def get_save_image_name(org_im, org_im_path, output_dir):

FILE: modules/image/semantic_segmentation/humanseg_server/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 34) | def tearDownClass(cls) -> None:
    method test_segment1 (line 40) | def test_segment1(self):
    method test_segment2 (line 44) | def test_segment2(self):
    method test_segment3 (line 48) | def test_segment3(self):
    method test_segment4 (line 52) | def test_segment4(self):
    method test_segment5 (line 56) | def test_segment5(self):
    method test_segment6 (line 59) | def test_segment6(self):
    method test_video_stream_segment1 (line 62) | def test_video_stream_segment1(self):
    method test_video_stream_segment2 (line 80) | def test_video_stream_segment2(self):
    method test_video_segment1 (line 98) | def test_video_segment1(self):
    method test_save_inference_model (line 101) | def test_save_inference_model(self):

FILE: modules/image/semantic_segmentation/isanet_resnet50_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 30) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 50) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 56) | class ConvBN(nn.Layer):
    method __init__ (line 59) | def __init__(self,
    method forward (line 70) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 76) | class ConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 91) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 98) | class Activation(nn.Layer):
    method __init__ (line 124) | def __init__(self, act: str = None):
    method forward (line 140) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 148) | class ASPPModule(nn.Layer):
    method __init__ (line 161) | def __init__(self,
    method forward (line 203) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 230) | class AuxLayer(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 263) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 270) | class Add(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 274) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name: str = None):
  class AttentionBlock (line 277) | class AttentionBlock(nn.Layer):
    method __init__ (line 299) | def __init__(self, key_in_channels, query_in_channels, channels,
    method build_project (line 345) | def build_project(self, in_channels: int , channels: int, num_convs: i...
    method forward (line 372) | def forward(self, query_feats: paddle.Tensor, key_feats: paddle.Tensor...

FILE: modules/image/semantic_segmentation/isanet_resnet50_cityscapes/module.py
  class ISANet (line 38) | class ISANet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 85) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 88) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class ISAHead (line 104) | class ISAHead(nn.Layer):
    method __init__ (line 116) | def __init__(self,
    method forward (line 144) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class SelfAttentionBlock (line 192) | class SelfAttentionBlock(layers.AttentionBlock):
    method __init__ (line 200) | def __init__(self, in_channels: int, channels: int):
    method forward (line 219) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/isanet_resnet50_cityscapes/resnet.py
  class ConvBNLayer (line 21) | class ConvBNLayer(nn.Layer):
    method __init__ (line 22) | def __init__(self,
    method forward (line 60) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 70) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 135) | class BasicBlock(nn.Layer):
    method __init__ (line 136) | def __init__(self,
    method forward (line 176) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 190) | class ResNet_vd(nn.Layer):
    method __init__ (line 206) | def __init__(self,
    method forward (line 340) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 357) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/isanet_resnet50_voc/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 30) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 50) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 56) | class ConvBN(nn.Layer):
    method __init__ (line 59) | def __init__(self,
    method forward (line 70) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 76) | class ConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 91) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 98) | class Activation(nn.Layer):
    method __init__ (line 124) | def __init__(self, act: str = None):
    method forward (line 140) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 148) | class ASPPModule(nn.Layer):
    method __init__ (line 161) | def __init__(self,
    method forward (line 203) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 230) | class AuxLayer(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 263) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 270) | class Add(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 274) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name: str = None):
  class AttentionBlock (line 277) | class AttentionBlock(nn.Layer):
    method __init__ (line 299) | def __init__(self, key_in_channels, query_in_channels, channels,
    method build_project (line 345) | def build_project(self, in_channels: int, channels: int, num_convs: in...
    method forward (line 372) | def forward(self, query_feats: paddle.Tensor, key_feats: paddle.Tensor...

FILE: modules/image/semantic_segmentation/isanet_resnet50_voc/module.py
  class ISANet (line 38) | class ISANet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 85) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 88) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class ISAHead (line 104) | class ISAHead(nn.Layer):
    method __init__ (line 116) | def __init__(self,
    method forward (line 144) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:
  class SelfAttentionBlock (line 192) | class SelfAttentionBlock(layers.AttentionBlock):
    method __init__ (line 200) | def __init__(self, in_channels, channels):
    method forward (line 219) | def forward(self, x):

FILE: modules/image/semantic_segmentation/isanet_resnet50_voc/resnet.py
  class ConvBNLayer (line 21) | class ConvBNLayer(nn.Layer):
    method __init__ (line 22) | def __init__(self,
    method forward (line 60) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 70) | class BottleneckBlock(nn.Layer):
    method __init__ (line 71) | def __init__(self,
    method forward (line 120) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 135) | class BasicBlock(nn.Layer):
    method __init__ (line 136) | def __init__(self,
    method forward (line 176) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 190) | class ResNet_vd(nn.Layer):
    method __init__ (line 206) | def __init__(self,
    method forward (line 340) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 357) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/lseg/models/clip.py
  class CLIPText (line 6) | class CLIPText(nn.Layer):
    method __init__ (line 8) | def __init__(self,
    method get_text_features (line 28) | def get_text_features(

FILE: modules/image/semantic_segmentation/lseg/models/lseg.py
  class LSeg (line 8) | class LSeg(nn.Layer):
    method __init__ (line 10) | def __init__(self):
    method forward (line 16) | def forward(self, images, texts):

FILE: modules/image/semantic_segmentation/lseg/models/scratch.py
  class Interpolate (line 6) | class Interpolate(nn.Layer):
    method __init__ (line 9) | def __init__(self, scale_factor, mode, align_corners=False):
    method forward (line 23) | def forward(self, x):
  class ResidualConvUnit (line 43) | class ResidualConvUnit(nn.Layer):
    method __init__ (line 46) | def __init__(self, features):
    method forward (line 60) | def forward(self, x):
  class FeatureFusionBlock (line 77) | class FeatureFusionBlock(nn.Layer):
    method __init__ (line 80) | def __init__(self, features):
    method forward (line 91) | def forward(self, *xs):
  class ResidualConvUnit_custom (line 109) | class ResidualConvUnit_custom(nn.Layer):
    method __init__ (line 112) | def __init__(self, features, activation, bn):
    method forward (line 150) | def forward(self, x):
  class FeatureFusionBlock_custom (line 176) | class FeatureFusionBlock_custom(nn.Layer):
    method __init__ (line 179) | def __init__(
    method forward (line 218) | def forward(self, *xs):
  class Scratch (line 239) | class Scratch(nn.Layer):
    method __init__ (line 241) | def __init__(self, in_channels=[256, 512, 1024, 1024], out_channels=256):
    method forward (line 291) | def forward(self, layer_1, layer_2, layer_3, layer_4, text_features):

FILE: modules/image/semantic_segmentation/lseg/models/vit.py
  class Slice (line 9) | class Slice(nn.Layer):
    method __init__ (line 11) | def __init__(self, start_index=1):
    method forward (line 15) | def forward(self, x):
  class AddReadout (line 19) | class AddReadout(nn.Layer):
    method __init__ (line 21) | def __init__(self, start_index=1):
    method forward (line 25) | def forward(self, x):
  class Transpose (line 33) | class Transpose(nn.Layer):
    method __init__ (line 35) | def __init__(self, dim0, dim1):
    method forward (line 40) | def forward(self, x):
  class Unflatten (line 47) | class Unflatten(nn.Layer):
    method __init__ (line 49) | def __init__(self, start_axis, shape):
    method forward (line 54) | def forward(self, x):
  class ProjectReadout (line 58) | class ProjectReadout(nn.Layer):
    method __init__ (line 60) | def __init__(self, in_features, start_index=1):
    method forward (line 66) | def forward(self, x):
  class ViT (line 73) | class ViT(VisionTransformer):
    method __init__ (line 75) | def __init__(self,
    method _resize_pos_embed (line 178) | def _resize_pos_embed(self, posemb, gs_h, gs_w):
    method forward (line 194) | def forward(self, x):

FILE: modules/image/semantic_segmentation/lseg/module.py
  function cv2_to_base64 (line 22) | def cv2_to_base64(image):
  function base64_to_cv2 (line 27) | def base64_to_cv2(b64str):
  class LSeg (line 42) | class LSeg(models.LSeg):
    method __init__ (line 44) | def __init__(self):
    method get_colormap (line 60) | def get_colormap(n):
    method segment (line 80) | def segment(self,
    method run_cmd (line 162) | def run_cmd(self, argvs):
    method serving_method (line 181) | def serving_method(self, image, **kwargs):

FILE: modules/image/semantic_segmentation/lseg/test.py
  class TestHubModule (line 14) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 17) | def setUpClass(cls) -> None:
    method tearDownClass (line 28) | def tearDownClass(cls) -> None:
    method test_segment1 (line 32) | def test_segment1(self):
    method test_segment2 (line 41) | def test_segment2(self):
    method test_segment3 (line 50) | def test_segment3(self):
    method test_segment4 (line 59) | def test_segment4(self):
    method test_segment5 (line 62) | def test_segment5(self):

FILE: modules/image/semantic_segmentation/ocrnet_hrnetw18_cityscapes/hrnet.py
  class HRNet_W18 (line 25) | class HRNet_W18(nn.Layer):
    method __init__ (line 51) | def __init__(self,
    method forward (line 131) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Layer1 (line 155) | class Layer1(nn.Layer):
    method __init__ (line 156) | def __init__(self, num_channels: int, num_filters: int, num_blocks: in...
    method forward (line 173) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class TransitionLayer (line 180) | class TransitionLayer(nn.Layer):
    method __init__ (line 181) | def __init__(self, in_channels: int, out_channels: int, name=None):
    method forward (line 211) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Branches (line 224) | class Branches(nn.Layer):
    method __init__ (line 225) | def __init__(self, num_blocks: int, in_channels: int, out_channels: in...
    method forward (line 243) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 253) | class BottleneckBlock(nn.Layer):
    method __init__ (line 254) | def __init__(self,
    method forward (line 288) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 305) | class BasicBlock(nn.Layer):
    method __init__ (line 306) | def __init__(self,
    method forward (line 335) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 351) | class SELayer(nn.Layer):
    method __init__ (line 352) | def __init__(self, num_channels: int, num_filters: int, reduction_rati...
    method forward (line 368) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Stage (line 380) | class Stage(nn.Layer):
    method __init__ (line 381) | def __init__(self,
    method forward (line 420) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class HighResolutionModule (line 427) | class HighResolutionModule(nn.Layer):
    method __init__ (line 428) | def __init__(self,
    method forward (line 448) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FuseLayers (line 454) | class FuseLayers(nn.Layer):
    method __init__ (line 455) | def __init__(self,
    method forward (line 507) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ocrnet_hrnetw18_cityscapes/layers.py
  function SyncBatchNorm (line 23) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 31) | class ConvBNLayer(nn.Layer):
    method __init__ (line 34) | def __init__(self,
    method forward (line 61) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 71) | class BottleneckBlock(nn.Layer):
    method __init__ (line 74) | def __init__(self,
    method forward (line 111) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 130) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 133) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 144) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 150) | class ConvBN(nn.Layer):
    method __init__ (line 153) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 158) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 164) | class ConvBNReLU(nn.Layer):
    method __init__ (line 167) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 173) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 180) | class Activation(nn.Layer):
    method __init__ (line 206) | def __init__(self, act: str = None):
    method forward (line 221) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 228) | class ASPPModule(nn.Layer):
    method __init__ (line 242) | def __init__(self,
    method forward (line 281) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ocrnet_hrnetw18_cityscapes/module.py
  class OCRNetHRNetW18 (line 37) | class OCRNetHRNetW18(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 86) | def transform(self, img: np.ndarray) -> np.ndarray:
    method forward (line 89) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class OCRHead (line 99) | class OCRHead(nn.Layer):
    method __init__ (line 109) | def __init__(self, num_classes: int, in_channels: int, ocr_mid_channel...
    method forward (line 124) | def forward(self, feat_list: List[paddle.Tensor]) -> paddle.Tensor:
  class SpatialGatherBlock (line 137) | class SpatialGatherBlock(nn.Layer):
    method forward (line 140) | def forward(self, pixels: paddle.Tensor, regions: paddle.Tensor) -> pa...
  class SpatialOCRModule (line 160) | class SpatialOCRModule(nn.Layer):
    method __init__ (line 163) | def __init__(self, in_channels: int, key_channels: int, out_channels: ...
    method forward (line 169) | def forward(self, pixels: paddle.Tensor, regions: paddle.Tensor) -> pa...
  class ObjectAttentionBlock (line 177) | class ObjectAttentionBlock(nn.Layer):
    method __init__ (line 180) | def __init__(self, in_channels: int, key_channels: int):
    method forward (line 196) | def forward(self, x: paddle.Tensor, proxy: paddle.Tensor) -> paddle.Te...

FILE: modules/image/semantic_segmentation/ocrnet_hrnetw18_voc/hrnet.py
  class HRNet_W18 (line 24) | class HRNet_W18(nn.Layer):
    method __init__ (line 51) | def __init__(self,
    method forward (line 132) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Layer1 (line 156) | class Layer1(nn.Layer):
    method __init__ (line 157) | def __init__(self, num_channels: int, num_filters: int, num_blocks: in...
    method forward (line 174) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class TransitionLayer (line 181) | class TransitionLayer(nn.Layer):
    method __init__ (line 182) | def __init__(self, in_channels: int, out_channels: int, name=None):
    method forward (line 212) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Branches (line 225) | class Branches(nn.Layer):
    method __init__ (line 226) | def __init__(self, num_blocks: int, in_channels: int, out_channels: in...
    method forward (line 244) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 254) | class BottleneckBlock(nn.Layer):
    method __init__ (line 255) | def __init__(self,
    method forward (line 289) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 306) | class BasicBlock(nn.Layer):
    method __init__ (line 307) | def __init__(self,
    method forward (line 336) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SELayer (line 352) | class SELayer(nn.Layer):
    method __init__ (line 353) | def __init__(self, num_channels: int, num_filters: int, reduction_rati...
    method forward (line 369) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Stage (line 381) | class Stage(nn.Layer):
    method __init__ (line 382) | def __init__(self,
    method forward (line 421) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class HighResolutionModule (line 428) | class HighResolutionModule(nn.Layer):
    method __init__ (line 429) | def __init__(self,
    method forward (line 449) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FuseLayers (line 455) | class FuseLayers(nn.Layer):
    method __init__ (line 456) | def __init__(self,
    method forward (line 508) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ocrnet_hrnetw18_voc/layers.py
  function SyncBatchNorm (line 21) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNLayer (line 29) | class ConvBNLayer(nn.Layer):
    method __init__ (line 32) | def __init__(self,
    method forward (line 59) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 69) | class BottleneckBlock(nn.Layer):
    method __init__ (line 72) | def __init__(self,
    method forward (line 109) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 128) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 131) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 142) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 148) | class ConvBN(nn.Layer):
    method __init__ (line 151) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 156) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 162) | class ConvBNReLU(nn.Layer):
    method __init__ (line 165) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 171) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 178) | class Activation(nn.Layer):
    method __init__ (line 212) | def __init__(self, act: str = None):
    method forward (line 227) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 235) | class ASPPModule(nn.Layer):
    method __init__ (line 249) | def __init__(self, aspp_ratios, in_channels, out_channels, align_corne...
    method forward (line 282) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/ocrnet_hrnetw18_voc/module.py
  class OCRNetHRNetW18 (line 37) | class OCRNetHRNetW18(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 86) | def transform(self, img: np.ndarray) -> np.ndarray:
    method forward (line 89) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class OCRHead (line 99) | class OCRHead(nn.Layer):
    method __init__ (line 109) | def __init__(self, num_classes: int, in_channels: int, ocr_mid_channel...
    method forward (line 124) | def forward(self, feat_list: List[paddle.Tensor]) -> paddle.Tensor:
  class SpatialGatherBlock (line 137) | class SpatialGatherBlock(nn.Layer):
    method forward (line 140) | def forward(self, pixels: paddle.Tensor, regions: paddle.Tensor) -> pa...
  class SpatialOCRModule (line 160) | class SpatialOCRModule(nn.Layer):
    method __init__ (line 163) | def __init__(self, in_channels: int, key_channels: int, out_channels: ...
    method forward (line 169) | def forward(self, pixels: paddle.Tensor, regions: paddle.Tensor) -> pa...
  class ObjectAttentionBlock (line 177) | class ObjectAttentionBlock(nn.Layer):
    method __init__ (line 180) | def __init__(self, in_channels: int, key_channels: int):
    method forward (line 196) | def forward(self, x: paddle.Tensor, proxy: paddle.Tensor) -> paddle.Te...

FILE: modules/image/semantic_segmentation/pspnet_resnet50_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 30) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 50) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 56) | class ConvBN(nn.Layer):
    method __init__ (line 59) | def __init__(self,
    method forward (line 70) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 76) | class ConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 91) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 98) | class Activation(nn.Layer):
    method __init__ (line 124) | def __init__(self, act: str = None):
    method forward (line 140) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 148) | class ASPPModule(nn.Layer):
    method __init__ (line 161) | def __init__(self,
    method forward (line 203) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 230) | class AuxLayer(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 263) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 270) | class Add(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 274) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name: str = None...
  class PPModule (line 277) | class PPModule(nn.Layer):
    method __init__ (line 290) | def __init__(self,
    method _make_stage (line 318) | def _make_stage(self, in_channels: int, out_channels: int, size: int):
    method forward (line 342) | def forward(self, input: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/pspnet_resnet50_cityscapes/module.py
  class PSPNet (line 37) | class PSPNet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 87) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 90) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class PSPNetHead (line 102) | class PSPNetHead(nn.Layer):
    method __init__ (line 122) | def __init__(self, num_classes, backbone_indices, backbone_channels,
    method forward (line 152) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:

FILE: modules/image/semantic_segmentation/pspnet_resnet50_cityscapes/resnet.py
  class ConvBNLayer (line 19) | class ConvBNLayer(nn.Layer):
    method __init__ (line 20) | def __init__(self,
    method forward (line 58) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 69) | def __init__(self,
    method forward (line 118) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 133) | class BasicBlock(nn.Layer):
    method __init__ (line 134) | def __init__(self,
    method forward (line 174) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 188) | class ResNet_vd(nn.Layer):
    method __init__ (line 204) | def __init__(self,
    method forward (line 338) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 355) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/pspnet_resnet50_voc/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 30) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 50) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 56) | class ConvBN(nn.Layer):
    method __init__ (line 59) | def __init__(self,
    method forward (line 70) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 76) | class ConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 91) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 98) | class Activation(nn.Layer):
    method __init__ (line 124) | def __init__(self, act: str = None):
    method forward (line 140) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 148) | class ASPPModule(nn.Layer):
    method __init__ (line 161) | def __init__(self,
    method forward (line 203) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 230) | class AuxLayer(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 263) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 270) | class Add(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 274) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name: str = None):
  class PPModule (line 277) | class PPModule(nn.Layer):
    method __init__ (line 290) | def __init__(self, in_channels: int, out_channels: int, bin_sizes: tup...
    method _make_stage (line 314) | def _make_stage(self, in_channels: int, out_channels: int, size: int):
    method forward (line 339) | def forward(self, input: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/pspnet_resnet50_voc/module.py
  class PSPNet (line 37) | class PSPNet(nn.Layer):
    method __init__ (line 56) | def __init__(self,
    method transform (line 87) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 90) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class PSPNetHead (line 102) | class PSPNetHead(nn.Layer):
    method __init__ (line 122) | def __init__(self, num_classes, backbone_indices, backbone_channels,
    method forward (line 152) | def forward(self, feat_list: List[paddle.Tensor]) -> List[paddle.Tensor]:

FILE: modules/image/semantic_segmentation/pspnet_resnet50_voc/resnet.py
  class ConvBNLayer (line 19) | class ConvBNLayer(nn.Layer):
    method __init__ (line 20) | def __init__(self,
    method forward (line 58) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BottleneckBlock (line 68) | class BottleneckBlock(nn.Layer):
    method __init__ (line 69) | def __init__(self,
    method forward (line 118) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class BasicBlock (line 133) | class BasicBlock(nn.Layer):
    method __init__ (line 134) | def __init__(self,
    method forward (line 174) | def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
  class ResNet_vd (line 188) | class ResNet_vd(nn.Layer):
    method __init__ (line 204) | def __init__(self,
    method forward (line 338) | def forward(self, inputs: paddle.Tensor) -> List[paddle.Tensor]:
  function ResNet50_vd (line 355) | def ResNet50_vd(**args):

FILE: modules/image/semantic_segmentation/stdc1_seg_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 30) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 50) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 56) | class ConvBN(nn.Layer):
    method __init__ (line 59) | def __init__(self,
    method forward (line 70) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 76) | class ConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 91) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 98) | class Activation(nn.Layer):
    method __init__ (line 124) | def __init__(self, act: str = None):
    method forward (line 140) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 148) | class ASPPModule(nn.Layer):
    method __init__ (line 161) | def __init__(self,
    method forward (line 203) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 230) | class AuxLayer(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 263) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 270) | class Add(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 274) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name=None) -> pa...
  class PPModule (line 277) | class PPModule(nn.Layer):
    method __init__ (line 290) | def __init__(self,
    method _make_stage (line 318) | def _make_stage(self, in_channels: int, out_channels: int, size: int):
    method forward (line 343) | def forward(self, input: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/stdc1_seg_cityscapes/module.py
  class STDCSeg (line 38) | class STDCSeg(nn.Layer):
    method __init__ (line 54) | def __init__(self,
    method transform (line 90) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 93) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class SegHead (line 129) | class SegHead(nn.Layer):
    method __init__ (line 130) | def __init__(self, in_chan: int, mid_chan: int, n_classes:int):
    method forward (line 137) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AttentionRefinementModule (line 143) | class AttentionRefinementModule(nn.Layer):
    method __init__ (line 144) | def __init__(self, in_chan: int, out_chan: int):
    method forward (line 153) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ContextPath (line 163) | class ContextPath(nn.Layer):
    method __init__ (line 164) | def __init__(self, backbone, use_conv_last: bool = False):
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FeatureFusionModule (line 203) | class FeatureFusionModule(nn.Layer):
    method __init__ (line 204) | def __init__(self, in_chan:int , out_chan: int):
    method forward (line 225) | def forward(self, fsp: paddle.Tensor, fcp: paddle.Tensor) -> paddle.Te...

FILE: modules/image/semantic_segmentation/stdc1_seg_cityscapes/stdcnet.py
  class STDCNet (line 26) | class STDCNet(nn.Layer):
    method __init__ (line 45) | def __init__(self,
    method forward (line 78) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
    method _make_layers (line 91) | def _make_layers(self, base, layers, block_num, block):
  class ConvBNRelu (line 112) | class ConvBNRelu(nn.Layer):
    method __init__ (line 113) | def __init__(self, in_planes: int, out_planes: int, kernel: int = 3, s...
    method forward (line 125) | def forward(self, x):
  class AddBottleneck (line 130) | class AddBottleneck(nn.Layer):
    method __init__ (line 131) | def __init__(self, in_planes: int, out_planes: int, block_num: int = 3...
    method forward (line 183) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class CatBottleneck (line 197) | class CatBottleneck(nn.Layer):
    method __init__ (line 198) | def __init__(self, in_planes: int, out_planes: int, block_num: int = 3...
    method forward (line 237) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  function STDC2 (line 257) | def STDC2(**kwargs):
  function STDC1 (line 261) | def STDC1(**kwargs):

FILE: modules/image/semantic_segmentation/stdc1_seg_voc/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class SeparableConvBNReLU (line 30) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self,
    method forward (line 50) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 56) | class ConvBN(nn.Layer):
    method __init__ (line 59) | def __init__(self,
    method forward (line 70) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBNReLU (line 76) | class ConvBNReLU(nn.Layer):
    method __init__ (line 79) | def __init__(self,
    method forward (line 91) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 98) | class Activation(nn.Layer):
    method __init__ (line 124) | def __init__(self, act: str = None):
    method forward (line 140) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ASPPModule (line 148) | class ASPPModule(nn.Layer):
    method __init__ (line 161) | def __init__(self,
    method forward (line 203) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 230) | class AuxLayer(nn.Layer):
    method __init__ (line 241) | def __init__(self,
    method forward (line 263) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Add (line 270) | class Add(nn.Layer):
    method __init__ (line 271) | def __init__(self):
    method forward (line 274) | def forward(self, x: paddle.Tensor, y: paddle.Tensor, name=None) -> pa...
  class PPModule (line 277) | class PPModule(nn.Layer):
    method __init__ (line 290) | def __init__(self,
    method _make_stage (line 318) | def _make_stage(self, in_channels: int, out_channels: int, size: int):
    method forward (line 343) | def forward(self, input: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/stdc1_seg_voc/module.py
  class STDCSeg (line 38) | class STDCSeg(nn.Layer):
    method __init__ (line 54) | def __init__(self,
    method transform (line 90) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 93) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class SegHead (line 129) | class SegHead(nn.Layer):
    method __init__ (line 130) | def __init__(self, in_chan: int, mid_chan: int, n_classes:int):
    method forward (line 137) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AttentionRefinementModule (line 143) | class AttentionRefinementModule(nn.Layer):
    method __init__ (line 144) | def __init__(self, in_chan: int, out_chan: int):
    method forward (line 153) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ContextPath (line 163) | class ContextPath(nn.Layer):
    method __init__ (line 164) | def __init__(self, backbone, use_conv_last: bool = False):
    method forward (line 179) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class FeatureFusionModule (line 203) | class FeatureFusionModule(nn.Layer):
    method __init__ (line 204) | def __init__(self, in_chan:int , out_chan: int):
    method forward (line 225) | def forward(self, fsp: paddle.Tensor, fcp: paddle.Tensor) -> paddle.Te...

FILE: modules/image/semantic_segmentation/stdc1_seg_voc/stdcnet.py
  class STDCNet (line 25) | class STDCNet(nn.Layer):
    method __init__ (line 44) | def __init__(self,
    method forward (line 77) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
    method _make_layers (line 90) | def _make_layers(self, base, layers, block_num, block):
  class ConvBNRelu (line 111) | class ConvBNRelu(nn.Layer):
    method __init__ (line 112) | def __init__(self, in_planes: int, out_planes: int, kernel: int = 3, s...
    method forward (line 124) | def forward(self, x):
  class AddBottleneck (line 129) | class AddBottleneck(nn.Layer):
    method __init__ (line 130) | def __init__(self, in_planes: int, out_planes: int, block_num: int = 3...
    method forward (line 182) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class CatBottleneck (line 196) | class CatBottleneck(nn.Layer):
    method __init__ (line 197) | def __init__(self, in_planes: int, out_planes: int, block_num: int = 3...
    method forward (line 236) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  function STDC2 (line 256) | def STDC2(**kwargs):
  function STDC1 (line 260) | def STDC1(**kwargs):

FILE: modules/image/semantic_segmentation/unet_cityscapes/layers.py
  function SyncBatchNorm (line 22) | def SyncBatchNorm(*args, **kwargs):
  class ConvBNReLU (line 30) | class ConvBNReLU(nn.Layer):
    method __init__ (line 33) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 40) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvBN (line 47) | class ConvBN(nn.Layer):
    method __init__ (line 50) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 55) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class ConvReLUPool (line 61) | class ConvReLUPool(nn.Layer):
    method __init__ (line 64) | def __init__(self, in_channels: int, out_channels: int):
    method forward (line 68) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class SeparableConvBNReLU (line 75) | class SeparableConvBNReLU(nn.Layer):
    method __init__ (line 78) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 89) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class DepthwiseConvBN (line 95) | class DepthwiseConvBN(nn.Layer):
    method __init__ (line 98) | def __init__(self, in_channels: int, out_channels: int, kernel_size: i...
    method forward (line 108) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class AuxLayer (line 113) | class AuxLayer(nn.Layer):
    method __init__ (line 124) | def __init__(self, in_channels: int, inter_channels: int, out_channels...
    method forward (line 133) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:
  class Activation (line 140) | class Activation(nn.Layer):
    method __init__ (line 166) | def __init__(self, act: str = None):
    method forward (line 181) | def forward(self, x: paddle.Tensor) -> paddle.Tensor:

FILE: modules/image/semantic_segmentation/unet_cityscapes/module.py
  class UNet (line 37) | class UNet(nn.Layer):
    method __init__ (line 54) | def __init__(self,
    method transform (line 78) | def transform(self, img: Union[np.ndarray, str]) -> Union[np.ndarray, ...
    method forward (line 81) | def forward(self, x: paddle.Tensor) -> List[paddle.Tensor]:
  class Encoder (line 90) | class Encoder(nn.Layer):
    method __init__ (line 91) | def __init__(self):
    method down_sampling (line 98) | def down_sampling(self, in_channels: int, out_channels: int) -> nn.Layer:
    method forward (line 105) | def forward(self, x: paddle.Tensor) -> Tuple:
  class Decoder (line 114) | class Decoder(nn.Layer):
    method __init__ (line 115) | def __init__(self, align_corners: bool, use_deconv: bool = False):
    method forward (line 122) | def forward(self, x: paddle.Tensor, short_cuts: List) -> paddle.Tensor:
  class UpSampling (line 128) | class UpSampling(nn.Layer):
    method __init__ (line 129) | def __init__(self, in_channels: int, out_channels: int, align_corners:...
    method forward (line 144) | def forward(self, x: paddle.Tensor, short_cut: paddle.Tensor) -> paddl...

FILE: modules/image/text_recognition/Vehicle_License_Plate_Recognition/module.py
  class Vehicle_License_Plate_Recognition (line 17) | class Vehicle_License_Plate_Recognition(nn.Layer):
    method __init__ (line 18) | def __init__(self):
    method base64_to_cv2 (line 25) | def base64_to_cv2(b64str):
    method plate_recognition (line 31) | def plate_recognition(self, images=None):
    method serving_method (line 47) | def serving_method(self, images):

FILE: modules/image/text_recognition/arabic_ocr_db_crnn_mobile/module.py
  class ArabicOCRDBCRNNMobile (line 13) | class ArabicOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/ch_pp-ocrv3/character.py
  class CharacterOps (line 19) | class CharacterOps(object):
    method __init__ (line 25) | def __init__(self, config):
    method add_special_char (line 61) | def add_special_char(self, dict_character):
    method encode (line 65) | def encode(self, text):
    method decode (line 86) | def decode(self, text_index, text_prob=None, is_remove_duplicate=False):
    method get_char_num (line 109) | def get_char_num(self):
    method get_beg_end_flag_idx (line 112) | def get_beg_end_flag_idx(self, beg_or_end):
    method get_ignored_tokens (line 127) | def get_ignored_tokens(self):
  function cal_predicts_accuracy (line 131) | def cal_predicts_accuracy(char_ops, preds, preds_lod, labels, labels_lod...
  function cal_predicts_accuracy_srn (line 167) | def cal_predicts_accuracy_srn(char_ops, preds, labels, max_text_len, is_...
  function convert_rec_attention_infer_res (line 197) | def convert_rec_attention_infer_res(preds):
  function convert_rec_label_to_lod (line 214) | def convert_rec_label_to_lod(ori_labels):

FILE: modules/image/text_recognition/ch_pp-ocrv3/module.py
  class ChPPOCRv3 (line 48) | class ChPPOCRv3:
    method __init__ (line 50) | def __init__(self, text_detector_module=None, enable_mkldnn=False):
    method _set_config (line 75) | def _set_config(self, pretrained_model_path):
    method text_detector_module (line 116) | def text_detector_module(self):
    method read_images (line 126) | def read_images(self, paths=[]):
    method get_rotate_crop_image (line 137) | def get_rotate_crop_image(self, img, points):
    method resize_norm_img_rec (line 161) | def resize_norm_img_rec(self, img, max_wh_ratio):
    method resize_norm_img_cls (line 180) | def resize_norm_img_cls(self, img):
    method recognize_text (line 203) | def recognize_text(self,
    method serving_method (line 295) | def serving_method(self, images, **kwargs):
    method save_result_image (line 303) | def save_result_image(
    method _classify_text (line 330) | def _classify_text(self, image_list, angle_classification_thresh=0.9):
    method _recognize_text (line 372) | def _recognize_text(self, img_list):
    method run_cmd (line 425) | def run_cmd(self, argvs):
    method add_module_config_arg (line 450) | def add_module_config_arg(self):
    method add_module_input_arg (line 476) | def add_module_input_arg(self):
    method create_gradio_app (line 482) | def create_gradio_app(self):

FILE: modules/image/text_recognition/ch_pp-ocrv3/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_recognize_text1 (line 32) | def test_recognize_text1(self):
    method test_recognize_text2 (line 48) | def test_recognize_text2(self):
    method test_recognize_text3 (line 64) | def test_recognize_text3(self):
    method test_recognize_text4 (line 80) | def test_recognize_text4(self):
    method test_recognize_text5 (line 96) | def test_recognize_text5(self):
    method test_recognize_text6 (line 99) | def test_recognize_text6(self):
    method test_save_inference_model (line 102) | def test_save_inference_model(self):

FILE: modules/image/text_recognition/ch_pp-ocrv3/utils.py
  function draw_ocr (line 30) | def draw_ocr(image, boxes, txts, scores, font_file, draw_txt=True, drop_...
  function text_visual (line 59) | def text_visual(texts, scores, font_file, img_h=400, img_w=600, threshol...
  function str_count (line 128) | def str_count(s):
  function resize_img (line 152) | def resize_img(img, input_size=600):
  function get_image_ext (line 162) | def get_image_ext(image):
  function sorted_boxes (line 168) | def sorted_boxes(dt_boxes):
  function base64_to_cv2 (line 189) | def base64_to_cv2(b64str):

FILE: modules/image/text_recognition/ch_pp-ocrv3_det/module.py
  function base64_to_cv2 (line 37) | def base64_to_cv2(b64str):
  class ChPPOCRv3Det (line 65) | class ChPPOCRv3Det:
    method __init__ (line 67) | def __init__(self, enable_mkldnn=False):
    method check_requirements (line 76) | def check_requirements(self):
    method _set_config (line 84) | def _set_config(self):
    method read_images (line 123) | def read_images(self, paths=[]):
    method order_points_clockwise (line 134) | def order_points_clockwise(self, pts):
    method clip_det_res (line 144) | def clip_det_res(self, points, img_height, img_width):
    method filter_tag_det_res (line 150) | def filter_tag_det_res(self, dt_boxes, image_shape):
    method filter_tag_det_res_only_clip (line 164) | def filter_tag_det_res_only_clip(self, dt_boxes, image_shape):
    method detect_text (line 173) | def detect_text(self,
    method serving_method (line 273) | def serving_method(self, images, **kwargs):
    method run_cmd (line 282) | def run_cmd(self, argvs):
    method add_module_config_arg (line 307) | def add_module_config_arg(self):
    method add_module_input_arg (line 333) | def add_module_input_arg(self):

FILE: modules/image/text_recognition/ch_pp-ocrv3_det/processor.py
  class DBProcessTest (line 28) | class DBProcessTest(object):
    method __init__ (line 33) | def __init__(self, params):
    method resize_image_type0 (line 44) | def resize_image_type0(self, img):
    method resize_image_type1 (line 80) | def resize_image_type1(self, im):
    method normalize (line 88) | def normalize(self, im):
    method __call__ (line 103) | def __call__(self, im):
  class DBPostProcess (line 114) | class DBPostProcess(object):
    method __init__ (line 119) | def __init__(self, params):
    method boxes_from_bitmap (line 128) | def boxes_from_bitmap(self, pred, _bitmap, dest_width, dest_height):
    method unclip (line 172) | def unclip(self, box):
    method get_mini_boxes (line 181) | def get_mini_boxes(self, contour):
    method box_score_fast (line 202) | def box_score_fast(self, bitmap, _box):
    method box_score_slow (line 219) | def box_score_slow(self, bitmap, contour):
    method __call__ (line 240) | def __call__(self, outs_dict, shape_list):
  function draw_boxes (line 257) | def draw_boxes(image, boxes, scores=None, drop_score=0.5):
  function get_image_ext (line 276) | def get_image_ext(image):

FILE: modules/image/text_recognition/ch_pp-ocrv3_det/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_detect_text1 (line 32) | def test_detect_text1(self):
    method test_detect_text2 (line 42) | def test_detect_text2(self):
    method test_detect_text3 (line 52) | def test_detect_text3(self):
    method test_detect_text4 (line 62) | def test_detect_text4(self):
    method test_detect_text5 (line 72) | def test_detect_text5(self):
    method test_detect_text6 (line 75) | def test_detect_text6(self):
    method test_save_inference_model (line 78) | def test_save_inference_model(self):

FILE: modules/image/text_recognition/chinese_cht_ocr_db_crnn_mobile/module.py
  class ChineseChtOCRDBCRNNMobile (line 13) | class ChineseChtOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_mobile/character.py
  class CharacterOps (line 19) | class CharacterOps(object):
    method __init__ (line 25) | def __init__(self, config):
    method encode (line 68) | def encode(self, text):
    method decode (line 89) | def decode(self, text_index, is_remove_duplicate=False):
    method get_char_num (line 111) | def get_char_num(self):
    method get_beg_end_flag_idx (line 114) | def get_beg_end_flag_idx(self, beg_or_end):
  function cal_predicts_accuracy (line 130) | def cal_predicts_accuracy(char_ops, preds, preds_lod, labels, labels_lod...
  function cal_predicts_accuracy_srn (line 166) | def cal_predicts_accuracy_srn(char_ops, preds, labels, max_text_len, is_...
  function convert_rec_attention_infer_res (line 196) | def convert_rec_attention_infer_res(preds):
  function convert_rec_label_to_lod (line 213) | def convert_rec_label_to_lod(ori_labels):

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_mobile/module.py
  class ChineseOCRDBCRNN (line 35) | class ChineseOCRDBCRNN:
    method __init__ (line 37) | def __init__(self, text_detector_module=None, enable_mkldnn=False):
    method _set_config (line 62) | def _set_config(self, pretrained_model_path):
    method text_detector_module (line 103) | def text_detector_module(self):
    method read_images (line 112) | def read_images(self, paths=[]):
    method get_rotate_crop_image (line 123) | def get_rotate_crop_image(self, img, points):
    method resize_norm_img_rec (line 147) | def resize_norm_img_rec(self, img, max_wh_ratio):
    method resize_norm_img_cls (line 166) | def resize_norm_img_cls(self, img):
    method recognize_text (line 189) | def recognize_text(self,
    method serving_method (line 276) | def serving_method(self, images, **kwargs):
    method save_result_image (line 284) | def save_result_image(
    method _classify_text (line 311) | def _classify_text(self, image_list, angle_classification_thresh=0.9):
    method _recognize_text (line 355) | def _recognize_text(self, img_list):
    method save_inference_model (line 408) | def save_inference_model(self, dirname):
    method _save_detector_model (line 418) | def _save_detector_model(self, dirname):
    method _save_recognizer_model (line 421) | def _save_recognizer_model(self, dirname):
    method _save_classifier_model (line 435) | def _save_classifier_model(self, dirname):
    method run_cmd (line 450) | def run_cmd(self, argvs):
    method add_module_config_arg (line 473) | def add_module_config_arg(self):
    method add_module_input_arg (line 490) | def add_module_input_arg(self):
    method create_gradio_app (line 496) | def create_gradio_app(self):

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_mobile/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_recognize_text1 (line 32) | def test_recognize_text1(self):
    method test_recognize_text2 (line 48) | def test_recognize_text2(self):
    method test_recognize_text3 (line 64) | def test_recognize_text3(self):
    method test_recognize_text4 (line 80) | def test_recognize_text4(self):
    method test_recognize_text5 (line 96) | def test_recognize_text5(self):
    method test_recognize_text6 (line 99) | def test_recognize_text6(self):
    method test_save_inference_model (line 102) | def test_save_inference_model(self):

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_mobile/utils.py
  function draw_ocr (line 16) | def draw_ocr(image, boxes, txts, scores, font_file, draw_txt=True, drop_...
  function text_visual (line 45) | def text_visual(texts, scores, font_file, img_h=400, img_w=600, threshol...
  function str_count (line 114) | def str_count(s):
  function resize_img (line 138) | def resize_img(img, input_size=600):
  function get_image_ext (line 148) | def get_image_ext(image):
  function sorted_boxes (line 154) | def sorted_boxes(dt_boxes):
  function base64_to_cv2 (line 175) | def base64_to_cv2(b64str):

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_server/character.py
  class CharacterOps (line 19) | class CharacterOps(object):
    method __init__ (line 25) | def __init__(self, config):
    method encode (line 68) | def encode(self, text):
    method decode (line 89) | def decode(self, text_index, is_remove_duplicate=False):
    method get_char_num (line 111) | def get_char_num(self):
    method get_beg_end_flag_idx (line 114) | def get_beg_end_flag_idx(self, beg_or_end):
  function cal_predicts_accuracy (line 130) | def cal_predicts_accuracy(char_ops, preds, preds_lod, labels, labels_lod...
  function cal_predicts_accuracy_srn (line 166) | def cal_predicts_accuracy_srn(char_ops, preds, labels, max_text_len, is_...
  function convert_rec_attention_infer_res (line 196) | def convert_rec_attention_infer_res(preds):
  function convert_rec_label_to_lod (line 213) | def convert_rec_label_to_lod(ori_labels):

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_server/module.py
  class ChineseOCRDBCRNNServer (line 39) | class ChineseOCRDBCRNNServer:
    method __init__ (line 41) | def __init__(self, text_detector_module=None, enable_mkldnn=False):
    method _set_config (line 66) | def _set_config(self, pretrained_model_path):
    method text_detector_module (line 107) | def text_detector_module(self):
    method read_images (line 116) | def read_images(self, paths=[]):
    method get_rotate_crop_image (line 127) | def get_rotate_crop_image(self, img, points):
    method resize_norm_img_rec (line 151) | def resize_norm_img_rec(self, img, max_wh_ratio):
    method resize_norm_img_cls (line 170) | def resize_norm_img_cls(self, img):
    method recognize_text (line 193) | def recognize_text(self,
    method serving_method (line 280) | def serving_method(self, images, **kwargs):
    method save_result_image (line 288) | def save_result_image(
    method _classify_text (line 315) | def _classify_text(self, image_list, angle_classification_thresh=0.9):
    method _recognize_text (line 359) | def _recognize_text(self, img_list):
    method save_inference_model (line 412) | def save_inference_model(self, dirname):
    method _save_detector_model (line 422) | def _save_detector_model(self, dirname):
    method _save_recognizer_model (line 425) | def _save_recognizer_model(self, dirname):
    method _save_classifier_model (line 439) | def _save_classifier_model(self, dirname):
    method run_cmd (line 454) | def run_cmd(self, argvs):
    method add_module_config_arg (line 477) | def add_module_config_arg(self):
    method add_module_input_arg (line 494) | def add_module_input_arg(self):
    method create_gradio_app (line 500) | def create_gradio_app(self):

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_server/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_recognize_text1 (line 32) | def test_recognize_text1(self):
    method test_recognize_text2 (line 48) | def test_recognize_text2(self):
    method test_recognize_text3 (line 64) | def test_recognize_text3(self):
    method test_recognize_text4 (line 80) | def test_recognize_text4(self):
    method test_recognize_text5 (line 96) | def test_recognize_text5(self):
    method test_recognize_text6 (line 99) | def test_recognize_text6(self):
    method test_save_inference_model (line 102) | def test_save_inference_model(self):

FILE: modules/image/text_recognition/chinese_ocr_db_crnn_server/utils.py
  function draw_ocr (line 16) | def draw_ocr(image, boxes, txts, scores, font_file, draw_txt=True, drop_...
  function text_visual (line 45) | def text_visual(texts, scores, font_file, img_h=400, img_w=600, threshol...
  function str_count (line 114) | def str_count(s):
  function resize_img (line 138) | def resize_img(img, input_size=600):
  function get_image_ext (line 148) | def get_image_ext(image):
  function sorted_boxes (line 154) | def sorted_boxes(dt_boxes):
  function base64_to_cv2 (line 175) | def base64_to_cv2(b64str):

FILE: modules/image/text_recognition/chinese_text_detection_db_mobile/module.py
  function base64_to_cv2 (line 24) | def base64_to_cv2(b64str):
  class ChineseTextDetectionDB (line 52) | class ChineseTextDetectionDB:
    method __init__ (line 54) | def __init__(self, enable_mkldnn=False):
    method check_requirements (line 63) | def check_requirements(self):
    method _set_config (line 71) | def _set_config(self):
    method read_images (line 110) | def read_images(self, paths=[]):
    method order_points_clockwise (line 121) | def order_points_clockwise(self, pts):
    method clip_det_res (line 145) | def clip_det_res(self, points, img_height, img_width):
    method filter_tag_det_res (line 151) | def filter_tag_det_res(self, dt_boxes, image_shape):
    method filter_tag_det_res_only_clip (line 165) | def filter_tag_det_res_only_clip(self, dt_boxes, image_shape):
    method detect_text (line 174) | def detect_text(self,
    method serving_method (line 270) | def serving_method(self, images, **kwargs):
    method run_cmd (line 279) | def run_cmd(self, argvs):
    method add_module_config_arg (line 302) | def add_module_config_arg(self):
    method add_module_input_arg (line 319) | def add_module_input_arg(self):

FILE: modules/image/text_recognition/chinese_text_detection_db_mobile/processor.py
  class DBProcessTest (line 14) | class DBProcessTest(object):
    method __init__ (line 19) | def __init__(self, params):
    method resize_image_type0 (line 31) | def resize_image_type0(self, im):
    method resize_image_type1 (line 78) | def resize_image_type1(self, im):
    method normalize (line 86) | def normalize(self, im):
    method __call__ (line 101) | def __call__(self, im):
  class DBPostProcess (line 111) | class DBPostProcess(object):
    method __init__ (line 116) | def __init__(self, params):
    method boxes_from_bitmap (line 124) | def boxes_from_bitmap(self, pred, _bitmap, dest_width, dest_height):
    method unclip (line 168) | def unclip(self, box):
    method get_mini_boxes (line 177) | def get_mini_boxes(self, contour):
    method box_score_fast (line 198) | def box_score_fast(self, bitmap, _box):
    method __call__ (line 212) | def __call__(self, outs_dict, ratio_list):
  function draw_boxes (line 240) | def draw_boxes(image, boxes, scores=None, drop_score=0.5):
  function get_image_ext (line 259) | def get_image_ext(image):

FILE: modules/image/text_recognition/chinese_text_detection_db_mobile/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_detect_text1 (line 32) | def test_detect_text1(self):
    method test_detect_text2 (line 42) | def test_detect_text2(self):
    method test_detect_text3 (line 52) | def test_detect_text3(self):
    method test_detect_text4 (line 62) | def test_detect_text4(self):
    method test_detect_text5 (line 72) | def test_detect_text5(self):
    method test_detect_text6 (line 75) | def test_detect_text6(self):
    method test_save_inference_model (line 78) | def test_save_inference_model(self):

FILE: modules/image/text_recognition/chinese_text_detection_db_server/module.py
  function base64_to_cv2 (line 25) | def base64_to_cv2(b64str):
  class ChineseTextDetectionDBServer (line 53) | class ChineseTextDetectionDBServer:
    method __init__ (line 55) | def __init__(self, enable_mkldnn=False):
    method check_requirements (line 64) | def check_requirements(self):
    method _set_config (line 72) | def _set_config(self):
    method read_images (line 108) | def read_images(self, paths=[]):
    method filter_tag_det_res (line 119) | def filter_tag_det_res(self, dt_boxes, image_shape):
    method order_points_clockwise (line 140) | def order_points_clockwise(self, pts):
    method detect_text (line 164) | def detect_text(self,
    method serving_method (line 245) | def serving_method(self, images, **kwargs):
    method run_cmd (line 254) | def run_cmd(self, argvs):
    method add_module_config_arg (line 277) | def add_module_config_arg(self):
    method add_module_input_arg (line 294) | def add_module_input_arg(self):

FILE: modules/image/text_recognition/chinese_text_detection_db_server/processor.py
  class DBPreProcess (line 14) | class DBPreProcess(object):
    method __init__ (line 16) | def __init__(self, max_side_len=960):
    method resize_image_type (line 19) | def resize_image_type(self, im):
    method normalize (line 61) | def normalize(self, im):
    method __call__ (line 72) | def __call__(self, im):
  class DBPostProcess (line 79) | class DBPostProcess(object):
    method __init__ (line 84) | def __init__(self, thresh=0.3, box_thresh=0.5, max_candidates=1000):
    method boxes_from_bitmap (line 90) | def boxes_from_bitmap(self, pred, _bitmap, dest_width, dest_height):
    method unclip (line 134) | def unclip(self, box, unclip_ratio=2.0):
    method get_mini_boxes (line 142) | def get_mini_boxes(self, contour):
    method box_score_fast (line 163) | def box_score_fast(self, bitmap, _box):
    method __call__ (line 177) | def __call__(self, predictions, ratio_list):
  function draw_boxes (line 201) | def draw_boxes(image, boxes, scores=None, drop_score=0.5):
  function get_image_ext (line 220) | def get_image_ext(image):

FILE: modules/image/text_recognition/chinese_text_detection_db_server/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 16) | def setUpClass(cls) -> None:
    method tearDownClass (line 27) | def tearDownClass(cls) -> None:
    method test_detect_text1 (line 32) | def test_detect_text1(self):
    method test_detect_text2 (line 42) | def test_detect_text2(self):
    method test_detect_text3 (line 52) | def test_detect_text3(self):
    method test_detect_text4 (line 62) | def test_detect_text4(self):
    method test_detect_text5 (line 72) | def test_detect_text5(self):
    method test_detect_text6 (line 75) | def test_detect_text6(self):
    method test_save_inference_model (line 78) | def test_save_inference_model(self):

FILE: modules/image/text_recognition/cyrillic_ocr_db_crnn_mobile/module.py
  class CyrillicOCRDBCRNNMobile (line 13) | class CyrillicOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/devanagari_ocr_db_crnn_mobile/module.py
  class DevanagariOCRDBCRNNMobile (line 13) | class DevanagariOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/french_ocr_db_crnn_mobile/module.py
  class FrechOCRDBCRNNMobile (line 13) | class FrechOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/german_ocr_db_crnn_mobile/module.py
  class GermanOCRDBCRNNMobile (line 13) | class GermanOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/japan_ocr_db_crnn_mobile/module.py
  class JapanOCRDBCRNNMobile (line 13) | class JapanOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/kannada_ocr_db_crnn_mobile/module.py
  class KannadaOCRDBCRNNMobile (line 13) | class KannadaOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/korean_ocr_db_crnn_mobile/module.py
  class KoreanOCRDBCRNNMobile (line 13) | class KoreanOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/latin_ocr_db_crnn_mobile/module.py
  class LatinOCRDBCRNNMobile (line 13) | class LatinOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/multi_languages_ocr_db_crnn/module.py
  class MultiLangOCR (line 23) | class MultiLangOCR:
    method __init__ (line 24) | def __init__(self,
    method recognize_text (line 63) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 118) | def serving_method(self, images, **kwargs):
    method run_cmd (line 127) | def run_cmd(self, argvs):
    method arg_parser (line 151) | def arg_parser(self):
    method export_onnx_model (line 179) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/multi_languages_ocr_db_crnn/test.py
  class TestHubModule (line 13) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 15) | def setUpClass(cls) -> None:
    method tearDownClass (line 26) | def tearDownClass(cls) -> None:
    method test_recognize_text1 (line 31) | def test_recognize_text1(self):
    method test_recognize_text2 (line 46) | def test_recognize_text2(self):
    method test_recognize_text3 (line 61) | def test_recognize_text3(self):
    method test_recognize_text4 (line 76) | def test_recognize_text4(self):
    method test_recognize_text5 (line 83) | def test_recognize_text5(self):
    method test_export_onnx_model (line 90) | def test_export_onnx_model(self):

FILE: modules/image/text_recognition/multi_languages_ocr_db_crnn/utils.py
  function save_result_image (line 11) | def save_result_image(original_image,
  function read_images (line 61) | def read_images(paths=[]):
  function draw_boxes (line 72) | def draw_boxes(image, boxes, scores=None, drop_score=0.5):
  function get_image_ext (line 91) | def get_image_ext(image):
  function mkdir (line 97) | def mkdir(path):

FILE: modules/image/text_recognition/tamil_ocr_db_crnn_mobile/module.py
  class TamilOCRDBCRNNMobile (line 13) | class TamilOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_recognition/telugu_ocr_db_crnn_mobile/module.py
  class TeluguOCRDBCRNNMobile (line 13) | class TeluguOCRDBCRNNMobile:
    method __init__ (line 14) | def __init__(self,
    method recognize_text (line 46) | def recognize_text(self, images=[], paths=[], output_dir='ocr_result',...
    method serving_method (line 62) | def serving_method(self, images, **kwargs):
    method run_cmd (line 71) | def run_cmd(self, argvs):
    method export_onnx_model (line 78) | def export_onnx_model(self, dirname: str, input_shape_dict=None, opset...

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/clip/clip/layers.py
  function multi_head_attention_forward (line 12) | def multi_head_attention_forward(x: Tensor,
  class MultiHeadAttention (line 47) | class MultiHeadAttention(nn.Layer):  # without attention mask
    method __init__ (line 49) | def __init__(self, emb_dim: int, num_heads: int):
    method forward (line 61) | def forward(self, x, attn_mask=None):  # x is in shape[max_len,batch_s...
  class Identity (line 74) | class Identity(nn.Layer):
    method __init__ (line 76) | def __init__(self):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 83) | class Bottleneck(nn.Layer):
    method __init__ (line 86) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 111) | def forward(self, x):
  class AttentionPool2d (line 127) | class AttentionPool2d(nn.Layer):
    method __init__ (line 129) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 143) | def forward(self, x):
  class QuickGELU (line 155) | class QuickGELU(nn.Layer):
    method forward (line 157) | def forward(self, x):
  class ResidualAttentionBlock (line 161) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 163) | def __init__(self, d_model: int, n_head: int, attn_mask=None):
    method attention (line 173) | def attention(self, x):
    method forward (line 178) | def forward(self, x):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/clip/clip/model.py
  class ModifiedResNet (line 15) | class ModifiedResNet(nn.Layer):
    method __init__ (line 23) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 48) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 57) | def forward(self, x):
  class Transformer (line 76) | class Transformer(nn.Layer):
    method __init__ (line 78) | def __init__(self, width: int, layers: int, heads: int, attn_mask=None):
    method forward (line 84) | def forward(self, x):
  class VisualTransformer (line 88) | class VisualTransformer(nn.Layer):
    method __init__ (line 90) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 113) | def forward(self, x):
  class CLIP (line 132) | class CLIP(nn.Layer):
    method __init__ (line 134) | def __init__(
    method build_attention_mask (line 180) | def build_attention_mask(self):
    method encode_image (line 191) | def encode_image(self, image):
    method encode_text (line 194) | def encode_text(self, text):
    method forward (line 213) | def forward(self, image, text):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/clip/clip/simple_tokenizer.py
  function default_bpe (line 11) | def default_bpe():
  function bytes_to_unicode (line 16) | def bytes_to_unicode():
  function get_pairs (line 38) | def get_pairs(word):
  function basic_clean (line 50) | def basic_clean(text):
  function whitespace_clean (line 56) | def whitespace_clean(text):
  class SimpleTokenizer (line 62) | class SimpleTokenizer(object):
    method __init__ (line 64) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/clip/clip/utils.py
  function tokenize (line 38) | def tokenize(texts: Union[str, List[str]], context_length: int = 77):
  function build_model (line 70) | def build_model(name='RN101'):
  function build_vit_model (line 81) | def build_vit_model():
  function build_rn101_model (line 96) | def build_rn101_model():
  function build_rn50_model (line 111) | def build_rn50_model():

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/module.py
  class DiscoDiffusionClip (line 39) | class DiscoDiffusionClip:
    method generate_image (line 41) | def generate_image(self,
    method serving_method (line 173) | def serving_method(self, text_prompts, **kwargs):
    method run_cmd (line 181) | def run_cmd(self, argvs):
    method add_module_config_arg (line 230) | def add_module_config_arg(self):
    method add_module_input_arg (line 391) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/resize_right/interp_methods.py
  function set_framework_dependencies (line 18) | def set_framework_dependencies(x):
  function support_sz (line 30) | def support_sz(sz):
  function cubic (line 40) | def cubic(x):
  function lanczos2 (line 50) | def lanczos2(x):
  function lanczos3 (line 56) | def lanczos3(x):
  function linear (line 62) | def linear(x):
  function box (line 68) | def box(x):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/resize_right/resize_right.py
  class NoneClass (line 9) | class NoneClass:
  function resize (line 33) | def resize(input,
  function get_projected_grid (line 111) | def get_projected_grid(in_sz, out_sz, scale_factor, fw, by_convs, device...
  function get_field_of_view (line 125) | def get_field_of_view(projected_grid, cur_support_sz, fw, eps, device):
  function calc_pad_sz (line 137) | def calc_pad_sz(in_sz, out_sz, field_of_view, projected_grid, scale_fact...
  function get_weights (line 186) | def get_weights(interp_method, projected_grid, field_of_view):
  function apply_weights (line 199) | def apply_weights(input, field_of_view, weights, dim, n_dims, pad_sz, pa...
  function apply_convs (line 232) | def apply_convs(input, scale_factor, in_sz, out_sz, weights, dim, pad_sz...
  function set_scale_and_out_sz (line 260) | def set_scale_and_out_sz(in_shape, out_shape, scale_factors, by_convs, s...
  function apply_antialiasing_if_needed (line 315) | def apply_antialiasing_if_needed(interp_method, support_sz, scale_factor...
  function fw_ceil (line 328) | def fw_ceil(x, fw):
  function fw_floor (line 335) | def fw_floor(x, fw):
  function fw_cat (line 342) | def fw_cat(x, fw):
  function fw_swapaxes (line 349) | def fw_swapaxes(x, ax_1, ax_2, fw):
  function fw_pad (line 364) | def fw_pad(x, fw, pad_sz, pad_mode, dim=0):
  function fw_conv (line 380) | def fw_conv(input, filter, stride):
  function fw_arange (line 392) | def fw_arange(upper_bound, fw, device):
  function fw_empty (line 399) | def fw_empty(shape, fw, device):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/__init__.py
  function create (line 40) | def create(text_prompts: Optional[List[str]] = [
  function create (line 118) | def create(init_document: 'Document') -> 'DocumentArray':
  function create (line 126) | def create(**kwargs) -> 'DocumentArray':

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/config.py
  function load_config (line 19) | def load_config(user_config: Dict, ):
  function print_args_table (line 53) | def print_args_table(cfg):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/helper.py
  function _get_logger (line 19) | def _get_logger():
  function load_clip_models (line 33) | def load_clip_models(enabled: List[str], clip_models: Dict[str, Any] = {}):
  function load_all_models (line 54) | def load_all_models(diffusion_model, use_secondary_model):
  function load_diffusion_model (line 109) | def load_diffusion_model(model_config, diffusion_model, steps):
  function parse_prompt (line 130) | def parse_prompt(prompt):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/gaussian_diffusion.py
  function get_named_beta_schedule (line 17) | def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
  function betas_for_alpha_bar (line 42) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
  class ModelMeanType (line 62) | class ModelMeanType(enum.Enum):
  class ModelVarType (line 72) | class ModelVarType(enum.Enum):
  class LossType (line 86) | class LossType(enum.Enum):
    method is_vb (line 92) | def is_vb(self):
  class GaussianDiffusion (line 96) | class GaussianDiffusion:
    method __init__ (line 113) | def __init__(
    method q_mean_variance (line 156) | def q_mean_variance(self, x_start, t):
    method q_sample (line 169) | def q_sample(self, x_start, t, noise=None):
    method q_posterior_mean_variance (line 187) | def q_posterior_mean_variance(self, x_start, x_t, t):
    method p_mean_variance (line 203) | def p_mean_variance(self, model, x, t, clip_denoised=True, denoised_fn...
    method _predict_xstart_from_eps (line 287) | def _predict_xstart_from_eps(self, x_t, t, eps):
    method _predict_xstart_from_xprev (line 292) | def _predict_xstart_from_xprev(self, x_t, t, xprev):
    method _predict_eps_from_xstart (line 298) | def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
    method _scale_timesteps (line 302) | def _scale_timesteps(self, t):
    method condition_mean (line 307) | def condition_mean(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_mean_with_grad (line 321) | def condition_mean_with_grad(self, cond_fn, p_mean_var, x, t, model_kw...
    method condition_score (line 335) | def condition_score(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_score_with_grad (line 355) | def condition_score_with_grad(self, cond_fn, p_mean_var, x, t, model_k...
    method p_sample (line 375) | def p_sample(
    method p_sample_with_grad (line 419) | def p_sample_with_grad(
    method p_sample_loop (line 467) | def p_sample_loop(
    method p_sample_loop_progressive (line 521) | def p_sample_loop_progressive(
    method ddim_sample (line 586) | def ddim_sample(
    method ddim_sample_with_grad (line 633) | def ddim_sample_with_grad(
    method ddim_reverse_sample (line 686) | def ddim_reverse_sample(
    method ddim_sample_loop (line 719) | def ddim_sample_loop(
    method ddim_sample_loop_progressive (line 761) | def ddim_sample_loop_progressive(
    method plms_sample (line 831) | def plms_sample(
    method plms_sample_loop (line 915) | def plms_sample_loop(
    method plms_sample_loop_progressive (line 957) | def plms_sample_loop_progressive(
    method _vb_terms_bpd (line 1026) | def _vb_terms_bpd(self, model, x_start, x_t, t, clip_denoised=True, mo...
    method training_losses (line 1052) | def training_losses(self, model, x_start, t, model_kwargs=None, noise=...
    method _prior_bpd (line 1126) | def _prior_bpd(self, x_start):
    method calc_bpd_loop (line 1142) | def calc_bpd_loop(self, model, x_start, clip_denoised=True, model_kwar...
  function _extract_into_tensor (line 1201) | def _extract_into_tensor(arr, timesteps, broadcast_shape):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/losses.py
  function normal_kl (line 11) | def normal_kl(mean1, logvar1, mean2, logvar2):
  function approx_standard_normal_cdf (line 33) | def approx_standard_normal_cdf(x):
  function discretized_gaussian_log_likelihood (line 41) | def discretized_gaussian_log_likelihood(x, *, means, log_scales):
  function spherical_dist_loss (line 71) | def spherical_dist_loss(x, y):
  function tv_loss (line 77) | def tv_loss(input):
  function range_loss (line 85) | def range_loss(input):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/make_cutouts.py
  function sinc (line 17) | def sinc(x):
  function lanczos (line 21) | def lanczos(x, a):
  function ramp (line 27) | def ramp(ratio, width):
  class MakeCutouts (line 37) | class MakeCutouts(nn.Layer):
    method __init__ (line 39) | def __init__(self, cut_size, cutn, skip_augs=False):
    method forward (line 56) | def forward(self, input):
  class MakeCutoutsDango (line 81) | class MakeCutoutsDango(nn.Layer):
    method __init__ (line 83) | def __init__(self, cut_size, Overview=4, InnerCrop=0, IC_Size_Pow=0.5,...
    method forward (line 104) | def forward(self, input):
  function resample (line 155) | def resample(input, size, align_corners=True):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/nn.py
  class SiLU (line 11) | class SiLU(nn.Layer):
    method forward (line 13) | def forward(self, x):
  class GroupNorm32 (line 17) | class GroupNorm32(nn.GroupNorm):
    method forward (line 19) | def forward(self, x):
  function conv_nd (line 23) | def conv_nd(dims, *args, **kwargs):
  function linear (line 36) | def linear(*args, **kwargs):
  function avg_pool_nd (line 43) | def avg_pool_nd(dims, *args, **kwargs):
  function update_ema (line 56) | def update_ema(target_params, source_params, rate=0.99):
  function zero_module (line 69) | def zero_module(module):
  function scale_module (line 78) | def scale_module(module, scale):
  function mean_flat (line 87) | def mean_flat(tensor):
  function normalization (line 94) | def normalization(channels):
  function timestep_embedding (line 104) | def timestep_embedding(timesteps, dim, max_period=10000):
  function checkpoint (line 123) | def checkpoint(func, inputs, params, flag):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/perlin_noises.py
  function interp (line 13) | def interp(t):
  function perlin (line 17) | def perlin(width, height, scale=10):
  function perlin_ms (line 31) | def perlin_ms(octaves, width, height, grayscale):
  function create_perlin_noise (line 47) | def create_perlin_noise(octaves, width, height, grayscale, side_y, side_x):
  function regen_perlin (line 65) | def regen_perlin(perlin_mode, side_y, side_x, batch_size):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/respace.py
  function space_timesteps (line 11) | def space_timesteps(num_timesteps, section_counts):
  class SpacedDiffusion (line 63) | class SpacedDiffusion(GaussianDiffusion):
    method __init__ (line 72) | def __init__(self, use_timesteps, **kwargs):
    method p_mean_variance (line 88) | def p_mean_variance(self, model, *args, **kwargs):  # pylint: disable=...
    method training_losses (line 91) | def training_losses(self, model, *args, **kwargs):  # pylint: disable=...
    method condition_mean (line 94) | def condition_mean(self, cond_fn, *args, **kwargs):
    method condition_score (line 97) | def condition_score(self, cond_fn, *args, **kwargs):
    method _wrap_model (line 100) | def _wrap_model(self, model):
    method _scale_timesteps (line 105) | def _scale_timesteps(self, t):
  class _WrappedModel (line 110) | class _WrappedModel:
    method __init__ (line 112) | def __init__(self, model, timestep_map, rescale_timesteps, original_nu...
    method __call__ (line 118) | def __call__(self, x, ts, **kwargs):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/script_util.py
  function diffusion_defaults (line 18) | def diffusion_defaults():
  function model_and_diffusion_defaults (line 34) | def model_and_diffusion_defaults():
  function create_model_and_diffusion (line 59) | def create_model_and_diffusion(
  function create_model (line 115) | def create_model(
  function create_gaussian_diffusion (line 172) | def create_gaussian_diffusion(

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/sec_diff.py
  class DiffusionOutput (line 14) | class DiffusionOutput:
  class SkipBlock (line 20) | class SkipBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self, main, skip=None):
    method forward (line 27) | def forward(self, input):
  function append_dims (line 31) | def append_dims(x, n):
  function expand_to_planes (line 35) | def expand_to_planes(x, shape):
  function alpha_sigma_to_t (line 39) | def alpha_sigma_to_t(alpha, sigma):
  function t_to_alpha_sigma (line 43) | def t_to_alpha_sigma(t):
  class SecondaryDiffusionImageNet2 (line 47) | class SecondaryDiffusionImageNet2(nn.Layer):
    method __init__ (line 49) | def __init__(self):
    method forward (line 105) | def forward(self, input, t):
  class FourierFeatures (line 114) | class FourierFeatures(nn.Layer):
    method __init__ (line 116) | def __init__(self, in_features, out_features, std=1.0):
    method forward (line 124) | def forward(self, input):
  class ConvBlock (line 129) | class ConvBlock(nn.Sequential):
    method __init__ (line 131) | def __init__(self, c_in, c_out):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/transforms.py
  class Normalize (line 25) | class Normalize(nn.Layer):
    method __init__ (line 27) | def __init__(self, mean, std):
    method forward (line 32) | def forward(self, tensor: Tensor):
  class InterpolationMode (line 42) | class InterpolationMode(Enum):
  class Grayscale (line 56) | class Grayscale(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_output_channels):
    method forward (line 62) | def forward(self, x):
  class Lambda (line 70) | class Lambda(nn.Layer):
    method __init__ (line 72) | def __init__(self, func):
    method forward (line 76) | def forward(self, x):
  class RandomGrayscale (line 80) | class RandomGrayscale(nn.Layer):
    method __init__ (line 82) | def __init__(self, p):
    method forward (line 87) | def forward(self, x):
  class RandomHorizontalFlip (line 94) | class RandomHorizontalFlip(nn.Layer):
    method __init__ (line 96) | def __init__(self, prob):
    method forward (line 100) | def forward(self, x):
  function _blend (line 107) | def _blend(img1: Tensor, img2: Tensor, ratio: float) -> Tensor:
  function trunc_div (line 113) | def trunc_div(a, b):
  function fmod (line 122) | def fmod(a, b):
  function _rgb2hsv (line 126) | def _rgb2hsv(img: Tensor) -> Tensor:
  function _hsv2rgb (line 165) | def _hsv2rgb(img: Tensor) -> Tensor:
  function adjust_brightness (line 186) | def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
  function adjust_contrast (line 193) | def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
  function adjust_hue (line 209) | def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
  function adjust_saturation (line 221) | def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
  class ColorJitter (line 230) | class ColorJitter(nn.Layer):
    method __init__ (line 232) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):
    method _check_input (line 239) | def _check_input(self, value, name, center=1, bound=(0, float("inf")),...
    method get_params (line 259) | def get_params(
    method forward (line 290) | def forward(self, img):
    method __repr__ (line 313) | def __repr__(self) -> str:
  function _apply_grid_transform (line 322) | def _apply_grid_transform(img: Tensor, grid: Tensor, mode: str, fill: Op...
  function _gen_affine_grid (line 350) | def _gen_affine_grid(
  function affine_impl (line 375) | def affine_impl(img: Tensor,
  function _get_inverse_affine_matrix (line 386) | def _get_inverse_affine_matrix(center: List[float],
  function affine (line 449) | def affine(
  function _interpolation_modes_from_int (line 558) | def _interpolation_modes_from_int(i: int) -> InterpolationMode:
  function _check_sequence_input (line 570) | def _check_sequence_input(x, name, req_sizes):
  function _setup_angle (line 578) | def _setup_angle(x, name, req_sizes=(2, )):
  class RandomAffine (line 589) | class RandomAffine(nn.Layer):
    method __init__ (line 631) | def __init__(
    method get_params (line 696) | def get_params(
    method forward (line 733) | def forward(self, img):
    method __repr__ (line 747) | def __repr__(self) -> str:

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/model/unet.py
  class AttentionPool2d (line 23) | class AttentionPool2d(nn.Layer):
    method __init__ (line 28) | def __init__(
    method forward (line 46) | def forward(self, x):
  class TimestepBlock (line 58) | class TimestepBlock(nn.Layer):
    method forward (line 64) | def forward(self, x, emb):
  class TimestepEmbedSequential (line 70) | class TimestepEmbedSequential(nn.Sequential, TimestepBlock):
    method forward (line 76) | def forward(self, x, emb):
  class Upsample (line 85) | class Upsample(nn.Layer):
    method __init__ (line 95) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 104) | def forward(self, x):
  class Downsample (line 115) | class Downsample(nn.Layer):
    method __init__ (line 125) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 138) | def forward(self, x):
  class ResBlock (line 143) | class ResBlock(TimestepBlock):
    method __init__ (line 160) | def __init__(
    method forward (line 220) | def forward(self, x, emb):
    method _forward (line 230) | def _forward(self, x, emb):
  class AttentionBlock (line 254) | class AttentionBlock(nn.Layer):
    method __init__ (line 262) | def __init__(
    method forward (line 290) | def forward(self, x):
    method _forward (line 293) | def _forward(self, x):
  function count_flops_attn (line 304) | def count_flops_attn(model, _x, y):
  class QKVAttentionLegacy (line 324) | class QKVAttentionLegacy(nn.Layer):
    method __init__ (line 329) | def __init__(self, n_heads):
    method forward (line 333) | def forward(self, qkv):
    method count_flops (line 353) | def count_flops(model, _x, y):
  class QKVAttention (line 357) | class QKVAttention(nn.Layer):
    method __init__ (line 362) | def __init__(self, n_heads):
    method forward (line 366) | def forward(self, qkv):
    method count_flops (line 389) | def count_flops(model, _x, y):
  class UNetModel (line 393) | class UNetModel(nn.Layer):
    method __init__ (line 424) | def __init__(
    method forward (line 602) | def forward(self, x, timesteps, y=None):
  class SuperResModel (line 632) | class SuperResModel(UNetModel):
    method __init__ (line 639) | def __init__(self, image_size, in_channels, *args, **kwargs):
    method forward (line 642) | def forward(self, x, timesteps, low_res=None, **kwargs):
  class EncoderUNetModel (line 649) | class EncoderUNetModel(nn.Layer):
    method __init__ (line 656) | def __init__(
    method forward (line 812) | def forward(self, x, timesteps):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn101/reverse_diffusion/runner.py
  function do_run (line 32) | def do_run(args, models) -> 'DocumentArray':
  function _silent_push (line 281) | def _silent_push(da_batches: DocumentArray, name: str) -> None:

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/clip/clip/layers.py
  function multi_head_attention_forward (line 12) | def multi_head_attention_forward(x: Tensor,
  class MultiHeadAttention (line 47) | class MultiHeadAttention(nn.Layer):  # without attention mask
    method __init__ (line 49) | def __init__(self, emb_dim: int, num_heads: int):
    method forward (line 61) | def forward(self, x, attn_mask=None):  # x is in shape[max_len,batch_s...
  class Identity (line 74) | class Identity(nn.Layer):
    method __init__ (line 76) | def __init__(self):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 83) | class Bottleneck(nn.Layer):
    method __init__ (line 86) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 111) | def forward(self, x):
  class AttentionPool2d (line 127) | class AttentionPool2d(nn.Layer):
    method __init__ (line 129) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 143) | def forward(self, x):
  class QuickGELU (line 155) | class QuickGELU(nn.Layer):
    method forward (line 157) | def forward(self, x):
  class ResidualAttentionBlock (line 161) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 163) | def __init__(self, d_model: int, n_head: int, attn_mask=None):
    method attention (line 173) | def attention(self, x):
    method forward (line 178) | def forward(self, x):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/clip/clip/model.py
  class ModifiedResNet (line 15) | class ModifiedResNet(nn.Layer):
    method __init__ (line 23) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 48) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 57) | def forward(self, x):
  class Transformer (line 76) | class Transformer(nn.Layer):
    method __init__ (line 78) | def __init__(self, width: int, layers: int, heads: int, attn_mask=None):
    method forward (line 84) | def forward(self, x):
  class VisualTransformer (line 88) | class VisualTransformer(nn.Layer):
    method __init__ (line 90) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 113) | def forward(self, x):
  class CLIP (line 132) | class CLIP(nn.Layer):
    method __init__ (line 134) | def __init__(
    method build_attention_mask (line 180) | def build_attention_mask(self):
    method encode_image (line 191) | def encode_image(self, image):
    method encode_text (line 194) | def encode_text(self, text):
    method forward (line 213) | def forward(self, image, text):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/clip/clip/simple_tokenizer.py
  function default_bpe (line 11) | def default_bpe():
  function bytes_to_unicode (line 16) | def bytes_to_unicode():
  function get_pairs (line 38) | def get_pairs(word):
  function basic_clean (line 50) | def basic_clean(text):
  function whitespace_clean (line 56) | def whitespace_clean(text):
  class SimpleTokenizer (line 62) | class SimpleTokenizer(object):
    method __init__ (line 64) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/clip/clip/utils.py
  function tokenize (line 38) | def tokenize(texts: Union[str, List[str]], context_length: int = 77):
  function build_model (line 70) | def build_model(name='RN50'):
  function build_vit_model (line 81) | def build_vit_model():
  function build_rn101_model (line 96) | def build_rn101_model():
  function build_rn50_model (line 111) | def build_rn50_model():

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/module.py
  class DiscoDiffusionClip (line 39) | class DiscoDiffusionClip:
    method generate_image (line 41) | def generate_image(self,
    method serving_method (line 173) | def serving_method(self, text_prompts, **kwargs):
    method run_cmd (line 181) | def run_cmd(self, argvs):
    method add_module_config_arg (line 230) | def add_module_config_arg(self):
    method add_module_input_arg (line 391) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/resize_right/interp_methods.py
  function set_framework_dependencies (line 18) | def set_framework_dependencies(x):
  function support_sz (line 30) | def support_sz(sz):
  function cubic (line 40) | def cubic(x):
  function lanczos2 (line 50) | def lanczos2(x):
  function lanczos3 (line 56) | def lanczos3(x):
  function linear (line 62) | def linear(x):
  function box (line 68) | def box(x):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/resize_right/resize_right.py
  class NoneClass (line 9) | class NoneClass:
  function resize (line 33) | def resize(input,
  function get_projected_grid (line 111) | def get_projected_grid(in_sz, out_sz, scale_factor, fw, by_convs, device...
  function get_field_of_view (line 125) | def get_field_of_view(projected_grid, cur_support_sz, fw, eps, device):
  function calc_pad_sz (line 137) | def calc_pad_sz(in_sz, out_sz, field_of_view, projected_grid, scale_fact...
  function get_weights (line 186) | def get_weights(interp_method, projected_grid, field_of_view):
  function apply_weights (line 199) | def apply_weights(input, field_of_view, weights, dim, n_dims, pad_sz, pa...
  function apply_convs (line 232) | def apply_convs(input, scale_factor, in_sz, out_sz, weights, dim, pad_sz...
  function set_scale_and_out_sz (line 260) | def set_scale_and_out_sz(in_shape, out_shape, scale_factors, by_convs, s...
  function apply_antialiasing_if_needed (line 315) | def apply_antialiasing_if_needed(interp_method, support_sz, scale_factor...
  function fw_ceil (line 328) | def fw_ceil(x, fw):
  function fw_floor (line 335) | def fw_floor(x, fw):
  function fw_cat (line 342) | def fw_cat(x, fw):
  function fw_swapaxes (line 349) | def fw_swapaxes(x, ax_1, ax_2, fw):
  function fw_pad (line 364) | def fw_pad(x, fw, pad_sz, pad_mode, dim=0):
  function fw_conv (line 380) | def fw_conv(input, filter, stride):
  function fw_arange (line 392) | def fw_arange(upper_bound, fw, device):
  function fw_empty (line 399) | def fw_empty(shape, fw, device):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/__init__.py
  function create (line 40) | def create(text_prompts: Optional[List[str]] = [
  function create (line 118) | def create(init_document: 'Document') -> 'DocumentArray':
  function create (line 126) | def create(**kwargs) -> 'DocumentArray':

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/config.py
  function load_config (line 19) | def load_config(user_config: Dict, ):
  function print_args_table (line 53) | def print_args_table(cfg):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/helper.py
  function _get_logger (line 19) | def _get_logger():
  function load_clip_models (line 33) | def load_clip_models(enabled: List[str], clip_models: Dict[str, Any] = {}):
  function load_all_models (line 54) | def load_all_models(diffusion_model, use_secondary_model):
  function load_diffusion_model (line 109) | def load_diffusion_model(model_config, diffusion_model, steps):
  function parse_prompt (line 130) | def parse_prompt(prompt):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/gaussian_diffusion.py
  function get_named_beta_schedule (line 17) | def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
  function betas_for_alpha_bar (line 42) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
  class ModelMeanType (line 62) | class ModelMeanType(enum.Enum):
  class ModelVarType (line 72) | class ModelVarType(enum.Enum):
  class LossType (line 86) | class LossType(enum.Enum):
    method is_vb (line 92) | def is_vb(self):
  class GaussianDiffusion (line 96) | class GaussianDiffusion:
    method __init__ (line 113) | def __init__(
    method q_mean_variance (line 156) | def q_mean_variance(self, x_start, t):
    method q_sample (line 169) | def q_sample(self, x_start, t, noise=None):
    method q_posterior_mean_variance (line 187) | def q_posterior_mean_variance(self, x_start, x_t, t):
    method p_mean_variance (line 203) | def p_mean_variance(self, model, x, t, clip_denoised=True, denoised_fn...
    method _predict_xstart_from_eps (line 287) | def _predict_xstart_from_eps(self, x_t, t, eps):
    method _predict_xstart_from_xprev (line 292) | def _predict_xstart_from_xprev(self, x_t, t, xprev):
    method _predict_eps_from_xstart (line 298) | def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
    method _scale_timesteps (line 302) | def _scale_timesteps(self, t):
    method condition_mean (line 307) | def condition_mean(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_mean_with_grad (line 321) | def condition_mean_with_grad(self, cond_fn, p_mean_var, x, t, model_kw...
    method condition_score (line 335) | def condition_score(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_score_with_grad (line 355) | def condition_score_with_grad(self, cond_fn, p_mean_var, x, t, model_k...
    method p_sample (line 375) | def p_sample(
    method p_sample_with_grad (line 419) | def p_sample_with_grad(
    method p_sample_loop (line 467) | def p_sample_loop(
    method p_sample_loop_progressive (line 521) | def p_sample_loop_progressive(
    method ddim_sample (line 586) | def ddim_sample(
    method ddim_sample_with_grad (line 633) | def ddim_sample_with_grad(
    method ddim_reverse_sample (line 686) | def ddim_reverse_sample(
    method ddim_sample_loop (line 719) | def ddim_sample_loop(
    method ddim_sample_loop_progressive (line 761) | def ddim_sample_loop_progressive(
    method plms_sample (line 831) | def plms_sample(
    method plms_sample_loop (line 915) | def plms_sample_loop(
    method plms_sample_loop_progressive (line 957) | def plms_sample_loop_progressive(
    method _vb_terms_bpd (line 1026) | def _vb_terms_bpd(self, model, x_start, x_t, t, clip_denoised=True, mo...
    method training_losses (line 1052) | def training_losses(self, model, x_start, t, model_kwargs=None, noise=...
    method _prior_bpd (line 1126) | def _prior_bpd(self, x_start):
    method calc_bpd_loop (line 1142) | def calc_bpd_loop(self, model, x_start, clip_denoised=True, model_kwar...
  function _extract_into_tensor (line 1201) | def _extract_into_tensor(arr, timesteps, broadcast_shape):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/losses.py
  function normal_kl (line 11) | def normal_kl(mean1, logvar1, mean2, logvar2):
  function approx_standard_normal_cdf (line 33) | def approx_standard_normal_cdf(x):
  function discretized_gaussian_log_likelihood (line 41) | def discretized_gaussian_log_likelihood(x, *, means, log_scales):
  function spherical_dist_loss (line 71) | def spherical_dist_loss(x, y):
  function tv_loss (line 77) | def tv_loss(input):
  function range_loss (line 85) | def range_loss(input):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/make_cutouts.py
  function sinc (line 17) | def sinc(x):
  function lanczos (line 21) | def lanczos(x, a):
  function ramp (line 27) | def ramp(ratio, width):
  class MakeCutouts (line 37) | class MakeCutouts(nn.Layer):
    method __init__ (line 39) | def __init__(self, cut_size, cutn, skip_augs=False):
    method forward (line 56) | def forward(self, input):
  class MakeCutoutsDango (line 81) | class MakeCutoutsDango(nn.Layer):
    method __init__ (line 83) | def __init__(self, cut_size, Overview=4, InnerCrop=0, IC_Size_Pow=0.5,...
    method forward (line 104) | def forward(self, input):
  function resample (line 155) | def resample(input, size, align_corners=True):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/nn.py
  class SiLU (line 11) | class SiLU(nn.Layer):
    method forward (line 13) | def forward(self, x):
  class GroupNorm32 (line 17) | class GroupNorm32(nn.GroupNorm):
    method forward (line 19) | def forward(self, x):
  function conv_nd (line 23) | def conv_nd(dims, *args, **kwargs):
  function linear (line 36) | def linear(*args, **kwargs):
  function avg_pool_nd (line 43) | def avg_pool_nd(dims, *args, **kwargs):
  function update_ema (line 56) | def update_ema(target_params, source_params, rate=0.99):
  function zero_module (line 69) | def zero_module(module):
  function scale_module (line 78) | def scale_module(module, scale):
  function mean_flat (line 87) | def mean_flat(tensor):
  function normalization (line 94) | def normalization(channels):
  function timestep_embedding (line 104) | def timestep_embedding(timesteps, dim, max_period=10000):
  function checkpoint (line 123) | def checkpoint(func, inputs, params, flag):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/perlin_noises.py
  function interp (line 13) | def interp(t):
  function perlin (line 17) | def perlin(width, height, scale=10):
  function perlin_ms (line 31) | def perlin_ms(octaves, width, height, grayscale):
  function create_perlin_noise (line 47) | def create_perlin_noise(octaves, width, height, grayscale, side_y, side_x):
  function regen_perlin (line 65) | def regen_perlin(perlin_mode, side_y, side_x, batch_size):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/respace.py
  function space_timesteps (line 11) | def space_timesteps(num_timesteps, section_counts):
  class SpacedDiffusion (line 63) | class SpacedDiffusion(GaussianDiffusion):
    method __init__ (line 72) | def __init__(self, use_timesteps, **kwargs):
    method p_mean_variance (line 88) | def p_mean_variance(self, model, *args, **kwargs):  # pylint: disable=...
    method training_losses (line 91) | def training_losses(self, model, *args, **kwargs):  # pylint: disable=...
    method condition_mean (line 94) | def condition_mean(self, cond_fn, *args, **kwargs):
    method condition_score (line 97) | def condition_score(self, cond_fn, *args, **kwargs):
    method _wrap_model (line 100) | def _wrap_model(self, model):
    method _scale_timesteps (line 105) | def _scale_timesteps(self, t):
  class _WrappedModel (line 110) | class _WrappedModel:
    method __init__ (line 112) | def __init__(self, model, timestep_map, rescale_timesteps, original_nu...
    method __call__ (line 118) | def __call__(self, x, ts, **kwargs):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/script_util.py
  function diffusion_defaults (line 18) | def diffusion_defaults():
  function model_and_diffusion_defaults (line 34) | def model_and_diffusion_defaults():
  function create_model_and_diffusion (line 59) | def create_model_and_diffusion(
  function create_model (line 115) | def create_model(
  function create_gaussian_diffusion (line 172) | def create_gaussian_diffusion(

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/sec_diff.py
  class DiffusionOutput (line 14) | class DiffusionOutput:
  class SkipBlock (line 20) | class SkipBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self, main, skip=None):
    method forward (line 27) | def forward(self, input):
  function append_dims (line 31) | def append_dims(x, n):
  function expand_to_planes (line 35) | def expand_to_planes(x, shape):
  function alpha_sigma_to_t (line 39) | def alpha_sigma_to_t(alpha, sigma):
  function t_to_alpha_sigma (line 43) | def t_to_alpha_sigma(t):
  class SecondaryDiffusionImageNet2 (line 47) | class SecondaryDiffusionImageNet2(nn.Layer):
    method __init__ (line 49) | def __init__(self):
    method forward (line 105) | def forward(self, input, t):
  class FourierFeatures (line 114) | class FourierFeatures(nn.Layer):
    method __init__ (line 116) | def __init__(self, in_features, out_features, std=1.0):
    method forward (line 124) | def forward(self, input):
  class ConvBlock (line 129) | class ConvBlock(nn.Sequential):
    method __init__ (line 131) | def __init__(self, c_in, c_out):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/transforms.py
  class Normalize (line 25) | class Normalize(nn.Layer):
    method __init__ (line 27) | def __init__(self, mean, std):
    method forward (line 32) | def forward(self, tensor: Tensor):
  class InterpolationMode (line 42) | class InterpolationMode(Enum):
  class Grayscale (line 56) | class Grayscale(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_output_channels):
    method forward (line 62) | def forward(self, x):
  class Lambda (line 70) | class Lambda(nn.Layer):
    method __init__ (line 72) | def __init__(self, func):
    method forward (line 76) | def forward(self, x):
  class RandomGrayscale (line 80) | class RandomGrayscale(nn.Layer):
    method __init__ (line 82) | def __init__(self, p):
    method forward (line 87) | def forward(self, x):
  class RandomHorizontalFlip (line 94) | class RandomHorizontalFlip(nn.Layer):
    method __init__ (line 96) | def __init__(self, prob):
    method forward (line 100) | def forward(self, x):
  function _blend (line 107) | def _blend(img1: Tensor, img2: Tensor, ratio: float) -> Tensor:
  function trunc_div (line 113) | def trunc_div(a, b):
  function fmod (line 122) | def fmod(a, b):
  function _rgb2hsv (line 126) | def _rgb2hsv(img: Tensor) -> Tensor:
  function _hsv2rgb (line 165) | def _hsv2rgb(img: Tensor) -> Tensor:
  function adjust_brightness (line 186) | def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
  function adjust_contrast (line 193) | def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
  function adjust_hue (line 209) | def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
  function adjust_saturation (line 221) | def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
  class ColorJitter (line 230) | class ColorJitter(nn.Layer):
    method __init__ (line 232) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):
    method _check_input (line 239) | def _check_input(self, value, name, center=1, bound=(0, float("inf")),...
    method get_params (line 259) | def get_params(
    method forward (line 290) | def forward(self, img):
    method __repr__ (line 313) | def __repr__(self) -> str:
  function _apply_grid_transform (line 322) | def _apply_grid_transform(img: Tensor, grid: Tensor, mode: str, fill: Op...
  function _gen_affine_grid (line 350) | def _gen_affine_grid(
  function affine_impl (line 375) | def affine_impl(img: Tensor,
  function _get_inverse_affine_matrix (line 386) | def _get_inverse_affine_matrix(center: List[float],
  function affine (line 449) | def affine(
  function _interpolation_modes_from_int (line 558) | def _interpolation_modes_from_int(i: int) -> InterpolationMode:
  function _check_sequence_input (line 570) | def _check_sequence_input(x, name, req_sizes):
  function _setup_angle (line 578) | def _setup_angle(x, name, req_sizes=(2, )):
  class RandomAffine (line 589) | class RandomAffine(nn.Layer):
    method __init__ (line 631) | def __init__(
    method get_params (line 696) | def get_params(
    method forward (line 733) | def forward(self, img):
    method __repr__ (line 747) | def __repr__(self) -> str:

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/unet.py
  class AttentionPool2d (line 23) | class AttentionPool2d(nn.Layer):
    method __init__ (line 28) | def __init__(
    method forward (line 46) | def forward(self, x):
  class TimestepBlock (line 58) | class TimestepBlock(nn.Layer):
    method forward (line 64) | def forward(self, x, emb):
  class TimestepEmbedSequential (line 70) | class TimestepEmbedSequential(nn.Sequential, TimestepBlock):
    method forward (line 76) | def forward(self, x, emb):
  class Upsample (line 85) | class Upsample(nn.Layer):
    method __init__ (line 95) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 104) | def forward(self, x):
  class Downsample (line 115) | class Downsample(nn.Layer):
    method __init__ (line 125) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 138) | def forward(self, x):
  class ResBlock (line 143) | class ResBlock(TimestepBlock):
    method __init__ (line 160) | def __init__(
    method forward (line 220) | def forward(self, x, emb):
    method _forward (line 230) | def _forward(self, x, emb):
  class AttentionBlock (line 254) | class AttentionBlock(nn.Layer):
    method __init__ (line 262) | def __init__(
    method forward (line 290) | def forward(self, x):
    method _forward (line 293) | def _forward(self, x):
  function count_flops_attn (line 304) | def count_flops_attn(model, _x, y):
  class QKVAttentionLegacy (line 324) | class QKVAttentionLegacy(nn.Layer):
    method __init__ (line 329) | def __init__(self, n_heads):
    method forward (line 333) | def forward(self, qkv):
    method count_flops (line 353) | def count_flops(model, _x, y):
  class QKVAttention (line 357) | class QKVAttention(nn.Layer):
    method __init__ (line 362) | def __init__(self, n_heads):
    method forward (line 366) | def forward(self, qkv):
    method count_flops (line 389) | def count_flops(model, _x, y):
  class UNetModel (line 393) | class UNetModel(nn.Layer):
    method __init__ (line 424) | def __init__(
    method forward (line 602) | def forward(self, x, timesteps, y=None):
  class SuperResModel (line 632) | class SuperResModel(UNetModel):
    method __init__ (line 639) | def __init__(self, image_size, in_channels, *args, **kwargs):
    method forward (line 642) | def forward(self, x, timesteps, low_res=None, **kwargs):
  class EncoderUNetModel (line 649) | class EncoderUNetModel(nn.Layer):
    method __init__ (line 656) | def __init__(
    method forward (line 812) | def forward(self, x, timesteps):

FILE: modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/runner.py
  function do_run (line 32) | def do_run(args, models) -> 'DocumentArray':
  function _silent_push (line 281) | def _silent_push(da_batches: DocumentArray, name: str) -> None:

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/clip/clip/layers.py
  function multi_head_attention_forward (line 12) | def multi_head_attention_forward(x: Tensor,
  class MultiHeadAttention (line 47) | class MultiHeadAttention(nn.Layer):  # without attention mask
    method __init__ (line 49) | def __init__(self, emb_dim: int, num_heads: int):
    method forward (line 61) | def forward(self, x, attn_mask=None):  # x is in shape[max_len,batch_s...
  class Identity (line 74) | class Identity(nn.Layer):
    method __init__ (line 76) | def __init__(self):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 83) | class Bottleneck(nn.Layer):
    method __init__ (line 86) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 111) | def forward(self, x):
  class AttentionPool2d (line 127) | class AttentionPool2d(nn.Layer):
    method __init__ (line 129) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 143) | def forward(self, x):
  class QuickGELU (line 155) | class QuickGELU(nn.Layer):
    method forward (line 157) | def forward(self, x):
  class ResidualAttentionBlock (line 161) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 163) | def __init__(self, d_model: int, n_head: int, attn_mask=None):
    method attention (line 173) | def attention(self, x):
    method forward (line 178) | def forward(self, x):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/clip/clip/model.py
  class ModifiedResNet (line 15) | class ModifiedResNet(nn.Layer):
    method __init__ (line 23) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 48) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 57) | def forward(self, x):
  class Transformer (line 76) | class Transformer(nn.Layer):
    method __init__ (line 78) | def __init__(self, width: int, layers: int, heads: int, attn_mask=None):
    method forward (line 84) | def forward(self, x):
  class VisualTransformer (line 88) | class VisualTransformer(nn.Layer):
    method __init__ (line 90) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 113) | def forward(self, x):
  class CLIP (line 132) | class CLIP(nn.Layer):
    method __init__ (line 134) | def __init__(
    method build_attention_mask (line 180) | def build_attention_mask(self):
    method encode_image (line 191) | def encode_image(self, image):
    method encode_text (line 194) | def encode_text(self, text):
    method forward (line 213) | def forward(self, image, text):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/clip/clip/simple_tokenizer.py
  function default_bpe (line 11) | def default_bpe():
  function bytes_to_unicode (line 16) | def bytes_to_unicode():
  function get_pairs (line 38) | def get_pairs(word):
  function basic_clean (line 50) | def basic_clean(text):
  function whitespace_clean (line 56) | def whitespace_clean(text):
  class SimpleTokenizer (line 62) | class SimpleTokenizer(object):
    method __init__ (line 64) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/clip/clip/utils.py
  function tokenize (line 38) | def tokenize(texts: Union[str, List[str]], context_length: int = 77):
  function build_model (line 70) | def build_model(name='VIT32'):
  function build_vit_model (line 81) | def build_vit_model():
  function build_rn101_model (line 96) | def build_rn101_model():
  function build_rn50_model (line 111) | def build_rn50_model():

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/module.py
  class DiscoDiffusionClip (line 39) | class DiscoDiffusionClip:
    method generate_image (line 41) | def generate_image(self,
    method serving_method (line 173) | def serving_method(self, text_prompts, **kwargs):
    method run_cmd (line 181) | def run_cmd(self, argvs):
    method add_module_config_arg (line 230) | def add_module_config_arg(self):
    method add_module_input_arg (line 391) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/resize_right/interp_methods.py
  function set_framework_dependencies (line 18) | def set_framework_dependencies(x):
  function support_sz (line 30) | def support_sz(sz):
  function cubic (line 40) | def cubic(x):
  function lanczos2 (line 50) | def lanczos2(x):
  function lanczos3 (line 56) | def lanczos3(x):
  function linear (line 62) | def linear(x):
  function box (line 68) | def box(x):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/resize_right/resize_right.py
  class NoneClass (line 9) | class NoneClass:
  function resize (line 33) | def resize(input,
  function get_projected_grid (line 111) | def get_projected_grid(in_sz, out_sz, scale_factor, fw, by_convs, device...
  function get_field_of_view (line 125) | def get_field_of_view(projected_grid, cur_support_sz, fw, eps, device):
  function calc_pad_sz (line 137) | def calc_pad_sz(in_sz, out_sz, field_of_view, projected_grid, scale_fact...
  function get_weights (line 186) | def get_weights(interp_method, projected_grid, field_of_view):
  function apply_weights (line 199) | def apply_weights(input, field_of_view, weights, dim, n_dims, pad_sz, pa...
  function apply_convs (line 232) | def apply_convs(input, scale_factor, in_sz, out_sz, weights, dim, pad_sz...
  function set_scale_and_out_sz (line 260) | def set_scale_and_out_sz(in_shape, out_shape, scale_factors, by_convs, s...
  function apply_antialiasing_if_needed (line 315) | def apply_antialiasing_if_needed(interp_method, support_sz, scale_factor...
  function fw_ceil (line 328) | def fw_ceil(x, fw):
  function fw_floor (line 335) | def fw_floor(x, fw):
  function fw_cat (line 342) | def fw_cat(x, fw):
  function fw_swapaxes (line 349) | def fw_swapaxes(x, ax_1, ax_2, fw):
  function fw_pad (line 364) | def fw_pad(x, fw, pad_sz, pad_mode, dim=0):
  function fw_conv (line 380) | def fw_conv(input, filter, stride):
  function fw_arange (line 392) | def fw_arange(upper_bound, fw, device):
  function fw_empty (line 399) | def fw_empty(shape, fw, device):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/__init__.py
  function create (line 40) | def create(text_prompts: Optional[List[str]] = [
  function create (line 118) | def create(init_document: 'Document') -> 'DocumentArray':
  function create (line 126) | def create(**kwargs) -> 'DocumentArray':

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/config.py
  function load_config (line 19) | def load_config(user_config: Dict, ):
  function print_args_table (line 53) | def print_args_table(cfg):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/helper.py
  function _get_logger (line 19) | def _get_logger():
  function load_clip_models (line 33) | def load_clip_models(enabled: List[str], clip_models: Dict[str, Any] = {}):
  function load_all_models (line 54) | def load_all_models(diffusion_model, use_secondary_model):
  function load_diffusion_model (line 109) | def load_diffusion_model(model_config, diffusion_model, steps):
  function parse_prompt (line 130) | def parse_prompt(prompt):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/gaussian_diffusion.py
  function get_named_beta_schedule (line 17) | def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
  function betas_for_alpha_bar (line 42) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
  class ModelMeanType (line 62) | class ModelMeanType(enum.Enum):
  class ModelVarType (line 72) | class ModelVarType(enum.Enum):
  class LossType (line 86) | class LossType(enum.Enum):
    method is_vb (line 92) | def is_vb(self):
  class GaussianDiffusion (line 96) | class GaussianDiffusion:
    method __init__ (line 113) | def __init__(
    method q_mean_variance (line 156) | def q_mean_variance(self, x_start, t):
    method q_sample (line 169) | def q_sample(self, x_start, t, noise=None):
    method q_posterior_mean_variance (line 187) | def q_posterior_mean_variance(self, x_start, x_t, t):
    method p_mean_variance (line 203) | def p_mean_variance(self, model, x, t, clip_denoised=True, denoised_fn...
    method _predict_xstart_from_eps (line 287) | def _predict_xstart_from_eps(self, x_t, t, eps):
    method _predict_xstart_from_xprev (line 292) | def _predict_xstart_from_xprev(self, x_t, t, xprev):
    method _predict_eps_from_xstart (line 298) | def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
    method _scale_timesteps (line 302) | def _scale_timesteps(self, t):
    method condition_mean (line 307) | def condition_mean(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_mean_with_grad (line 321) | def condition_mean_with_grad(self, cond_fn, p_mean_var, x, t, model_kw...
    method condition_score (line 335) | def condition_score(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_score_with_grad (line 355) | def condition_score_with_grad(self, cond_fn, p_mean_var, x, t, model_k...
    method p_sample (line 375) | def p_sample(
    method p_sample_with_grad (line 419) | def p_sample_with_grad(
    method p_sample_loop (line 467) | def p_sample_loop(
    method p_sample_loop_progressive (line 521) | def p_sample_loop_progressive(
    method ddim_sample (line 586) | def ddim_sample(
    method ddim_sample_with_grad (line 633) | def ddim_sample_with_grad(
    method ddim_reverse_sample (line 686) | def ddim_reverse_sample(
    method ddim_sample_loop (line 719) | def ddim_sample_loop(
    method ddim_sample_loop_progressive (line 761) | def ddim_sample_loop_progressive(
    method plms_sample (line 831) | def plms_sample(
    method plms_sample_loop (line 915) | def plms_sample_loop(
    method plms_sample_loop_progressive (line 957) | def plms_sample_loop_progressive(
    method _vb_terms_bpd (line 1026) | def _vb_terms_bpd(self, model, x_start, x_t, t, clip_denoised=True, mo...
    method training_losses (line 1052) | def training_losses(self, model, x_start, t, model_kwargs=None, noise=...
    method _prior_bpd (line 1126) | def _prior_bpd(self, x_start):
    method calc_bpd_loop (line 1142) | def calc_bpd_loop(self, model, x_start, clip_denoised=True, model_kwar...
  function _extract_into_tensor (line 1201) | def _extract_into_tensor(arr, timesteps, broadcast_shape):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/losses.py
  function normal_kl (line 11) | def normal_kl(mean1, logvar1, mean2, logvar2):
  function approx_standard_normal_cdf (line 33) | def approx_standard_normal_cdf(x):
  function discretized_gaussian_log_likelihood (line 41) | def discretized_gaussian_log_likelihood(x, *, means, log_scales):
  function spherical_dist_loss (line 71) | def spherical_dist_loss(x, y):
  function tv_loss (line 77) | def tv_loss(input):
  function range_loss (line 85) | def range_loss(input):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/make_cutouts.py
  function sinc (line 17) | def sinc(x):
  function lanczos (line 21) | def lanczos(x, a):
  function ramp (line 27) | def ramp(ratio, width):
  class MakeCutouts (line 37) | class MakeCutouts(nn.Layer):
    method __init__ (line 39) | def __init__(self, cut_size, cutn, skip_augs=False):
    method forward (line 56) | def forward(self, input):
  class MakeCutoutsDango (line 81) | class MakeCutoutsDango(nn.Layer):
    method __init__ (line 83) | def __init__(self, cut_size, Overview=4, InnerCrop=0, IC_Size_Pow=0.5,...
    method forward (line 104) | def forward(self, input):
  function resample (line 155) | def resample(input, size, align_corners=True):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/nn.py
  class SiLU (line 11) | class SiLU(nn.Layer):
    method forward (line 13) | def forward(self, x):
  class GroupNorm32 (line 17) | class GroupNorm32(nn.GroupNorm):
    method forward (line 19) | def forward(self, x):
  function conv_nd (line 23) | def conv_nd(dims, *args, **kwargs):
  function linear (line 36) | def linear(*args, **kwargs):
  function avg_pool_nd (line 43) | def avg_pool_nd(dims, *args, **kwargs):
  function update_ema (line 56) | def update_ema(target_params, source_params, rate=0.99):
  function zero_module (line 69) | def zero_module(module):
  function scale_module (line 78) | def scale_module(module, scale):
  function mean_flat (line 87) | def mean_flat(tensor):
  function normalization (line 94) | def normalization(channels):
  function timestep_embedding (line 104) | def timestep_embedding(timesteps, dim, max_period=10000):
  function checkpoint (line 123) | def checkpoint(func, inputs, params, flag):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/perlin_noises.py
  function interp (line 13) | def interp(t):
  function perlin (line 17) | def perlin(width, height, scale=10):
  function perlin_ms (line 31) | def perlin_ms(octaves, width, height, grayscale):
  function create_perlin_noise (line 47) | def create_perlin_noise(octaves, width, height, grayscale, side_y, side_x):
  function regen_perlin (line 65) | def regen_perlin(perlin_mode, side_y, side_x, batch_size):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/respace.py
  function space_timesteps (line 11) | def space_timesteps(num_timesteps, section_counts):
  class SpacedDiffusion (line 63) | class SpacedDiffusion(GaussianDiffusion):
    method __init__ (line 72) | def __init__(self, use_timesteps, **kwargs):
    method p_mean_variance (line 88) | def p_mean_variance(self, model, *args, **kwargs):  # pylint: disable=...
    method training_losses (line 91) | def training_losses(self, model, *args, **kwargs):  # pylint: disable=...
    method condition_mean (line 94) | def condition_mean(self, cond_fn, *args, **kwargs):
    method condition_score (line 97) | def condition_score(self, cond_fn, *args, **kwargs):
    method _wrap_model (line 100) | def _wrap_model(self, model):
    method _scale_timesteps (line 105) | def _scale_timesteps(self, t):
  class _WrappedModel (line 110) | class _WrappedModel:
    method __init__ (line 112) | def __init__(self, model, timestep_map, rescale_timesteps, original_nu...
    method __call__ (line 118) | def __call__(self, x, ts, **kwargs):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/script_util.py
  function diffusion_defaults (line 18) | def diffusion_defaults():
  function model_and_diffusion_defaults (line 34) | def model_and_diffusion_defaults():
  function create_model_and_diffusion (line 59) | def create_model_and_diffusion(
  function create_model (line 115) | def create_model(
  function create_gaussian_diffusion (line 172) | def create_gaussian_diffusion(

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/sec_diff.py
  class DiffusionOutput (line 14) | class DiffusionOutput:
  class SkipBlock (line 20) | class SkipBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self, main, skip=None):
    method forward (line 27) | def forward(self, input):
  function append_dims (line 31) | def append_dims(x, n):
  function expand_to_planes (line 35) | def expand_to_planes(x, shape):
  function alpha_sigma_to_t (line 39) | def alpha_sigma_to_t(alpha, sigma):
  function t_to_alpha_sigma (line 43) | def t_to_alpha_sigma(t):
  class SecondaryDiffusionImageNet2 (line 47) | class SecondaryDiffusionImageNet2(nn.Layer):
    method __init__ (line 49) | def __init__(self):
    method forward (line 105) | def forward(self, input, t):
  class FourierFeatures (line 114) | class FourierFeatures(nn.Layer):
    method __init__ (line 116) | def __init__(self, in_features, out_features, std=1.0):
    method forward (line 124) | def forward(self, input):
  class ConvBlock (line 129) | class ConvBlock(nn.Sequential):
    method __init__ (line 131) | def __init__(self, c_in, c_out):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/transforms.py
  class Normalize (line 25) | class Normalize(nn.Layer):
    method __init__ (line 27) | def __init__(self, mean, std):
    method forward (line 32) | def forward(self, tensor: Tensor):
  class InterpolationMode (line 42) | class InterpolationMode(Enum):
  class Grayscale (line 56) | class Grayscale(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_output_channels):
    method forward (line 62) | def forward(self, x):
  class Lambda (line 70) | class Lambda(nn.Layer):
    method __init__ (line 72) | def __init__(self, func):
    method forward (line 76) | def forward(self, x):
  class RandomGrayscale (line 80) | class RandomGrayscale(nn.Layer):
    method __init__ (line 82) | def __init__(self, p):
    method forward (line 87) | def forward(self, x):
  class RandomHorizontalFlip (line 94) | class RandomHorizontalFlip(nn.Layer):
    method __init__ (line 96) | def __init__(self, prob):
    method forward (line 100) | def forward(self, x):
  function _blend (line 107) | def _blend(img1: Tensor, img2: Tensor, ratio: float) -> Tensor:
  function trunc_div (line 113) | def trunc_div(a, b):
  function fmod (line 122) | def fmod(a, b):
  function _rgb2hsv (line 126) | def _rgb2hsv(img: Tensor) -> Tensor:
  function _hsv2rgb (line 165) | def _hsv2rgb(img: Tensor) -> Tensor:
  function adjust_brightness (line 186) | def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
  function adjust_contrast (line 193) | def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
  function adjust_hue (line 209) | def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
  function adjust_saturation (line 221) | def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
  class ColorJitter (line 230) | class ColorJitter(nn.Layer):
    method __init__ (line 232) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):
    method _check_input (line 239) | def _check_input(self, value, name, center=1, bound=(0, float("inf")),...
    method get_params (line 259) | def get_params(
    method forward (line 290) | def forward(self, img):
    method __repr__ (line 313) | def __repr__(self) -> str:
  function _apply_grid_transform (line 322) | def _apply_grid_transform(img: Tensor, grid: Tensor, mode: str, fill: Op...
  function _gen_affine_grid (line 350) | def _gen_affine_grid(
  function affine_impl (line 375) | def affine_impl(img: Tensor,
  function _get_inverse_affine_matrix (line 386) | def _get_inverse_affine_matrix(center: List[float],
  function affine (line 449) | def affine(
  function _interpolation_modes_from_int (line 558) | def _interpolation_modes_from_int(i: int) -> InterpolationMode:
  function _check_sequence_input (line 570) | def _check_sequence_input(x, name, req_sizes):
  function _setup_angle (line 578) | def _setup_angle(x, name, req_sizes=(2, )):
  class RandomAffine (line 589) | class RandomAffine(nn.Layer):
    method __init__ (line 631) | def __init__(
    method get_params (line 696) | def get_params(
    method forward (line 733) | def forward(self, img):
    method __repr__ (line 747) | def __repr__(self) -> str:

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/model/unet.py
  class AttentionPool2d (line 23) | class AttentionPool2d(nn.Layer):
    method __init__ (line 28) | def __init__(
    method forward (line 46) | def forward(self, x):
  class TimestepBlock (line 58) | class TimestepBlock(nn.Layer):
    method forward (line 64) | def forward(self, x, emb):
  class TimestepEmbedSequential (line 70) | class TimestepEmbedSequential(nn.Sequential, TimestepBlock):
    method forward (line 76) | def forward(self, x, emb):
  class Upsample (line 85) | class Upsample(nn.Layer):
    method __init__ (line 95) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 104) | def forward(self, x):
  class Downsample (line 115) | class Downsample(nn.Layer):
    method __init__ (line 125) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 138) | def forward(self, x):
  class ResBlock (line 143) | class ResBlock(TimestepBlock):
    method __init__ (line 160) | def __init__(
    method forward (line 220) | def forward(self, x, emb):
    method _forward (line 230) | def _forward(self, x, emb):
  class AttentionBlock (line 254) | class AttentionBlock(nn.Layer):
    method __init__ (line 262) | def __init__(
    method forward (line 290) | def forward(self, x):
    method _forward (line 293) | def _forward(self, x):
  function count_flops_attn (line 304) | def count_flops_attn(model, _x, y):
  class QKVAttentionLegacy (line 324) | class QKVAttentionLegacy(nn.Layer):
    method __init__ (line 329) | def __init__(self, n_heads):
    method forward (line 333) | def forward(self, qkv):
    method count_flops (line 353) | def count_flops(model, _x, y):
  class QKVAttention (line 357) | class QKVAttention(nn.Layer):
    method __init__ (line 362) | def __init__(self, n_heads):
    method forward (line 366) | def forward(self, qkv):
    method count_flops (line 389) | def count_flops(model, _x, y):
  class UNetModel (line 393) | class UNetModel(nn.Layer):
    method __init__ (line 424) | def __init__(
    method forward (line 602) | def forward(self, x, timesteps, y=None):
  class SuperResModel (line 632) | class SuperResModel(UNetModel):
    method __init__ (line 639) | def __init__(self, image_size, in_channels, *args, **kwargs):
    method forward (line 642) | def forward(self, x, timesteps, low_res=None, **kwargs):
  class EncoderUNetModel (line 649) | class EncoderUNetModel(nn.Layer):
    method __init__ (line 656) | def __init__(
    method forward (line 812) | def forward(self, x, timesteps):

FILE: modules/image/text_to_image/disco_diffusion_clip_vitb32/reverse_diffusion/runner.py
  function do_run (line 32) | def do_run(args, models) -> 'DocumentArray':
  function _silent_push (line 281) | def _silent_push(da_batches: DocumentArray, name: str) -> None:

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/cn_clip/clip/bert_tokenizer.py
  function default_vocab (line 30) | def default_vocab():
  function validate_case_matches_checkpoint (line 34) | def validate_case_matches_checkpoint(do_lower_case, init_checkpoint):
  function convert_to_unicode (line 79) | def convert_to_unicode(text):
  function printable_text (line 99) | def printable_text(text):
  function load_vocab (line 122) | def load_vocab(vocab_file):
  function convert_by_vocab (line 137) | def convert_by_vocab(vocab, items):
  function convert_tokens_to_ids (line 145) | def convert_tokens_to_ids(vocab, tokens):
  function convert_ids_to_tokens (line 149) | def convert_ids_to_tokens(inv_vocab, ids):
  function whitespace_tokenize (line 153) | def whitespace_tokenize(text):
  class FullTokenizer (line 162) | class FullTokenizer(object):
    method __init__ (line 165) | def __init__(self, vocab_file=default_vocab(), do_lower_case=True):
    method tokenize (line 171) | def tokenize(self, text):
    method convert_tokens_to_ids (line 179) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 182) | def convert_ids_to_tokens(self, ids):
    method convert_tokens_to_string (line 186) | def convert_tokens_to_string(tokens, clean_up_tokenization_spaces=True):
    method vocab_size (line 210) | def vocab_size(self):
  class BasicTokenizer (line 214) | class BasicTokenizer(object):
    method __init__ (line 217) | def __init__(self, do_lower_case=True):
    method tokenize (line 225) | def tokenize(self, text):
    method _run_strip_accents (line 249) | def _run_strip_accents(self, text):
    method _run_split_on_punc (line 260) | def _run_split_on_punc(self, text):
    method _tokenize_chinese_chars (line 280) | def _tokenize_chinese_chars(self, text):
    method _is_chinese_char (line 293) | def _is_chinese_char(self, cp):
    method _clean_text (line 314) | def _clean_text(self, text):
  class WordpieceTokenizer (line 328) | class WordpieceTokenizer(object):
    method __init__ (line 331) | def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=...
    method tokenize (line 336) | def tokenize(self, text):
  function _is_whitespace (line 390) | def _is_whitespace(char):
  function _is_control (line 402) | def _is_control(char):
  function _is_punctuation (line 414) | def _is_punctuation(char):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/cn_clip/clip/configuration_bert.py
  class BertConfig (line 27) | class BertConfig(object):
    method __init__ (line 57) | def __init__(self,

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/cn_clip/clip/model.py
  class Bottleneck (line 15) | class Bottleneck(nn.Layer):
    method __init__ (line 18) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 44) | def forward(self, x: paddle.Tensor):
  class QuickGELU (line 60) | class QuickGELU(nn.Layer):
    method forward (line 62) | def forward(self, x: paddle.Tensor):
  class ResidualAttentionBlock (line 66) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 68) | def __init__(self, d_model: int, n_head: int, attn_mask: paddle.Tensor...
    method attention (line 77) | def attention(self, x: paddle.Tensor):
    method forward (line 81) | def forward(self, x: paddle.Tensor):
  class Transformer (line 87) | class Transformer(nn.Layer):
    method __init__ (line 89) | def __init__(self, width: int, layers: int, heads: int, attn_mask: pad...
    method forward (line 95) | def forward(self, x: paddle.Tensor):
  class VisualTransformer (line 99) | class VisualTransformer(nn.Layer):
    method __init__ (line 101) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 127) | def forward(self, x: paddle.Tensor):
  class CLIP (line 146) | class CLIP(nn.Layer):
    method __init__ (line 148) | def __init__(
    method dtype (line 204) | def dtype(self):
    method encode_image (line 207) | def encode_image(self, image):
    method encode_text (line 210) | def encode_text(self, text):
    method forward (line 218) | def forward(self, image, text):
    method get_similarity (line 233) | def get_similarity(self, image, text):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/cn_clip/clip/modeling_bert.py
  function gelu (line 37) | def gelu(x):
  function gelu_new (line 46) | def gelu_new(x):
  function swish (line 53) | def swish(x):
  class BertEmbeddings (line 62) | class BertEmbeddings(nn.Layer):
    method __init__ (line 66) | def __init__(self, config):
    method forward (line 77) | def forward(self, input_ids, token_type_ids=None, position_ids=None):
  class BertSelfAttention (line 98) | class BertSelfAttention(nn.Layer):
    method __init__ (line 100) | def __init__(self, config):
    method transpose_for_scores (line 117) | def transpose_for_scores(self, x):
    method forward (line 122) | def forward(self, hidden_states, attention_mask=None, head_mask=None):
  class BertSelfOutput (line 159) | class BertSelfOutput(nn.Layer):
    method __init__ (line 161) | def __init__(self, config):
    method forward (line 167) | def forward(self, hidden_states, input_tensor):
  class BertAttention (line 174) | class BertAttention(nn.Layer):
    method __init__ (line 176) | def __init__(self, config):
    method forward (line 182) | def forward(self, input_tensor, attention_mask=None, head_mask=None):
  class BertIntermediate (line 189) | class BertIntermediate(nn.Layer):
    method __init__ (line 191) | def __init__(self, config):
    method forward (line 199) | def forward(self, hidden_states):
  class BertOutput (line 205) | class BertOutput(nn.Layer):
    method __init__ (line 207) | def __init__(self, config):
    method forward (line 213) | def forward(self, hidden_states, input_tensor):
  class BertLayer (line 220) | class BertLayer(nn.Layer):
    method __init__ (line 222) | def __init__(self, config):
    method forward (line 228) | def forward(self, hidden_states, attention_mask=None, head_mask=None):
  class BertEncoder (line 237) | class BertEncoder(nn.Layer):
    method __init__ (line 239) | def __init__(self, config):
    method forward (line 245) | def forward(self, hidden_states, attention_mask=None, head_mask=None):
  class BertPooler (line 269) | class BertPooler(nn.Layer):
    method __init__ (line 271) | def __init__(self, config):
    method forward (line 276) | def forward(self, hidden_states):
  class BertPredictionHeadTransform (line 285) | class BertPredictionHeadTransform(nn.Layer):
    method __init__ (line 287) | def __init__(self, config):
    method forward (line 296) | def forward(self, hidden_states):
  class BertLMPredictionHead (line 303) | class BertLMPredictionHead(nn.Layer):
    method __init__ (line 305) | def __init__(self, config):
    method forward (line 315) | def forward(self, hidden_states):
  class BertOnlyMLMHead (line 321) | class BertOnlyMLMHead(nn.Layer):
    method __init__ (line 323) | def __init__(self, config):
    method forward (line 327) | def forward(self, sequence_output):
  class BertOnlyNSPHead (line 332) | class BertOnlyNSPHead(nn.Layer):
    method __init__ (line 334) | def __init__(self, config):
    method forward (line 338) | def forward(self, pooled_output):
  class BertPreTrainingHeads (line 343) | class BertPreTrainingHeads(nn.Layer):
    method __init__ (line 345) | def __init__(self, config):
    method forward (line 350) | def forward(self, sequence_output, pooled_output):
  class BertPreTrainedModel (line 356) | class BertPreTrainedModel(nn.Layer):
    method __init__ (line 360) | def __init__(self, config):
  class BertModel (line 365) | class BertModel(BertPreTrainedModel):
    method __init__ (line 395) | def __init__(self, config):
    method forward (line 402) | def forward(self, input_ids, attention_mask=None, token_type_ids=None,...

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/cn_clip/clip/utils.py
  function available_models (line 18) | def available_models() -> List[str]:
  function tokenize (line 23) | def tokenize(texts: Union[str, List[str]], context_length: int = 64):
  function create_model (line 54) | def create_model(name):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/module.py
  class DiscoDiffusionClip (line 38) | class DiscoDiffusionClip:
    method generate_image (line 40) | def generate_image(self,
    method serving_method (line 172) | def serving_method(self, text_prompts, **kwargs):
    method run_cmd (line 180) | def run_cmd(self, argvs):
    method add_module_config_arg (line 229) | def add_module_config_arg(self):
    method add_module_input_arg (line 390) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/resize_right/interp_methods.py
  function set_framework_dependencies (line 18) | def set_framework_dependencies(x):
  function support_sz (line 30) | def support_sz(sz):
  function cubic (line 40) | def cubic(x):
  function lanczos2 (line 50) | def lanczos2(x):
  function lanczos3 (line 56) | def lanczos3(x):
  function linear (line 62) | def linear(x):
  function box (line 68) | def box(x):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/resize_right/resize_right.py
  class NoneClass (line 9) | class NoneClass:
  function resize (line 33) | def resize(input,
  function get_projected_grid (line 111) | def get_projected_grid(in_sz, out_sz, scale_factor, fw, by_convs, device...
  function get_field_of_view (line 125) | def get_field_of_view(projected_grid, cur_support_sz, fw, eps, device):
  function calc_pad_sz (line 137) | def calc_pad_sz(in_sz, out_sz, field_of_view, projected_grid, scale_fact...
  function get_weights (line 186) | def get_weights(interp_method, projected_grid, field_of_view):
  function apply_weights (line 199) | def apply_weights(input, field_of_view, weights, dim, n_dims, pad_sz, pa...
  function apply_convs (line 232) | def apply_convs(input, scale_factor, in_sz, out_sz, weights, dim, pad_sz...
  function set_scale_and_out_sz (line 260) | def set_scale_and_out_sz(in_shape, out_shape, scale_factors, by_convs, s...
  function apply_antialiasing_if_needed (line 315) | def apply_antialiasing_if_needed(interp_method, support_sz, scale_factor...
  function fw_ceil (line 328) | def fw_ceil(x, fw):
  function fw_floor (line 335) | def fw_floor(x, fw):
  function fw_cat (line 342) | def fw_cat(x, fw):
  function fw_swapaxes (line 349) | def fw_swapaxes(x, ax_1, ax_2, fw):
  function fw_pad (line 364) | def fw_pad(x, fw, pad_sz, pad_mode, dim=0):
  function fw_conv (line 380) | def fw_conv(input, filter, stride):
  function fw_arange (line 392) | def fw_arange(upper_bound, fw, device):
  function fw_empty (line 399) | def fw_empty(shape, fw, device):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/__init__.py
  function create (line 40) | def create(text_prompts: Optional[List[str]] = [
  function create (line 118) | def create(init_document: 'Document') -> 'DocumentArray':
  function create (line 126) | def create(**kwargs) -> 'DocumentArray':

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/config.py
  function load_config (line 19) | def load_config(user_config: Dict, ):
  function print_args_table (line 53) | def print_args_table(cfg):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/helper.py
  function _get_logger (line 19) | def _get_logger():
  function load_clip_models (line 34) | def load_clip_models(enabled: List[str], clip_models: Dict[str, Any] = {}):
  function load_all_models (line 55) | def load_all_models(diffusion_model, use_secondary_model):
  function load_diffusion_model (line 110) | def load_diffusion_model(model_config, diffusion_model, steps):
  function parse_prompt (line 131) | def parse_prompt(prompt):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/gaussian_diffusion.py
  function get_named_beta_schedule (line 17) | def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
  function betas_for_alpha_bar (line 42) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
  class ModelMeanType (line 62) | class ModelMeanType(enum.Enum):
  class ModelVarType (line 72) | class ModelVarType(enum.Enum):
  class LossType (line 86) | class LossType(enum.Enum):
    method is_vb (line 92) | def is_vb(self):
  class GaussianDiffusion (line 96) | class GaussianDiffusion:
    method __init__ (line 113) | def __init__(
    method q_mean_variance (line 156) | def q_mean_variance(self, x_start, t):
    method q_sample (line 169) | def q_sample(self, x_start, t, noise=None):
    method q_posterior_mean_variance (line 187) | def q_posterior_mean_variance(self, x_start, x_t, t):
    method p_mean_variance (line 203) | def p_mean_variance(self, model, x, t, clip_denoised=True, denoised_fn...
    method _predict_xstart_from_eps (line 287) | def _predict_xstart_from_eps(self, x_t, t, eps):
    method _predict_xstart_from_xprev (line 292) | def _predict_xstart_from_xprev(self, x_t, t, xprev):
    method _predict_eps_from_xstart (line 298) | def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
    method _scale_timesteps (line 302) | def _scale_timesteps(self, t):
    method condition_mean (line 307) | def condition_mean(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_mean_with_grad (line 321) | def condition_mean_with_grad(self, cond_fn, p_mean_var, x, t, model_kw...
    method condition_score (line 335) | def condition_score(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_score_with_grad (line 355) | def condition_score_with_grad(self, cond_fn, p_mean_var, x, t, model_k...
    method p_sample (line 375) | def p_sample(
    method p_sample_with_grad (line 419) | def p_sample_with_grad(
    method p_sample_loop (line 467) | def p_sample_loop(
    method p_sample_loop_progressive (line 521) | def p_sample_loop_progressive(
    method ddim_sample (line 586) | def ddim_sample(
    method ddim_sample_with_grad (line 633) | def ddim_sample_with_grad(
    method ddim_reverse_sample (line 686) | def ddim_reverse_sample(
    method ddim_sample_loop (line 719) | def ddim_sample_loop(
    method ddim_sample_loop_progressive (line 761) | def ddim_sample_loop_progressive(
    method plms_sample (line 831) | def plms_sample(
    method plms_sample_loop (line 915) | def plms_sample_loop(
    method plms_sample_loop_progressive (line 957) | def plms_sample_loop_progressive(
    method _vb_terms_bpd (line 1026) | def _vb_terms_bpd(self, model, x_start, x_t, t, clip_denoised=True, mo...
    method training_losses (line 1052) | def training_losses(self, model, x_start, t, model_kwargs=None, noise=...
    method _prior_bpd (line 1126) | def _prior_bpd(self, x_start):
    method calc_bpd_loop (line 1142) | def calc_bpd_loop(self, model, x_start, clip_denoised=True, model_kwar...
  function _extract_into_tensor (line 1201) | def _extract_into_tensor(arr, timesteps, broadcast_shape):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/losses.py
  function normal_kl (line 11) | def normal_kl(mean1, logvar1, mean2, logvar2):
  function approx_standard_normal_cdf (line 33) | def approx_standard_normal_cdf(x):
  function discretized_gaussian_log_likelihood (line 41) | def discretized_gaussian_log_likelihood(x, *, means, log_scales):
  function spherical_dist_loss (line 71) | def spherical_dist_loss(x, y):
  function tv_loss (line 77) | def tv_loss(input):
  function range_loss (line 85) | def range_loss(input):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/make_cutouts.py
  function sinc (line 17) | def sinc(x):
  function lanczos (line 21) | def lanczos(x, a):
  function ramp (line 27) | def ramp(ratio, width):
  class MakeCutouts (line 37) | class MakeCutouts(nn.Layer):
    method __init__ (line 39) | def __init__(self, cut_size, cutn, skip_augs=False):
    method forward (line 56) | def forward(self, input):
  class MakeCutoutsDango (line 81) | class MakeCutoutsDango(nn.Layer):
    method __init__ (line 83) | def __init__(self, cut_size, Overview=4, InnerCrop=0, IC_Size_Pow=0.5,...
    method forward (line 104) | def forward(self, input):
  function resample (line 155) | def resample(input, size, align_corners=True):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/nn.py
  class SiLU (line 11) | class SiLU(nn.Layer):
    method forward (line 13) | def forward(self, x):
  class GroupNorm32 (line 17) | class GroupNorm32(nn.GroupNorm):
    method forward (line 19) | def forward(self, x):
  function conv_nd (line 23) | def conv_nd(dims, *args, **kwargs):
  function linear (line 36) | def linear(*args, **kwargs):
  function avg_pool_nd (line 43) | def avg_pool_nd(dims, *args, **kwargs):
  function update_ema (line 56) | def update_ema(target_params, source_params, rate=0.99):
  function zero_module (line 69) | def zero_module(module):
  function scale_module (line 78) | def scale_module(module, scale):
  function mean_flat (line 87) | def mean_flat(tensor):
  function normalization (line 94) | def normalization(channels):
  function timestep_embedding (line 104) | def timestep_embedding(timesteps, dim, max_period=10000):
  function checkpoint (line 123) | def checkpoint(func, inputs, params, flag):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/perlin_noises.py
  function interp (line 13) | def interp(t):
  function perlin (line 17) | def perlin(width, height, scale=10):
  function perlin_ms (line 31) | def perlin_ms(octaves, width, height, grayscale):
  function create_perlin_noise (line 47) | def create_perlin_noise(octaves, width, height, grayscale, side_y, side_x):
  function regen_perlin (line 65) | def regen_perlin(perlin_mode, side_y, side_x, batch_size):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/respace.py
  function space_timesteps (line 11) | def space_timesteps(num_timesteps, section_counts):
  class SpacedDiffusion (line 63) | class SpacedDiffusion(GaussianDiffusion):
    method __init__ (line 72) | def __init__(self, use_timesteps, **kwargs):
    method p_mean_variance (line 88) | def p_mean_variance(self, model, *args, **kwargs):  # pylint: disable=...
    method training_losses (line 91) | def training_losses(self, model, *args, **kwargs):  # pylint: disable=...
    method condition_mean (line 94) | def condition_mean(self, cond_fn, *args, **kwargs):
    method condition_score (line 97) | def condition_score(self, cond_fn, *args, **kwargs):
    method _wrap_model (line 100) | def _wrap_model(self, model):
    method _scale_timesteps (line 105) | def _scale_timesteps(self, t):
  class _WrappedModel (line 110) | class _WrappedModel:
    method __init__ (line 112) | def __init__(self, model, timestep_map, rescale_timesteps, original_nu...
    method __call__ (line 118) | def __call__(self, x, ts, **kwargs):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/script_util.py
  function diffusion_defaults (line 18) | def diffusion_defaults():
  function model_and_diffusion_defaults (line 34) | def model_and_diffusion_defaults():
  function create_model_and_diffusion (line 59) | def create_model_and_diffusion(
  function create_model (line 115) | def create_model(
  function create_gaussian_diffusion (line 172) | def create_gaussian_diffusion(

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/sec_diff.py
  class DiffusionOutput (line 14) | class DiffusionOutput:
  class SkipBlock (line 20) | class SkipBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self, main, skip=None):
    method forward (line 27) | def forward(self, input):
  function append_dims (line 31) | def append_dims(x, n):
  function expand_to_planes (line 35) | def expand_to_planes(x, shape):
  function alpha_sigma_to_t (line 39) | def alpha_sigma_to_t(alpha, sigma):
  function t_to_alpha_sigma (line 43) | def t_to_alpha_sigma(t):
  class SecondaryDiffusionImageNet2 (line 47) | class SecondaryDiffusionImageNet2(nn.Layer):
    method __init__ (line 49) | def __init__(self):
    method forward (line 105) | def forward(self, input, t):
  class FourierFeatures (line 114) | class FourierFeatures(nn.Layer):
    method __init__ (line 116) | def __init__(self, in_features, out_features, std=1.0):
    method forward (line 124) | def forward(self, input):
  class ConvBlock (line 129) | class ConvBlock(nn.Sequential):
    method __init__ (line 131) | def __init__(self, c_in, c_out):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/transforms.py
  class Normalize (line 25) | class Normalize(nn.Layer):
    method __init__ (line 27) | def __init__(self, mean, std):
    method forward (line 32) | def forward(self, tensor: Tensor):
  class InterpolationMode (line 42) | class InterpolationMode(Enum):
  class Grayscale (line 56) | class Grayscale(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_output_channels):
    method forward (line 62) | def forward(self, x):
  class Lambda (line 70) | class Lambda(nn.Layer):
    method __init__ (line 72) | def __init__(self, func):
    method forward (line 76) | def forward(self, x):
  class RandomGrayscale (line 80) | class RandomGrayscale(nn.Layer):
    method __init__ (line 82) | def __init__(self, p):
    method forward (line 87) | def forward(self, x):
  class RandomHorizontalFlip (line 94) | class RandomHorizontalFlip(nn.Layer):
    method __init__ (line 96) | def __init__(self, prob):
    method forward (line 100) | def forward(self, x):
  function _blend (line 107) | def _blend(img1: Tensor, img2: Tensor, ratio: float) -> Tensor:
  function trunc_div (line 113) | def trunc_div(a, b):
  function fmod (line 122) | def fmod(a, b):
  function _rgb2hsv (line 126) | def _rgb2hsv(img: Tensor) -> Tensor:
  function _hsv2rgb (line 165) | def _hsv2rgb(img: Tensor) -> Tensor:
  function adjust_brightness (line 186) | def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
  function adjust_contrast (line 193) | def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
  function adjust_hue (line 209) | def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
  function adjust_saturation (line 221) | def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
  class ColorJitter (line 230) | class ColorJitter(nn.Layer):
    method __init__ (line 232) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):
    method _check_input (line 239) | def _check_input(self, value, name, center=1, bound=(0, float("inf")),...
    method get_params (line 259) | def get_params(
    method forward (line 290) | def forward(self, img):
    method __repr__ (line 313) | def __repr__(self) -> str:
  function _apply_grid_transform (line 322) | def _apply_grid_transform(img: Tensor, grid: Tensor, mode: str, fill: Op...
  function _gen_affine_grid (line 350) | def _gen_affine_grid(
  function affine_impl (line 375) | def affine_impl(img: Tensor,
  function _get_inverse_affine_matrix (line 386) | def _get_inverse_affine_matrix(center: List[float],
  function affine (line 449) | def affine(
  function _interpolation_modes_from_int (line 558) | def _interpolation_modes_from_int(i: int) -> InterpolationMode:
  function _check_sequence_input (line 570) | def _check_sequence_input(x, name, req_sizes):
  function _setup_angle (line 578) | def _setup_angle(x, name, req_sizes=(2, )):
  class RandomAffine (line 589) | class RandomAffine(nn.Layer):
    method __init__ (line 631) | def __init__(
    method get_params (line 696) | def get_params(
    method forward (line 733) | def forward(self, img):
    method __repr__ (line 747) | def __repr__(self) -> str:

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/unet.py
  class AttentionPool2d (line 23) | class AttentionPool2d(nn.Layer):
    method __init__ (line 28) | def __init__(
    method forward (line 46) | def forward(self, x):
  class TimestepBlock (line 58) | class TimestepBlock(nn.Layer):
    method forward (line 64) | def forward(self, x, emb):
  class TimestepEmbedSequential (line 70) | class TimestepEmbedSequential(nn.Sequential, TimestepBlock):
    method forward (line 76) | def forward(self, x, emb):
  class Upsample (line 85) | class Upsample(nn.Layer):
    method __init__ (line 95) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 104) | def forward(self, x):
  class Downsample (line 115) | class Downsample(nn.Layer):
    method __init__ (line 125) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 138) | def forward(self, x):
  class ResBlock (line 143) | class ResBlock(TimestepBlock):
    method __init__ (line 160) | def __init__(
    method forward (line 220) | def forward(self, x, emb):
    method _forward (line 230) | def _forward(self, x, emb):
  class AttentionBlock (line 254) | class AttentionBlock(nn.Layer):
    method __init__ (line 262) | def __init__(
    method forward (line 290) | def forward(self, x):
    method _forward (line 293) | def _forward(self, x):
  function count_flops_attn (line 304) | def count_flops_attn(model, _x, y):
  class QKVAttentionLegacy (line 324) | class QKVAttentionLegacy(nn.Layer):
    method __init__ (line 329) | def __init__(self, n_heads):
    method forward (line 333) | def forward(self, qkv):
    method count_flops (line 353) | def count_flops(model, _x, y):
  class QKVAttention (line 357) | class QKVAttention(nn.Layer):
    method __init__ (line 362) | def __init__(self, n_heads):
    method forward (line 366) | def forward(self, qkv):
    method count_flops (line 389) | def count_flops(model, _x, y):
  class UNetModel (line 393) | class UNetModel(nn.Layer):
    method __init__ (line 424) | def __init__(
    method forward (line 602) | def forward(self, x, timesteps, y=None):
  class SuperResModel (line 632) | class SuperResModel(UNetModel):
    method __init__ (line 639) | def __init__(self, image_size, in_channels, *args, **kwargs):
    method forward (line 642) | def forward(self, x, timesteps, low_res=None, **kwargs):
  class EncoderUNetModel (line 649) | class EncoderUNetModel(nn.Layer):
    method __init__ (line 656) | def __init__(
    method forward (line 812) | def forward(self, x, timesteps):

FILE: modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/runner.py
  function do_run (line 32) | def do_run(args, models) -> 'DocumentArray':
  function _silent_push (line 281) | def _silent_push(da_batches: DocumentArray, name: str) -> None:

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/module.py
  class DiscoDiffusionClip (line 39) | class DiscoDiffusionClip:
    method generate_image (line 41) | def generate_image(self,
    method serving_method (line 174) | def serving_method(self, text_prompts, **kwargs):
    method run_cmd (line 182) | def run_cmd(self, argvs):
    method add_module_config_arg (line 231) | def add_module_config_arg(self):
    method add_module_input_arg (line 392) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/resize_right/interp_methods.py
  function set_framework_dependencies (line 18) | def set_framework_dependencies(x):
  function support_sz (line 30) | def support_sz(sz):
  function cubic (line 40) | def cubic(x):
  function lanczos2 (line 50) | def lanczos2(x):
  function lanczos3 (line 56) | def lanczos3(x):
  function linear (line 62) | def linear(x):
  function box (line 68) | def box(x):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/resize_right/resize_right.py
  class NoneClass (line 9) | class NoneClass:
  function resize (line 33) | def resize(input,
  function get_projected_grid (line 111) | def get_projected_grid(in_sz, out_sz, scale_factor, fw, by_convs, device...
  function get_field_of_view (line 125) | def get_field_of_view(projected_grid, cur_support_sz, fw, eps, device):
  function calc_pad_sz (line 137) | def calc_pad_sz(in_sz, out_sz, field_of_view, projected_grid, scale_fact...
  function get_weights (line 186) | def get_weights(interp_method, projected_grid, field_of_view):
  function apply_weights (line 199) | def apply_weights(input, field_of_view, weights, dim, n_dims, pad_sz, pa...
  function apply_convs (line 232) | def apply_convs(input, scale_factor, in_sz, out_sz, weights, dim, pad_sz...
  function set_scale_and_out_sz (line 260) | def set_scale_and_out_sz(in_shape, out_shape, scale_factors, by_convs, s...
  function apply_antialiasing_if_needed (line 315) | def apply_antialiasing_if_needed(interp_method, support_sz, scale_factor...
  function fw_ceil (line 328) | def fw_ceil(x, fw):
  function fw_floor (line 335) | def fw_floor(x, fw):
  function fw_cat (line 342) | def fw_cat(x, fw):
  function fw_swapaxes (line 349) | def fw_swapaxes(x, ax_1, ax_2, fw):
  function fw_pad (line 364) | def fw_pad(x, fw, pad_sz, pad_mode, dim=0):
  function fw_conv (line 380) | def fw_conv(input, filter, stride):
  function fw_arange (line 392) | def fw_arange(upper_bound, fw, device):
  function fw_empty (line 399) | def fw_empty(shape, fw, device):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/__init__.py
  function create (line 40) | def create(text_prompts: Optional[List[str]] = [
  function create (line 118) | def create(init_document: 'Document') -> 'DocumentArray':
  function create (line 126) | def create(**kwargs) -> 'DocumentArray':

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/config.py
  function load_config (line 19) | def load_config(user_config: Dict, ):
  function print_args_table (line 53) | def print_args_table(cfg):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/helper.py
  function _get_logger (line 19) | def _get_logger():
  function load_clip_models (line 34) | def load_clip_models(enabled: List[str], clip_models: Dict[str, Any] = {}):
  function load_all_models (line 55) | def load_all_models(diffusion_model, use_secondary_model):
  function load_diffusion_model (line 110) | def load_diffusion_model(model_config, diffusion_model, steps):
  function parse_prompt (line 131) | def parse_prompt(prompt):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/gaussian_diffusion.py
  function get_named_beta_schedule (line 17) | def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
  function betas_for_alpha_bar (line 42) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
  class ModelMeanType (line 62) | class ModelMeanType(enum.Enum):
  class ModelVarType (line 72) | class ModelVarType(enum.Enum):
  class LossType (line 86) | class LossType(enum.Enum):
    method is_vb (line 92) | def is_vb(self):
  class GaussianDiffusion (line 96) | class GaussianDiffusion:
    method __init__ (line 113) | def __init__(
    method q_mean_variance (line 156) | def q_mean_variance(self, x_start, t):
    method q_sample (line 169) | def q_sample(self, x_start, t, noise=None):
    method q_posterior_mean_variance (line 187) | def q_posterior_mean_variance(self, x_start, x_t, t):
    method p_mean_variance (line 203) | def p_mean_variance(self, model, x, t, clip_denoised=True, denoised_fn...
    method _predict_xstart_from_eps (line 287) | def _predict_xstart_from_eps(self, x_t, t, eps):
    method _predict_xstart_from_xprev (line 292) | def _predict_xstart_from_xprev(self, x_t, t, xprev):
    method _predict_eps_from_xstart (line 298) | def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
    method _scale_timesteps (line 302) | def _scale_timesteps(self, t):
    method condition_mean (line 307) | def condition_mean(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_mean_with_grad (line 321) | def condition_mean_with_grad(self, cond_fn, p_mean_var, x, t, model_kw...
    method condition_score (line 335) | def condition_score(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_score_with_grad (line 355) | def condition_score_with_grad(self, cond_fn, p_mean_var, x, t, model_k...
    method p_sample (line 375) | def p_sample(
    method p_sample_with_grad (line 419) | def p_sample_with_grad(
    method p_sample_loop (line 467) | def p_sample_loop(
    method p_sample_loop_progressive (line 521) | def p_sample_loop_progressive(
    method ddim_sample (line 586) | def ddim_sample(
    method ddim_sample_with_grad (line 633) | def ddim_sample_with_grad(
    method ddim_reverse_sample (line 686) | def ddim_reverse_sample(
    method ddim_sample_loop (line 719) | def ddim_sample_loop(
    method ddim_sample_loop_progressive (line 761) | def ddim_sample_loop_progressive(
    method plms_sample (line 831) | def plms_sample(
    method plms_sample_loop (line 915) | def plms_sample_loop(
    method plms_sample_loop_progressive (line 957) | def plms_sample_loop_progressive(
    method _vb_terms_bpd (line 1026) | def _vb_terms_bpd(self, model, x_start, x_t, t, clip_denoised=True, mo...
    method training_losses (line 1052) | def training_losses(self, model, x_start, t, model_kwargs=None, noise=...
    method _prior_bpd (line 1126) | def _prior_bpd(self, x_start):
    method calc_bpd_loop (line 1142) | def calc_bpd_loop(self, model, x_start, clip_denoised=True, model_kwar...
  function _extract_into_tensor (line 1201) | def _extract_into_tensor(arr, timesteps, broadcast_shape):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/losses.py
  function normal_kl (line 11) | def normal_kl(mean1, logvar1, mean2, logvar2):
  function approx_standard_normal_cdf (line 33) | def approx_standard_normal_cdf(x):
  function discretized_gaussian_log_likelihood (line 41) | def discretized_gaussian_log_likelihood(x, *, means, log_scales):
  function spherical_dist_loss (line 71) | def spherical_dist_loss(x, y):
  function tv_loss (line 77) | def tv_loss(input):
  function range_loss (line 85) | def range_loss(input):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/make_cutouts.py
  function sinc (line 17) | def sinc(x):
  function lanczos (line 21) | def lanczos(x, a):
  function ramp (line 27) | def ramp(ratio, width):
  class MakeCutouts (line 37) | class MakeCutouts(nn.Layer):
    method __init__ (line 39) | def __init__(self, cut_size, cutn, skip_augs=False):
    method forward (line 56) | def forward(self, input):
  class MakeCutoutsDango (line 81) | class MakeCutoutsDango(nn.Layer):
    method __init__ (line 83) | def __init__(self, cut_size, Overview=4, InnerCrop=0, IC_Size_Pow=0.5,...
    method forward (line 104) | def forward(self, input):
  function resample (line 155) | def resample(input, size, align_corners=True):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/nn.py
  class SiLU (line 11) | class SiLU(nn.Layer):
    method forward (line 13) | def forward(self, x):
  class GroupNorm32 (line 17) | class GroupNorm32(nn.GroupNorm):
    method forward (line 19) | def forward(self, x):
  function conv_nd (line 23) | def conv_nd(dims, *args, **kwargs):
  function linear (line 36) | def linear(*args, **kwargs):
  function avg_pool_nd (line 43) | def avg_pool_nd(dims, *args, **kwargs):
  function update_ema (line 56) | def update_ema(target_params, source_params, rate=0.99):
  function zero_module (line 69) | def zero_module(module):
  function scale_module (line 78) | def scale_module(module, scale):
  function mean_flat (line 87) | def mean_flat(tensor):
  function normalization (line 94) | def normalization(channels):
  function timestep_embedding (line 104) | def timestep_embedding(timesteps, dim, max_period=10000):
  function checkpoint (line 123) | def checkpoint(func, inputs, params, flag):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/perlin_noises.py
  function interp (line 13) | def interp(t):
  function perlin (line 17) | def perlin(width, height, scale=10):
  function perlin_ms (line 31) | def perlin_ms(octaves, width, height, grayscale):
  function create_perlin_noise (line 47) | def create_perlin_noise(octaves, width, height, grayscale, side_y, side_x):
  function regen_perlin (line 65) | def regen_perlin(perlin_mode, side_y, side_x, batch_size):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/respace.py
  function space_timesteps (line 11) | def space_timesteps(num_timesteps, section_counts):
  class SpacedDiffusion (line 63) | class SpacedDiffusion(GaussianDiffusion):
    method __init__ (line 72) | def __init__(self, use_timesteps, **kwargs):
    method p_mean_variance (line 88) | def p_mean_variance(self, model, *args, **kwargs):  # pylint: disable=...
    method training_losses (line 91) | def training_losses(self, model, *args, **kwargs):  # pylint: disable=...
    method condition_mean (line 94) | def condition_mean(self, cond_fn, *args, **kwargs):
    method condition_score (line 97) | def condition_score(self, cond_fn, *args, **kwargs):
    method _wrap_model (line 100) | def _wrap_model(self, model):
    method _scale_timesteps (line 105) | def _scale_timesteps(self, t):
  class _WrappedModel (line 110) | class _WrappedModel:
    method __init__ (line 112) | def __init__(self, model, timestep_map, rescale_timesteps, original_nu...
    method __call__ (line 118) | def __call__(self, x, ts, **kwargs):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/script_util.py
  function diffusion_defaults (line 18) | def diffusion_defaults():
  function model_and_diffusion_defaults (line 34) | def model_and_diffusion_defaults():
  function create_model_and_diffusion (line 59) | def create_model_and_diffusion(
  function create_model (line 115) | def create_model(
  function create_gaussian_diffusion (line 172) | def create_gaussian_diffusion(

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/sec_diff.py
  class DiffusionOutput (line 14) | class DiffusionOutput:
  class SkipBlock (line 20) | class SkipBlock(nn.Layer):
    method __init__ (line 22) | def __init__(self, main, skip=None):
    method forward (line 27) | def forward(self, input):
  function append_dims (line 31) | def append_dims(x, n):
  function expand_to_planes (line 35) | def expand_to_planes(x, shape):
  function alpha_sigma_to_t (line 39) | def alpha_sigma_to_t(alpha, sigma):
  function t_to_alpha_sigma (line 43) | def t_to_alpha_sigma(t):
  class SecondaryDiffusionImageNet2 (line 47) | class SecondaryDiffusionImageNet2(nn.Layer):
    method __init__ (line 49) | def __init__(self):
    method forward (line 105) | def forward(self, input, t):
  class FourierFeatures (line 114) | class FourierFeatures(nn.Layer):
    method __init__ (line 116) | def __init__(self, in_features, out_features, std=1.0):
    method forward (line 124) | def forward(self, input):
  class ConvBlock (line 129) | class ConvBlock(nn.Sequential):
    method __init__ (line 131) | def __init__(self, c_in, c_out):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/transforms.py
  class Normalize (line 25) | class Normalize(nn.Layer):
    method __init__ (line 27) | def __init__(self, mean, std):
    method forward (line 32) | def forward(self, tensor: Tensor):
  class InterpolationMode (line 42) | class InterpolationMode(Enum):
  class Grayscale (line 56) | class Grayscale(nn.Layer):
    method __init__ (line 58) | def __init__(self, num_output_channels):
    method forward (line 62) | def forward(self, x):
  class Lambda (line 70) | class Lambda(nn.Layer):
    method __init__ (line 72) | def __init__(self, func):
    method forward (line 76) | def forward(self, x):
  class RandomGrayscale (line 80) | class RandomGrayscale(nn.Layer):
    method __init__ (line 82) | def __init__(self, p):
    method forward (line 87) | def forward(self, x):
  class RandomHorizontalFlip (line 94) | class RandomHorizontalFlip(nn.Layer):
    method __init__ (line 96) | def __init__(self, prob):
    method forward (line 100) | def forward(self, x):
  function _blend (line 107) | def _blend(img1: Tensor, img2: Tensor, ratio: float) -> Tensor:
  function trunc_div (line 113) | def trunc_div(a, b):
  function fmod (line 122) | def fmod(a, b):
  function _rgb2hsv (line 126) | def _rgb2hsv(img: Tensor) -> Tensor:
  function _hsv2rgb (line 165) | def _hsv2rgb(img: Tensor) -> Tensor:
  function adjust_brightness (line 186) | def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
  function adjust_contrast (line 193) | def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
  function adjust_hue (line 209) | def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
  function adjust_saturation (line 221) | def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
  class ColorJitter (line 230) | class ColorJitter(nn.Layer):
    method __init__ (line 232) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):
    method _check_input (line 239) | def _check_input(self, value, name, center=1, bound=(0, float("inf")),...
    method get_params (line 259) | def get_params(
    method forward (line 290) | def forward(self, img):
    method __repr__ (line 313) | def __repr__(self) -> str:
  function _apply_grid_transform (line 322) | def _apply_grid_transform(img: Tensor, grid: Tensor, mode: str, fill: Op...
  function _gen_affine_grid (line 350) | def _gen_affine_grid(
  function affine_impl (line 375) | def affine_impl(img: Tensor,
  function _get_inverse_affine_matrix (line 386) | def _get_inverse_affine_matrix(center: List[float],
  function affine (line 449) | def affine(
  function _interpolation_modes_from_int (line 558) | def _interpolation_modes_from_int(i: int) -> InterpolationMode:
  function _check_sequence_input (line 570) | def _check_sequence_input(x, name, req_sizes):
  function _setup_angle (line 578) | def _setup_angle(x, name, req_sizes=(2, )):
  class RandomAffine (line 589) | class RandomAffine(nn.Layer):
    method __init__ (line 631) | def __init__(
    method get_params (line 696) | def get_params(
    method forward (line 733) | def forward(self, img):
    method __repr__ (line 747) | def __repr__(self) -> str:

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/model/unet.py
  class AttentionPool2d (line 23) | class AttentionPool2d(nn.Layer):
    method __init__ (line 28) | def __init__(
    method forward (line 46) | def forward(self, x):
  class TimestepBlock (line 58) | class TimestepBlock(nn.Layer):
    method forward (line 64) | def forward(self, x, emb):
  class TimestepEmbedSequential (line 70) | class TimestepEmbedSequential(nn.Sequential, TimestepBlock):
    method forward (line 76) | def forward(self, x, emb):
  class Upsample (line 85) | class Upsample(nn.Layer):
    method __init__ (line 95) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 104) | def forward(self, x):
  class Downsample (line 115) | class Downsample(nn.Layer):
    method __init__ (line 125) | def __init__(self, channels, use_conv, dims=2, out_channels=None):
    method forward (line 138) | def forward(self, x):
  class ResBlock (line 143) | class ResBlock(TimestepBlock):
    method __init__ (line 160) | def __init__(
    method forward (line 220) | def forward(self, x, emb):
    method _forward (line 230) | def _forward(self, x, emb):
  class AttentionBlock (line 254) | class AttentionBlock(nn.Layer):
    method __init__ (line 262) | def __init__(
    method forward (line 290) | def forward(self, x):
    method _forward (line 293) | def _forward(self, x):
  function count_flops_attn (line 304) | def count_flops_attn(model, _x, y):
  class QKVAttentionLegacy (line 324) | class QKVAttentionLegacy(nn.Layer):
    method __init__ (line 329) | def __init__(self, n_heads):
    method forward (line 333) | def forward(self, qkv):
    method count_flops (line 353) | def count_flops(model, _x, y):
  class QKVAttention (line 357) | class QKVAttention(nn.Layer):
    method __init__ (line 362) | def __init__(self, n_heads):
    method forward (line 366) | def forward(self, qkv):
    method count_flops (line 389) | def count_flops(model, _x, y):
  class UNetModel (line 393) | class UNetModel(nn.Layer):
    method __init__ (line 424) | def __init__(
    method forward (line 602) | def forward(self, x, timesteps, y=None):
  class SuperResModel (line 632) | class SuperResModel(UNetModel):
    method __init__ (line 639) | def __init__(self, image_size, in_channels, *args, **kwargs):
    method forward (line 642) | def forward(self, x, timesteps, low_res=None, **kwargs):
  class EncoderUNetModel (line 649) | class EncoderUNetModel(nn.Layer):
    method __init__ (line 656) | def __init__(
    method forward (line 812) | def forward(self, x, timesteps):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/reverse_diffusion/runner.py
  function do_run (line 32) | def do_run(args, models) -> 'DocumentArray':
  function _silent_push (line 281) | def _silent_push(da_batches: DocumentArray, name: str) -> None:

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/clip_vision_transformer.py
  class QuickGELU (line 37) | class QuickGELU(Layer):
    method forward (line 40) | def forward(self, x):
  function to_2tuple (line 44) | def to_2tuple(x):
  function drop_path (line 48) | def drop_path(x, drop_prob=0., training=False):
  class DropPath (line 63) | class DropPath(nn.Layer):
    method __init__ (line 67) | def __init__(self, drop_prob=None):
    method forward (line 71) | def forward(self, x):
  class Identity (line 75) | class Identity(nn.Layer):
    method __init__ (line 77) | def __init__(self):
    method forward (line 80) | def forward(self, input):
  class Mlp (line 84) | class Mlp(nn.Layer):
    method __init__ (line 86) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 95) | def forward(self, x):
  class Attention (line 104) | class Attention(nn.Layer):
    method __init__ (line 106) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method forward (line 117) | def forward(self, x):
  class Block (line 133) | class Block(nn.Layer):
    method __init__ (line 135) | def __init__(self,
    method forward (line 161) | def forward(self, x):
  class PatchEmbed (line 167) | class PatchEmbed(nn.Layer):
    method __init__ (line 171) | def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=...
    method forward (line 183) | def forward(self, x):
  class VisionTransformer (line 192) | class VisionTransformer(nn.Layer):
    method __init__ (line 196) | def __init__(self,
    method _init_weights (line 256) | def _init_weights(self, m):
    method forward_features (line 265) | def forward_features(self, x):
    method forward (line 282) | def forward(self, x):
  function ViT_small_patch16_224 (line 287) | def ViT_small_patch16_224(**kwargs):
  function ViT_base_patch16_224 (line 298) | def ViT_base_patch16_224(**kwargs):
  function ViT_base_patch16_384 (line 310) | def ViT_base_patch16_384(**kwargs):
  function ViT_base_patch32_384 (line 323) | def ViT_base_patch32_384(**kwargs):
  function ViT_base_patch32_224 (line 336) | def ViT_base_patch32_224(**kwargs):
  function ViT_large_patch16_224 (line 349) | def ViT_large_patch16_224(**kwargs):
  function ViT_large_patch16_384 (line 361) | def ViT_large_patch16_384(**kwargs):
  function ViT_large_patch14_224 (line 374) | def ViT_large_patch14_224(**kwargs):
  function ViT_large_patch32_384 (line 386) | def ViT_large_patch32_384(**kwargs):
  function ViT_huge_patch16_224 (line 399) | def ViT_huge_patch16_224(**kwargs):
  function ViT_huge_patch32_384 (line 404) | def ViT_huge_patch32_384(**kwargs):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/droppath.py
  class DropPath (line 21) | class DropPath(nn.Layer):
    method __init__ (line 24) | def __init__(self, drop_prob=None):
    method drop_path (line 28) | def drop_path(self, inputs):
    method forward (line 48) | def forward(self, inputs):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/efficientnet.py
  function load_dygraph_pretrain (line 54) | def load_dygraph_pretrain(model, path=None):
  function efficientnet_params (line 63) | def efficientnet_params(model_name):
  function efficientnet (line 78) | def efficientnet(width_coefficient=None, depth_coefficient=None, dropout...
  function get_model_params (line 103) | def get_model_params(model_name, override_params):
  function round_filters (line 115) | def round_filters(filters, global_params):
  function round_repeats (line 130) | def round_repeats(repeats, global_params):
  class BlockDecoder (line 138) | class BlockDecoder(object):
    method _decode_block_string (line 144) | def _decode_block_string(block_string):
    method _encode_block_string (line 171) | def _encode_block_string(block):
    method decode (line 188) | def decode(string_list):
    method encode (line 202) | def encode(blocks_args):
  function initial_type (line 214) | def initial_type(name, use_bias=False):
  function init_batch_norm_layer (line 223) | def init_batch_norm_layer(name="batch_norm"):
  function init_fc_layer (line 229) | def init_fc_layer(name="fc"):
  function cal_padding (line 235) | def cal_padding(img_size, stride, filter_size, dilation=1):
  function _drop_connect (line 269) | def _drop_connect(inputs, prob, is_test):
  class Conv2ds (line 281) | class Conv2ds(nn.Layer):
    method __init__ (line 283) | def __init__(self,
    method forward (line 348) | def forward(self, inputs):
  class ConvBNLayer (line 360) | class ConvBNLayer(nn.Layer):
    method __init__ (line 362) | def __init__(self,
    method forward (line 403) | def forward(self, inputs):
  class ExpandConvNorm (line 415) | class ExpandConvNorm(nn.Layer):
    method __init__ (line 417) | def __init__(self, input_channels, block_args, padding_type, name=None...
    method forward (line 435) | def forward(self, inputs):
  class DepthwiseConvNorm (line 442) | class DepthwiseConvNorm(nn.Layer):
    method __init__ (line 444) | def __init__(self, input_channels, block_args, padding_type, name=None...
    method forward (line 465) | def forward(self, inputs):
  class ProjectConvNorm (line 469) | class ProjectConvNorm(nn.Layer):
    method __init__ (line 471) | def __init__(self, input_channels, block_args, padding_type, name=None...
    method forward (line 487) | def forward(self, inputs):
  class SEBlock (line 491) | class SEBlock(nn.Layer):
    method __init__ (line 493) | def __init__(self,
    method forward (line 522) | def forward(self, inputs):
  class MbConvBlock (line 530) | class MbConvBlock(nn.Layer):
    method __init__ (line 532) | def __init__(self,
    method forward (line 582) | def forward(self, inputs):
  class ConvStemNorm (line 601) | class ConvStemNorm(nn.Layer):
    method __init__ (line 603) | def __init__(self, input_channels, padding_type, _global_params, name=...
    method forward (line 620) | def forward(self, inputs):
  class ExtractFeatures (line 624) | class ExtractFeatures(nn.Layer):
    method __init__ (line 626) | def __init__(self, input_channels, _block_args, _global_params, paddin...
    method forward (line 689) | def forward(self, inputs):
  class EfficientNet (line 701) | class EfficientNet(nn.Layer):
    method __init__ (line 703) | def __init__(self, name="b0", padding_type="SAME", override_params=Non...
    method forward (line 756) | def forward(self, inputs):
  function _load_pretrained (line 771) | def _load_pretrained(pretrained, model, model_url, use_ssld=False):
  function EfficientNetB0_small (line 780) | def EfficientNetB0_small(padding_type='DYNAMIC',
  function EfficientNetB0 (line 791) | def EfficientNetB0(padding_type='SAME', override_params=None, use_se=Tru...
  function EfficientNetB1 (line 797) | def EfficientNetB1(padding_type='SAME', override_params=None, use_se=Tru...
  function EfficientNetB2 (line 803) | def EfficientNetB2(padding_type='SAME', override_params=None, use_se=Tru...
  function EfficientNetB3 (line 809) | def EfficientNetB3(padding_type='SAME', override_params=None, use_se=Tru...
  function EfficientNetB4 (line 815) | def EfficientNetB4(padding_type='SAME', override_params=None, use_se=Tru...
  function EfficientNetB5 (line 821) | def EfficientNetB5(padding_type='SAME', override_params=None, use_se=Tru...
  function EfficientNetB6 (line 827) | def EfficientNetB6(padding_type='SAME', override_params=None, use_se=Tru...
  function EfficientNetB7 (line 833) | def EfficientNetB7(padding_type='SAME', override_params=None, use_se=Tru...

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/ernie2.py
  class ErnieModel (line 19) | class ErnieModel(nn.Layer):
    method __init__ (line 22) | def __init__(self, cfg, name=''):
    method get_checkpoints (line 86) | def get_checkpoints(self):
    method eval (line 92) | def eval(self):
    method train (line 101) | def train(self):
    method forward (line 110) | def forward(self,
  class ErnieEncoderStack (line 207) | class ErnieEncoderStack(nn.Layer):
    method __init__ (line 210) | def __init__(self, cfg, name=None):
    method forward (line 215) | def forward(self, inputs, attn_bias=None, past_cache=None, key_tag=None):
  class ErnieBlock (line 238) | class ErnieBlock(nn.Layer):
    method __init__ (line 241) | def __init__(self, cfg, name=None):
    method forward (line 251) | def forward(self, inputs, attn_bias=None, past_cache=None, key_tag=None):
  class AttentionLayer (line 266) | class AttentionLayer(nn.Layer):
    method __init__ (line 269) | def __init__(self, cfg, name=None):
    method forward (line 290) | def forward(self, queries, keys, values, attn_bias, past_cache, key_ta...
  class PositionWiseFeedForwardLayer (line 331) | class PositionWiseFeedForwardLayer(nn.Layer):
    method __init__ (line 334) | def __init__(self, cfg, name=None):
    method forward (line 346) | def forward(self, inputs):
  function _build_linear (line 354) | def _build_linear(n_in, n_out, name, init):
  function _build_ln (line 363) | def _build_ln(n_in, name):
  function append_name (line 373) | def append_name(name, postfix):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/ernie_modeling.py
  function _get_rel_pos_bias (line 29) | def _get_rel_pos_bias(seq_len, max_len=128, num_buckets=32, bidirectiona...
  function _build_linear (line 61) | def _build_linear(n_in, n_out, name, init):
  function _build_ln (line 70) | def _build_ln(n_in, name):
  function append_name (line 80) | def append_name(name, postfix):
  class AttentionLayer (line 90) | class AttentionLayer(nn.Layer):
    method __init__ (line 92) | def __init__(self, cfg, name=None):
    method forward (line 108) | def forward(self, queries, keys, values, attn_bias, past_cache):
  class PositionwiseFeedForwardLayer (line 142) | class PositionwiseFeedForwardLayer(nn.Layer):
    method __init__ (line 144) | def __init__(self, cfg, name=None):
    method forward (line 160) | def forward(self, inputs):
  class ErnieBlock (line 167) | class ErnieBlock(nn.Layer):
    method __init__ (line 169) | def __init__(self, cfg, name=None):
    method forward (line 179) | def forward(self, inputs, attn_bias=None, past_cache=None):
  class ErnieEncoderStack (line 192) | class ErnieEncoderStack(nn.Layer):
    method __init__ (line 194) | def __init__(self, cfg, name=None):
    method forward (line 199) | def forward(self, inputs, attn_bias=None, past_cache=None):
  class PretrainedModel (line 219) | class PretrainedModel(object):
    method from_pretrained (line 231) | def from_pretrained(cls, pretrain_dir_or_url, force_download=False, **...
  class ErnieModel (line 270) | class ErnieModel(nn.Layer, PretrainedModel):
    method __init__ (line 272) | def __init__(self, cfg, name=None):
    method eval (line 325) | def eval(self):
    method train (line 333) | def train(self):
    method forward (line 341) | def forward(self,
  class ErnieModelForSequenceClassification (line 424) | class ErnieModelForSequenceClassification(ErnieModel):
    method __init__ (line 429) | def __init__(self, cfg, name=None):
    method forward (line 440) | def forward(self, *args, **kwargs):
  class ErnieModelForTokenClassification (line 466) | class ErnieModelForTokenClassification(ErnieModel):
    method __init__ (line 471) | def __init__(self, cfg, name=None):
    method forward (line 482) | def forward(self, *args, **kwargs):
  class ErnieModelForQuestionAnswering (line 517) | class ErnieModelForQuestionAnswering(ErnieModel):
    method __init__ (line 522) | def __init__(self, cfg, name=None):
    method forward (line 533) | def forward(self, *args, **kwargs):
  class NSPHead (line 569) | class NSPHead(nn.Layer):
    method __init__ (line 571) | def __init__(self, cfg, name=None):
    method forward (line 576) | def forward(self, inputs, labels):
  class ErnieModelForPretraining (line 598) | class ErnieModelForPretraining(ErnieModel):
    method __init__ (line 603) | def __init__(self, cfg, name=None):
    method forward (line 628) | def forward(self, *args, **kwargs):
  class ErnieModelForGeneration (line 666) | class ErnieModelForGeneration(ErnieModel):
    method __init__ (line 677) | def __init__(self, cfg, name=None):
    method forward (line 703) | def forward(self, *args, **kwargs):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/ernie_tokenizer.py
  function _wordpiece (line 33) | def _wordpiece(token, vocab, unk_token, prefix='##', sentencepiece_prefi...
  class ErnieTokenizer (line 68) | class ErnieTokenizer(object):
    method from_pretrained (line 82) | def from_pretrained(cls, pretrain_dir_or_url, force_download=False, **...
    method __init__ (line 99) | def __init__(self,
    method tokenize (line 134) | def tokenize(self, text):
    method convert_tokens_to_ids (line 158) | def convert_tokens_to_ids(self, tokens):
    method truncate (line 161) | def truncate(self, id1, id2, seqlen):
    method build_for_ernie (line 171) | def build_for_ernie(self, text_id, pair_id=[]):
    method encode (line 183) | def encode(self, text, pair=None, truncate_to=None):
  class ErnieTinyTokenizer (line 197) | class ErnieTinyTokenizer(ErnieTokenizer):
    method from_pretrained (line 202) | def from_pretrained(cls, pretrain_dir_or_url, force_download=False, **...
    method __init__ (line 222) | def __init__(self, vocab, sp_model_path, **kwargs):
    method cut (line 231) | def cut(self, sentence):
    method tokenize (line 234) | def tokenize(self, text):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/file_utils.py
  function _fetch_from_remote (line 21) | def _fetch_from_remote(url, force_download=False, cached_dir='~/.paddle-...
  function add_docstring (line 76) | def add_docstring(doc):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/multimodal.py
  class MultiModalModel (line 20) | class MultiModalModel(nn.Layer):
    method __init__ (line 22) | def __init__(self, image_model=None, text_model=None, args=None):
    method encode_text (line 27) | def encode_text(self, input_ids, pos_ids=None):
    method encode_image (line 31) | def encode_image(self, img_word):
    method forward (line 35) | def forward(self, img_word=None, input_ids=None, pos_ids=None):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/paddle_vision_transformer.py
  class Identity (line 24) | class Identity(nn.Layer):
    method __init__ (line 30) | def __init__(self):
    method forward (line 33) | def forward(self, x):
  class PatchEmbedding (line 37) | class PatchEmbedding(nn.Layer):
    method __init__ (line 47) | def __init__(self, image_size=224, patch_size=16, in_channels=3, embed...
    method forward (line 67) | def forward(self, x):
  class Attention (line 79) | class Attention(nn.Layer):
    method __init__ (line 95) | def __init__(self, embed_dim, num_heads, attn_head_size=None, qkv_bias...
    method _init_weights (line 139) | def _init_weights(self):
    method transpose_multihead (line 144) | def transpose_multihead(self, x):
    method forward (line 150) | def forward(self, x):
  class Mlp (line 169) | class Mlp(nn.Layer):
    method __init__ (line 181) | def __init__(self, embed_dim, mlp_ratio, dropout=0.):
    method _init_weights (line 192) | def _init_weights(self):
    method forward (line 197) | def forward(self, x):
  class EncoderLayer (line 206) | class EncoderLayer(nn.Layer):
    method __init__ (line 217) | def __init__(self,
    method _init_weights (line 238) | def _init_weights(self):
    method forward (line 243) | def forward(self, x):
  class Encoder (line 259) | class Encoder(nn.Layer):
    method __init__ (line 267) | def __init__(self,
    method _init_weights (line 296) | def _init_weights(self):
    method forward (line 301) | def forward(self, x):
  class VisualTransformer (line 308) | class VisualTransformer(nn.Layer):
    method __init__ (line 328) | def __init__(self,
    method _init_weights (line 366) | def _init_weights(self):
    method forward (line 371) | def forward(self, x):
  function build_vit (line 380) | def build_vit(config):
  function ViT_large_patch16_384 (line 399) | def ViT_large_patch16_384(**kwargs):
  function ViT_large_patch16_224 (line 415) | def ViT_large_patch16_224(**kwargs):
  function ViT_base_patch16_224 (line 431) | def ViT_base_patch16_224(**kwargs):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/resnet.py
  class BasicBlock (line 35) | class BasicBlock(nn.Layer):
    method __init__ (line 38) | def __init__(self,
    method forward (line 62) | def forward(self, x):
  class BottleneckBlock (line 81) | class BottleneckBlock(nn.Layer):
    method __init__ (line 85) | def __init__(self,
    method forward (line 118) | def forward(self, x):
  class ResNet (line 141) | class ResNet(nn.Layer):
    method __init__ (line 173) | def __init__(self, block, depth=50, width=64, num_classes=1000, with_p...
    method _make_layer (line 200) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method forward (line 224) | def forward(self, x):
  function _resnet (line 244) | def _resnet(arch, Block, depth, pretrained, **kwargs):
  function resnet18 (line 257) | def resnet18(pretrained=False, **kwargs):
  function resnet34 (line 284) | def resnet34(pretrained=False, **kwargs):
  function resnet50 (line 311) | def resnet50(pretrained=False, **kwargs):
  function resnet101 (line 338) | def resnet101(pretrained=False, **kwargs):
  function resnet152 (line 365) | def resnet152(pretrained=False, **kwargs):
  function wide_resnet50_2 (line 392) | def wide_resnet50_2(pretrained=False, **kwargs):
  function wide_resnet101_2 (line 420) | def wide_resnet101_2(pretrained=False, **kwargs):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/utils/tokenizer.py
  function convert_to_unicode (line 27) | def convert_to_unicode(text):
  function load_vocab (line 47) | def load_vocab(vocab_file):
  function convert_by_vocab (line 62) | def convert_by_vocab(vocab, items):
  function convert_tokens_to_ids_include_unk (line 70) | def convert_tokens_to_ids_include_unk(vocab, tokens, unk_token="[UNK]"):
  function convert_tokens_to_ids (line 80) | def convert_tokens_to_ids(vocab, tokens):
  function convert_ids_to_tokens (line 84) | def convert_ids_to_tokens(inv_vocab, ids):
  function whitespace_tokenize (line 88) | def whitespace_tokenize(text):
  class FullTokenizer (line 97) | class FullTokenizer(object):
    method __init__ (line 100) | def __init__(self, vocab_file, do_lower_case=True):
    method tokenize (line 106) | def tokenize(self, text):
    method convert_tokens_to_ids (line 114) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 117) | def convert_ids_to_tokens(self, ids):
  class CharTokenizer (line 121) | class CharTokenizer(object):
    method __init__ (line 124) | def __init__(self, vocab_file, do_lower_case=True):
    method tokenize (line 129) | def tokenize(self, text):
    method convert_tokens_to_ids (line 136) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 139) | def convert_ids_to_tokens(self, ids):
  class BasicTokenizer (line 143) | class BasicTokenizer(object):
    method __init__ (line 146) | def __init__(self, do_lower_case=True):
    method tokenize (line 154) | def tokenize(self, text):
    method _run_strip_accents (line 178) | def _run_strip_accents(self, text):
    method _run_split_on_punc (line 189) | def _run_split_on_punc(self, text):
    method _tokenize_chinese_chars (line 209) | def _tokenize_chinese_chars(self, text):
    method _is_chinese_char (line 222) | def _is_chinese_char(self, cp):
    method _clean_text (line 243) | def _clean_text(self, text):
  class WordpieceTokenizer (line 257) | class WordpieceTokenizer(object):
    method __init__ (line 260) | def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=...
    method tokenize (line 265) | def tokenize(self, text):
  function _is_whitespace (line 319) | def _is_whitespace(char):
  function _is_control (line 331) | def _is_control(char):
  function _is_punctuation (line 343) | def _is_punctuation(char):

FILE: modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/utils/utils.py
  function tokenize (line 26) | def tokenize(texts: Union[str, List[str]], context_length: int = 64):
  function build_model (line 57) | def build_model(name='vit_b_16x'):
  function build_vit_b_16x_model (line 64) | def build_vit_b_16x_model():

FILE: modules/image/text_to_image/ernie_vilg/module.py
  class ErnieVilG (line 25) | class ErnieVilG:
    method __init__ (line 27) | def __init__(self, ak=None, sk=None):
    method _apply_token (line 37) | def _apply_token(self, ak, sk):
    method generate_image (line 59) | def generate_image(self,
    method run_cmd (line 218) | def run_cmd(self, argvs):
    method serving_method (line 240) | def serving_method(self, text_prompts, **kwargs):
    method add_module_input_arg (line 253) | def add_module_input_arg(self):
    method create_gradio_app (line 272) | def create_gradio_app(self):

FILE: modules/image/text_to_image/ernie_vilg/test.py
  class TestHubModule (line 7) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 10) | def setUpClass(cls) -> None:
    method tearDownClass (line 14) | def tearDownClass(cls) -> None:
    method test_generate_image (line 17) | def test_generate_image(self):

FILE: modules/image/text_to_image/stable_diffusion/clip/clip/layers.py
  function multi_head_attention_forward (line 12) | def multi_head_attention_forward(x: Tensor,
  class MultiHeadAttention (line 47) | class MultiHeadAttention(nn.Layer):  # without attention mask
    method __init__ (line 49) | def __init__(self, emb_dim: int, num_heads: int):
    method forward (line 61) | def forward(self, x, attn_mask=None):  # x is in shape[max_len,batch_s...
  class Identity (line 74) | class Identity(nn.Layer):
    method __init__ (line 76) | def __init__(self):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 83) | class Bottleneck(nn.Layer):
    method __init__ (line 86) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 111) | def forward(self, x):
  class AttentionPool2d (line 127) | class AttentionPool2d(nn.Layer):
    method __init__ (line 129) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 143) | def forward(self, x):
  class QuickGELU (line 155) | class QuickGELU(nn.Layer):
    method forward (line 157) | def forward(self, x):
  class ResidualAttentionBlock (line 161) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 163) | def __init__(self, d_model: int, n_head: int, attn_mask=None):
    method attention (line 173) | def attention(self, x):
    method forward (line 178) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion/clip/clip/model.py
  class ModifiedResNet (line 15) | class ModifiedResNet(nn.Layer):
    method __init__ (line 23) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 48) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 57) | def forward(self, x):
  class Transformer (line 76) | class Transformer(nn.Layer):
    method __init__ (line 78) | def __init__(self, width: int, layers: int, heads: int, attn_mask=None):
    method forward (line 84) | def forward(self, x):
  class VisualTransformer (line 88) | class VisualTransformer(nn.Layer):
    method __init__ (line 90) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 113) | def forward(self, x):
  class TextTransformer (line 132) | class TextTransformer(nn.Layer):
    method __init__ (line 134) | def __init__(self, context_length: int, vocab_size: int, transformer_w...
    method build_attention_mask (line 148) | def build_attention_mask(self):
    method forward (line 159) | def forward(self, text):
  class CLIP (line 169) | class CLIP(nn.Layer):
    method __init__ (line 171) | def __init__(
    method build_attention_mask (line 217) | def build_attention_mask(self):
    method encode_image (line 228) | def encode_image(self, image):
    method encode_text (line 231) | def encode_text(self, text):
    method forward (line 245) | def forward(self, image, text):

FILE: modules/image/text_to_image/stable_diffusion/clip/clip/simple_tokenizer.py
  function default_bpe (line 11) | def default_bpe():
  function bytes_to_unicode (line 16) | def bytes_to_unicode():
  function get_pairs (line 38) | def get_pairs(word):
  function basic_clean (line 50) | def basic_clean(text):
  function whitespace_clean (line 56) | def whitespace_clean(text):
  class SimpleTokenizer (line 62) | class SimpleTokenizer(object):
    method __init__ (line 64) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: modules/image/text_to_image/stable_diffusion/clip/clip/utils.py
  function tokenize (line 35) | def tokenize(texts: Union[str, List[str]], context_length: int = 77):
  function build_model (line 67) | def build_model(name='VITL14'):
  function build_vitl14_language_model (line 82) | def build_vitl14_language_model():

FILE: modules/image/text_to_image/stable_diffusion/diffusers/configuration_utils.py
  class ConfigMixin (line 38) | class ConfigMixin:
    method register_to_config (line 47) | def register_to_config(self, **kwargs):
    method save_config (line 69) | def save_config(self, save_directory: Union[str, os.PathLike], push_to...
    method from_config (line 92) | def from_config(cls, pretrained_model_name_or_path: Union[str, os.Path...
    method get_config_dict (line 105) | def get_config_dict(cls, pretrained_model_name_or_path: Union[str, os....
    method extract_init_dict (line 180) | def extract_init_dict(cls, config_dict, **kwargs):
    method _dict_from_json_file (line 208) | def _dict_from_json_file(cls, json_file: Union[str, os.PathLike]):
    method __repr__ (line 213) | def __repr__(self):
    method config (line 217) | def config(self) -> Dict[str, Any]:
    method to_json_string (line 220) | def to_json_string(self) -> str:
    method to_json_file (line 230) | def to_json_file(self, json_file_path: Union[str, os.PathLike]):
  class FrozenDict (line 242) | class FrozenDict(OrderedDict):
    method __init__ (line 244) | def __init__(self, *args, **kwargs):
    method __delitem__ (line 252) | def __delitem__(self, *args, **kwargs):
    method setdefault (line 255) | def setdefault(self, *args, **kwargs):
    method pop (line 258) | def pop(self, *args, **kwargs):
    method update (line 261) | def update(self, *args, **kwargs):
    method __setattr__ (line 264) | def __setattr__(self, name, value):
    method __setitem__ (line 269) | def __setitem__(self, name, value):
  function register_to_config (line 275) | def register_to_config(init):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/models/attention.py
  function finfo (line 23) | def finfo(dtype):
  class AttentionBlockNew (line 35) | class AttentionBlockNew(nn.Layer):
    method __init__ (line 43) | def __init__(
    method transpose_for_scores (line 66) | def transpose_for_scores(self, projection: paddle.Tensor) -> paddle.Te...
    method forward (line 72) | def forward(self, hidden_states):
    method set_weight (line 113) | def set_weight(self, attn_layer):
  class SpatialTransformer (line 162) | class SpatialTransformer(nn.Layer):
    method __init__ (line 168) | def __init__(self, in_channels, n_heads, d_head, depth=1, dropout=0.0,...
    method forward (line 185) | def forward(self, x, context=None):
    method set_weight (line 198) | def set_weight(self, layer):
  class BasicTransformerBlock (line 205) | class BasicTransformerBlock(nn.Layer):
    method __init__ (line 207) | def __init__(self, dim, n_heads, d_head, dropout=0.0, context_dim=None...
    method forward (line 222) | def forward(self, x, context=None):
  class CrossAttention (line 229) | class CrossAttention(nn.Layer):
    method __init__ (line 231) | def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, ...
    method reshape_heads_to_batch_dim (line 245) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 252) | def reshape_batch_dim_to_heads(self, tensor):
    method forward (line 259) | def forward(self, x, context=None, mask=None):
  class FeedForward (line 289) | class FeedForward(nn.Layer):
    method __init__ (line 291) | def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.0):
    method forward (line 299) | def forward(self, x):
  class GEGLU (line 304) | class GEGLU(nn.Layer):
    method __init__ (line 306) | def __init__(self, dim_in, dim_out):
    method forward (line 310) | def forward(self, x):
  class NIN (line 316) | class NIN(nn.Layer):
    method __init__ (line 318) | def __init__(self, in_dim, num_units, init_scale=0.1):
  function exists (line 328) | def exists(val):
  function default (line 332) | def default(val, d):
  class AttentionBlock (line 339) | class AttentionBlock(nn.Layer):
    method __init__ (line 347) | def __init__(
    method set_weights (line 403) | def set_weights(self, layer):
    method forward (line 430) | def forward(self, x, encoder_out=None):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/models/embeddings.py
  function get_timestep_embedding (line 22) | def get_timestep_embedding(timesteps,
  class TimestepEmbedding (line 61) | class TimestepEmbedding(nn.Layer):
    method __init__ (line 63) | def __init__(self, channel, time_embed_dim, act_fn="silu"):
    method forward (line 72) | def forward(self, sample):
  class Timesteps (line 82) | class Timesteps(nn.Layer):
    method __init__ (line 84) | def __init__(self, num_channels, flip_sin_to_cos, downscale_freq_shift):
    method forward (line 90) | def forward(self, timesteps):
  class GaussianFourierProjection (line 100) | class GaussianFourierProjection(nn.Layer):
    method __init__ (line 103) | def __init__(self, embedding_size=256, scale=1.0):
    method forward (line 112) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/models/resnet.py
  function pad_new (line 22) | def pad_new(x, pad, mode="constant", value=0):
  class Upsample2D (line 54) | class Upsample2D(nn.Layer):
    method __init__ (line 63) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 83) | def forward(self, x):
  class Downsample2D (line 100) | class Downsample2D(nn.Layer):
    method __init__ (line 109) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 133) | def forward(self, x):
  class FirUpsample2D (line 145) | class FirUpsample2D(nn.Layer):
    method __init__ (line 147) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _upsample_2d (line 156) | def _upsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 223) | def forward(self, x):
  class FirDownsample2D (line 233) | class FirDownsample2D(nn.Layer):
    method __init__ (line 235) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _downsample_2d (line 244) | def _downsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 286) | def forward(self, x):
  class ResnetBlock (line 296) | class ResnetBlock(nn.Layer):
    method __init__ (line 298) | def __init__(
    method forward (line 377) | def forward(self, x, temb, hey=False):
  class Mish (line 414) | class Mish(nn.Layer):
    method forward (line 416) | def forward(self, x):
  function upsample_2d (line 420) | def upsample_2d(x, k=None, factor=2, gain=1):
  function downsample_2d (line 451) | def downsample_2d(x, k=None, factor=2, gain=1):
  function upfirdn2d_native (line 483) | def upfirdn2d_native(input, kernel, up=1, down=1, pad=(0, 0)):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/models/unet_2d.py
  class UNet2DModel (line 30) | class UNet2DModel(nn.Layer, ConfigMixin):
    method __init__ (line 33) | def __init__(
    method forward (line 141) | def forward(self, sample: paddle.Tensor, timestep: Union[paddle.Tensor...

FILE: modules/image/text_to_image/stable_diffusion/diffusers/models/unet_2d_condition.py
  class UNet2DConditionModel (line 29) | class UNet2DConditionModel(nn.Layer, ConfigMixin):
    method __init__ (line 32) | def __init__(
    method forward (line 138) | def forward(

FILE: modules/image/text_to_image/stable_diffusion/diffusers/models/unet_blocks.py
  function get_down_block (line 27) | def get_down_block(
  function get_up_block (line 114) | def get_up_block(
  class UNetMidBlock2D (line 201) | class UNetMidBlock2D(nn.Layer):
    method __init__ (line 203) | def __init__(
    method forward (line 267) | def forward(self, hidden_states, temb=None, encoder_states=None):
  class UNetMidBlock2DCrossAttn (line 279) | class UNetMidBlock2DCrossAttn(nn.Layer):
    method __init__ (line 281) | def __init__(
    method forward (line 346) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class AttnDownBlock2D (line 355) | class AttnDownBlock2D(nn.Layer):
    method __init__ (line 357) | def __init__(
    method forward (line 418) | def forward(self, hidden_states, temb=None):
  class CrossAttnDownBlock2D (line 435) | class CrossAttnDownBlock2D(nn.Layer):
    method __init__ (line 437) | def __init__(
    method forward (line 499) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class DownBlock2D (line 516) | class DownBlock2D(nn.Layer):
    method __init__ (line 518) | def __init__(
    method forward (line 566) | def forward(self, hidden_states, temb=None):
  class DownEncoderBlock2D (line 582) | class DownEncoderBlock2D(nn.Layer):
    method __init__ (line 584) | def __init__(
    method forward (line 631) | def forward(self, hidden_states):
  class AttnDownEncoderBlock2D (line 642) | class AttnDownEncoderBlock2D(nn.Layer):
    method __init__ (line 644) | def __init__(
    method forward (line 702) | def forward(self, hidden_states):
  class AttnSkipDownBlock2D (line 714) | class AttnSkipDownBlock2D(nn.Layer):
    method __init__ (line 716) | def __init__(
    method forward (line 786) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class SkipDownBlock2D (line 806) | class SkipDownBlock2D(nn.Layer):
    method __init__ (line 808) | def __init__(
    method forward (line 866) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class AttnUpBlock2D (line 885) | class AttnUpBlock2D(nn.Layer):
    method __init__ (line 887) | def __init__(
    method forward (line 944) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class CrossAttnUpBlock2D (line 962) | class CrossAttnUpBlock2D(nn.Layer):
    method __init__ (line 964) | def __init__(
    method forward (line 1023) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, e...
  class UpBlock2D (line 1041) | class UpBlock2D(nn.Layer):
    method __init__ (line 1043) | def __init__(
    method forward (line 1087) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class UpDecoderBlock2D (line 1104) | class UpDecoderBlock2D(nn.Layer):
    method __init__ (line 1106) | def __init__(
    method forward (line 1147) | def forward(self, hidden_states):
  class AttnUpDecoderBlock2D (line 1158) | class AttnUpDecoderBlock2D(nn.Layer):
    method __init__ (line 1160) | def __init__(
    method forward (line 1212) | def forward(self, hidden_states):
  class AttnSkipUpBlock2D (line 1224) | class AttnSkipUpBlock2D(nn.Layer):
    method __init__ (line 1226) | def __init__(
    method forward (line 1307) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...
  class SkipUpBlock2D (line 1335) | class SkipUpBlock2D(nn.Layer):
    method __init__ (line 1337) | def __init__(
    method forward (line 1405) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...

FILE: modules/image/text_to_image/stable_diffusion/diffusers/models/vae.py
  class Encoder (line 25) | class Encoder(nn.Layer):
    method __init__ (line 27) | def __init__(
    method forward (line 86) | def forward(self, x):
  class Decoder (line 105) | class Decoder(nn.Layer):
    method __init__ (line 107) | def __init__(
    method forward (line 166) | def forward(self, z):
  class VectorQuantizer (line 185) | class VectorQuantizer(nn.Layer):
    method __init__ (line 194) | def __init__(self, n_e, e_dim, beta, remap=None, unknown_index="random...
    method remap_to_used (line 219) | def remap_to_used(self, inds):
    method unmap_to_all (line 233) | def unmap_to_all(self, inds):
    method forward (line 243) | def forward(self, z):
    method get_codebook_entry (line 279) | def get_codebook_entry(self, indices, shape):
  class DiagonalGaussianDistribution (line 297) | class DiagonalGaussianDistribution(object):
    method __init__ (line 299) | def __init__(self, parameters, deterministic=False):
    method sample (line 309) | def sample(self):
    method kl (line 313) | def kl(self, other=None):
    method nll (line 326) | def nll(self, sample, dims=[1, 2, 3]):
    method mode (line 332) | def mode(self):
  class VQModel (line 336) | class VQModel(ConfigMixin):
    method __init__ (line 339) | def __init__(
    method encode (line 383) | def encode(self, x):
    method decode (line 388) | def decode(self, h, force_not_quantize=False):
    method forward (line 398) | def forward(self, sample):
  class AutoencoderKL (line 405) | class AutoencoderKL(nn.Layer, ConfigMixin):
    method __init__ (line 408) | def __init__(
    method encode (line 446) | def encode(self, x):
    method decode (line 452) | def decode(self, z):
    method forward (line 457) | def forward(self, sample, sample_posterior=False):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_ddim.py
  function betas_for_alpha_bar (line 27) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDIMScheduler (line 50) | class DDIMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 53) | def __init__(
    method _get_variance (line 93) | def _get_variance(self, timestep, prev_timestep):
    method set_timesteps (line 103) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 110) | def step(
    method add_noise (line 172) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 181) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_ddpm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDPMScheduler (line 49) | class DDPMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 90) | def set_timesteps(self, num_inference_steps):
    method _get_variance (line 97) | def _get_variance(self, t, predicted_variance=None, variance_type=None):
    method step (line 130) | def step(
    method add_noise (line 181) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 190) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_karras_ve.py
  class KarrasVeScheduler (line 24) | class KarrasVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 35) | def __init__(
    method set_timesteps (line 70) | def set_timesteps(self, num_inference_steps):
    method add_noise_to_input (line 79) | def add_noise_to_input(self, sample, sigma, generator=None):
    method step (line 96) | def step(
    method step_correct (line 109) | def step_correct(
    method add_noise (line 123) | def add_noise(self, original_samples, noise, timesteps):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_lms_discrete.py
  class LMSDiscreteScheduler (line 25) | class LMSDiscreteScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 28) | def __init__(
    method get_lms_coefficient (line 65) | def get_lms_coefficient(self, order, t, current_order):
    method set_timesteps (line 82) | def set_timesteps(self, num_inference_steps):
    method step (line 97) | def step(
    method add_noise (line 125) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 132) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_pndm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class PNDMScheduler (line 49) | class PNDMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 100) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 125) | def step(
    method step_prk (line 136) | def step_prk(
    method step_plms (line 170) | def step_plms(
    method _get_prev_sample (line 214) | def _get_prev_sample(self, sample, timestep, timestep_prev, model_outp...
    method add_noise (line 248) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 257) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_sde_ve.py
  class ScoreSdeVeScheduler (line 26) | class ScoreSdeVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 39) | def __init__(
    method set_timesteps (line 61) | def set_timesteps(self, num_inference_steps, sampling_eps=None):
    method set_sigmas (line 71) | def set_sigmas(self, num_inference_steps, sigma_min=None, sigma_max=No...
    method get_adjacent_sigma (line 89) | def get_adjacent_sigma(self, timesteps, t):
    method set_seed (line 98) | def set_seed(self, seed):
    method step_pred (line 107) | def step_pred(
    method step_correct (line 141) | def step_correct(
    method __len__ (line 171) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_sde_vp.py
  class ScoreSdeVpScheduler (line 24) | class ScoreSdeVpScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 27) | def __init__(self, num_train_timesteps=2000, beta_min=0.1, beta_max=20...
    method set_timesteps (line 33) | def set_timesteps(self, num_inference_steps):
    method step_pred (line 36) | def step_pred(self, score, x, t):
    method __len__ (line 58) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_utils.py
  class SchedulerMixin (line 22) | class SchedulerMixin:
    method set_format (line 27) | def set_format(self, tensor_format="pd"):
    method clip (line 36) | def clip(self, tensor, min_value=None, max_value=None):
    method log (line 46) | def log(self, tensor):
    method match_shape (line 56) | def match_shape(self, values: Union[np.ndarray, paddle.Tensor], broadc...
    method norm (line 76) | def norm(self, tensor):
    method randn_like (line 85) | def randn_like(self, tensor, generator=None):
    method zeros_like (line 95) | def zeros_like(self, tensor):

FILE: modules/image/text_to_image/stable_diffusion/module.py
  class StableDiffusion (line 50) | class StableDiffusion:
    method __init__ (line 52) | def __init__(self):
    method generate_image (line 105) | def generate_image(self,
    method serving_method (line 253) | def serving_method(self, text_prompts, **kwargs):
    method run_cmd (line 261) | def run_cmd(self, argvs):
    method add_module_config_arg (line 289) | def add_module_config_arg(self):
    method add_module_input_arg (line 336) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/clip/clip/layers.py
  function multi_head_attention_forward (line 12) | def multi_head_attention_forward(x: Tensor,
  class MultiHeadAttention (line 47) | class MultiHeadAttention(nn.Layer):  # without attention mask
    method __init__ (line 49) | def __init__(self, emb_dim: int, num_heads: int):
    method forward (line 61) | def forward(self, x, attn_mask=None):  # x is in shape[max_len,batch_s...
  class Identity (line 74) | class Identity(nn.Layer):
    method __init__ (line 76) | def __init__(self):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 83) | class Bottleneck(nn.Layer):
    method __init__ (line 86) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 111) | def forward(self, x):
  class AttentionPool2d (line 127) | class AttentionPool2d(nn.Layer):
    method __init__ (line 129) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 143) | def forward(self, x):
  class QuickGELU (line 155) | class QuickGELU(nn.Layer):
    method forward (line 157) | def forward(self, x):
  class ResidualAttentionBlock (line 161) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 163) | def __init__(self, d_model: int, n_head: int, attn_mask=None):
    method attention (line 173) | def attention(self, x):
    method forward (line 178) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion_img2img/clip/clip/model.py
  class ModifiedResNet (line 15) | class ModifiedResNet(nn.Layer):
    method __init__ (line 23) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 48) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 57) | def forward(self, x):
  class Transformer (line 76) | class Transformer(nn.Layer):
    method __init__ (line 78) | def __init__(self, width: int, layers: int, heads: int, attn_mask=None):
    method forward (line 84) | def forward(self, x):
  class VisualTransformer (line 88) | class VisualTransformer(nn.Layer):
    method __init__ (line 90) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 113) | def forward(self, x):
  class TextTransformer (line 132) | class TextTransformer(nn.Layer):
    method __init__ (line 134) | def __init__(self, context_length: int, vocab_size: int, transformer_w...
    method build_attention_mask (line 148) | def build_attention_mask(self):
    method forward (line 159) | def forward(self, text):
  class CLIP (line 169) | class CLIP(nn.Layer):
    method __init__ (line 171) | def __init__(
    method build_attention_mask (line 217) | def build_attention_mask(self):
    method encode_image (line 228) | def encode_image(self, image):
    method encode_text (line 231) | def encode_text(self, text):
    method forward (line 245) | def forward(self, image, text):

FILE: modules/image/text_to_image/stable_diffusion_img2img/clip/clip/simple_tokenizer.py
  function default_bpe (line 11) | def default_bpe():
  function bytes_to_unicode (line 16) | def bytes_to_unicode():
  function get_pairs (line 38) | def get_pairs(word):
  function basic_clean (line 50) | def basic_clean(text):
  function whitespace_clean (line 56) | def whitespace_clean(text):
  class SimpleTokenizer (line 62) | class SimpleTokenizer(object):
    method __init__ (line 64) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: modules/image/text_to_image/stable_diffusion_img2img/clip/clip/utils.py
  function tokenize (line 35) | def tokenize(texts: Union[str, List[str]], context_length: int = 77):
  function build_model (line 67) | def build_model(name='VITL14'):
  function build_vitl14_language_model (line 82) | def build_vitl14_language_model():

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/configuration_utils.py
  class ConfigMixin (line 38) | class ConfigMixin:
    method register_to_config (line 47) | def register_to_config(self, **kwargs):
    method save_config (line 69) | def save_config(self, save_directory: Union[str, os.PathLike], push_to...
    method from_config (line 92) | def from_config(cls, pretrained_model_name_or_path: Union[str, os.Path...
    method get_config_dict (line 105) | def get_config_dict(cls, pretrained_model_name_or_path: Union[str, os....
    method extract_init_dict (line 180) | def extract_init_dict(cls, config_dict, **kwargs):
    method _dict_from_json_file (line 208) | def _dict_from_json_file(cls, json_file: Union[str, os.PathLike]):
    method __repr__ (line 213) | def __repr__(self):
    method config (line 217) | def config(self) -> Dict[str, Any]:
    method to_json_string (line 220) | def to_json_string(self) -> str:
    method to_json_file (line 230) | def to_json_file(self, json_file_path: Union[str, os.PathLike]):
  class FrozenDict (line 242) | class FrozenDict(OrderedDict):
    method __init__ (line 244) | def __init__(self, *args, **kwargs):
    method __delitem__ (line 252) | def __delitem__(self, *args, **kwargs):
    method setdefault (line 255) | def setdefault(self, *args, **kwargs):
    method pop (line 258) | def pop(self, *args, **kwargs):
    method update (line 261) | def update(self, *args, **kwargs):
    method __setattr__ (line 264) | def __setattr__(self, name, value):
    method __setitem__ (line 269) | def __setitem__(self, name, value):
  function register_to_config (line 275) | def register_to_config(init):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/models/attention.py
  function finfo (line 23) | def finfo(dtype):
  class AttentionBlockNew (line 35) | class AttentionBlockNew(nn.Layer):
    method __init__ (line 43) | def __init__(
    method transpose_for_scores (line 66) | def transpose_for_scores(self, projection: paddle.Tensor) -> paddle.Te...
    method forward (line 72) | def forward(self, hidden_states):
    method set_weight (line 113) | def set_weight(self, attn_layer):
  class SpatialTransformer (line 162) | class SpatialTransformer(nn.Layer):
    method __init__ (line 168) | def __init__(self, in_channels, n_heads, d_head, depth=1, dropout=0.0,...
    method forward (line 185) | def forward(self, x, context=None):
    method set_weight (line 198) | def set_weight(self, layer):
  class BasicTransformerBlock (line 205) | class BasicTransformerBlock(nn.Layer):
    method __init__ (line 207) | def __init__(self, dim, n_heads, d_head, dropout=0.0, context_dim=None...
    method forward (line 222) | def forward(self, x, context=None):
  class CrossAttention (line 229) | class CrossAttention(nn.Layer):
    method __init__ (line 231) | def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, ...
    method reshape_heads_to_batch_dim (line 245) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 252) | def reshape_batch_dim_to_heads(self, tensor):
    method forward (line 259) | def forward(self, x, context=None, mask=None):
  class FeedForward (line 289) | class FeedForward(nn.Layer):
    method __init__ (line 291) | def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.0):
    method forward (line 299) | def forward(self, x):
  class GEGLU (line 304) | class GEGLU(nn.Layer):
    method __init__ (line 306) | def __init__(self, dim_in, dim_out):
    method forward (line 310) | def forward(self, x):
  class NIN (line 316) | class NIN(nn.Layer):
    method __init__ (line 318) | def __init__(self, in_dim, num_units, init_scale=0.1):
  function exists (line 328) | def exists(val):
  function default (line 332) | def default(val, d):
  class AttentionBlock (line 339) | class AttentionBlock(nn.Layer):
    method __init__ (line 347) | def __init__(
    method set_weights (line 403) | def set_weights(self, layer):
    method forward (line 430) | def forward(self, x, encoder_out=None):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/models/embeddings.py
  function get_timestep_embedding (line 22) | def get_timestep_embedding(timesteps,
  class TimestepEmbedding (line 61) | class TimestepEmbedding(nn.Layer):
    method __init__ (line 63) | def __init__(self, channel, time_embed_dim, act_fn="silu"):
    method forward (line 72) | def forward(self, sample):
  class Timesteps (line 82) | class Timesteps(nn.Layer):
    method __init__ (line 84) | def __init__(self, num_channels, flip_sin_to_cos, downscale_freq_shift):
    method forward (line 90) | def forward(self, timesteps):
  class GaussianFourierProjection (line 100) | class GaussianFourierProjection(nn.Layer):
    method __init__ (line 103) | def __init__(self, embedding_size=256, scale=1.0):
    method forward (line 112) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/models/resnet.py
  function pad_new (line 22) | def pad_new(x, pad, mode="constant", value=0):
  class Upsample2D (line 54) | class Upsample2D(nn.Layer):
    method __init__ (line 63) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 83) | def forward(self, x):
  class Downsample2D (line 100) | class Downsample2D(nn.Layer):
    method __init__ (line 109) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 133) | def forward(self, x):
  class FirUpsample2D (line 145) | class FirUpsample2D(nn.Layer):
    method __init__ (line 147) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _upsample_2d (line 156) | def _upsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 223) | def forward(self, x):
  class FirDownsample2D (line 233) | class FirDownsample2D(nn.Layer):
    method __init__ (line 235) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _downsample_2d (line 244) | def _downsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 286) | def forward(self, x):
  class ResnetBlock (line 296) | class ResnetBlock(nn.Layer):
    method __init__ (line 298) | def __init__(
    method forward (line 377) | def forward(self, x, temb, hey=False):
  class Mish (line 414) | class Mish(nn.Layer):
    method forward (line 416) | def forward(self, x):
  function upsample_2d (line 420) | def upsample_2d(x, k=None, factor=2, gain=1):
  function downsample_2d (line 451) | def downsample_2d(x, k=None, factor=2, gain=1):
  function upfirdn2d_native (line 483) | def upfirdn2d_native(input, kernel, up=1, down=1, pad=(0, 0)):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/models/unet_2d.py
  class UNet2DModel (line 30) | class UNet2DModel(nn.Layer, ConfigMixin):
    method __init__ (line 33) | def __init__(
    method forward (line 141) | def forward(self, sample: paddle.Tensor, timestep: Union[paddle.Tensor...

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/models/unet_2d_condition.py
  class UNet2DConditionModel (line 29) | class UNet2DConditionModel(nn.Layer, ConfigMixin):
    method __init__ (line 32) | def __init__(
    method forward (line 138) | def forward(

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/models/unet_blocks.py
  function get_down_block (line 27) | def get_down_block(
  function get_up_block (line 114) | def get_up_block(
  class UNetMidBlock2D (line 201) | class UNetMidBlock2D(nn.Layer):
    method __init__ (line 203) | def __init__(
    method forward (line 267) | def forward(self, hidden_states, temb=None, encoder_states=None):
  class UNetMidBlock2DCrossAttn (line 279) | class UNetMidBlock2DCrossAttn(nn.Layer):
    method __init__ (line 281) | def __init__(
    method forward (line 346) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class AttnDownBlock2D (line 355) | class AttnDownBlock2D(nn.Layer):
    method __init__ (line 357) | def __init__(
    method forward (line 418) | def forward(self, hidden_states, temb=None):
  class CrossAttnDownBlock2D (line 435) | class CrossAttnDownBlock2D(nn.Layer):
    method __init__ (line 437) | def __init__(
    method forward (line 499) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class DownBlock2D (line 516) | class DownBlock2D(nn.Layer):
    method __init__ (line 518) | def __init__(
    method forward (line 566) | def forward(self, hidden_states, temb=None):
  class DownEncoderBlock2D (line 582) | class DownEncoderBlock2D(nn.Layer):
    method __init__ (line 584) | def __init__(
    method forward (line 631) | def forward(self, hidden_states):
  class AttnDownEncoderBlock2D (line 642) | class AttnDownEncoderBlock2D(nn.Layer):
    method __init__ (line 644) | def __init__(
    method forward (line 702) | def forward(self, hidden_states):
  class AttnSkipDownBlock2D (line 714) | class AttnSkipDownBlock2D(nn.Layer):
    method __init__ (line 716) | def __init__(
    method forward (line 786) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class SkipDownBlock2D (line 806) | class SkipDownBlock2D(nn.Layer):
    method __init__ (line 808) | def __init__(
    method forward (line 866) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class AttnUpBlock2D (line 885) | class AttnUpBlock2D(nn.Layer):
    method __init__ (line 887) | def __init__(
    method forward (line 944) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class CrossAttnUpBlock2D (line 962) | class CrossAttnUpBlock2D(nn.Layer):
    method __init__ (line 964) | def __init__(
    method forward (line 1023) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, e...
  class UpBlock2D (line 1041) | class UpBlock2D(nn.Layer):
    method __init__ (line 1043) | def __init__(
    method forward (line 1087) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class UpDecoderBlock2D (line 1104) | class UpDecoderBlock2D(nn.Layer):
    method __init__ (line 1106) | def __init__(
    method forward (line 1147) | def forward(self, hidden_states):
  class AttnUpDecoderBlock2D (line 1158) | class AttnUpDecoderBlock2D(nn.Layer):
    method __init__ (line 1160) | def __init__(
    method forward (line 1212) | def forward(self, hidden_states):
  class AttnSkipUpBlock2D (line 1224) | class AttnSkipUpBlock2D(nn.Layer):
    method __init__ (line 1226) | def __init__(
    method forward (line 1307) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...
  class SkipUpBlock2D (line 1335) | class SkipUpBlock2D(nn.Layer):
    method __init__ (line 1337) | def __init__(
    method forward (line 1405) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/models/vae.py
  class Encoder (line 25) | class Encoder(nn.Layer):
    method __init__ (line 27) | def __init__(
    method forward (line 86) | def forward(self, x):
  class Decoder (line 105) | class Decoder(nn.Layer):
    method __init__ (line 107) | def __init__(
    method forward (line 166) | def forward(self, z):
  class VectorQuantizer (line 185) | class VectorQuantizer(nn.Layer):
    method __init__ (line 194) | def __init__(self, n_e, e_dim, beta, remap=None, unknown_index="random...
    method remap_to_used (line 219) | def remap_to_used(self, inds):
    method unmap_to_all (line 233) | def unmap_to_all(self, inds):
    method forward (line 243) | def forward(self, z):
    method get_codebook_entry (line 279) | def get_codebook_entry(self, indices, shape):
  class DiagonalGaussianDistribution (line 297) | class DiagonalGaussianDistribution(object):
    method __init__ (line 299) | def __init__(self, parameters, deterministic=False):
    method sample (line 309) | def sample(self):
    method kl (line 313) | def kl(self, other=None):
    method nll (line 326) | def nll(self, sample, dims=[1, 2, 3]):
    method mode (line 332) | def mode(self):
  class VQModel (line 336) | class VQModel(ConfigMixin):
    method __init__ (line 339) | def __init__(
    method encode (line 383) | def encode(self, x):
    method decode (line 388) | def decode(self, h, force_not_quantize=False):
    method forward (line 398) | def forward(self, sample):
  class AutoencoderKL (line 405) | class AutoencoderKL(nn.Layer, ConfigMixin):
    method __init__ (line 408) | def __init__(
    method encode (line 446) | def encode(self, x):
    method decode (line 452) | def decode(self, z):
    method forward (line 457) | def forward(self, sample, sample_posterior=False):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_ddim.py
  function betas_for_alpha_bar (line 27) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDIMScheduler (line 50) | class DDIMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 53) | def __init__(
    method _get_variance (line 93) | def _get_variance(self, timestep, prev_timestep):
    method set_timesteps (line 103) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 110) | def step(
    method add_noise (line 172) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 181) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_ddpm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDPMScheduler (line 49) | class DDPMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 90) | def set_timesteps(self, num_inference_steps):
    method _get_variance (line 97) | def _get_variance(self, t, predicted_variance=None, variance_type=None):
    method step (line 130) | def step(
    method add_noise (line 181) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 190) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_karras_ve.py
  class KarrasVeScheduler (line 24) | class KarrasVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 35) | def __init__(
    method set_timesteps (line 70) | def set_timesteps(self, num_inference_steps):
    method add_noise_to_input (line 79) | def add_noise_to_input(self, sample, sigma, generator=None):
    method step (line 96) | def step(
    method step_correct (line 109) | def step_correct(
    method add_noise (line 123) | def add_noise(self, original_samples, noise, timesteps):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_lms_discrete.py
  class LMSDiscreteScheduler (line 25) | class LMSDiscreteScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 28) | def __init__(
    method get_lms_coefficient (line 65) | def get_lms_coefficient(self, order, t, current_order):
    method set_timesteps (line 82) | def set_timesteps(self, num_inference_steps):
    method step (line 97) | def step(
    method add_noise (line 125) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 132) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_pndm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class PNDMScheduler (line 49) | class PNDMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 100) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 125) | def step(
    method step_prk (line 136) | def step_prk(
    method step_plms (line 170) | def step_plms(
    method _get_prev_sample (line 214) | def _get_prev_sample(self, sample, timestep, timestep_prev, model_outp...
    method add_noise (line 248) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 257) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_sde_ve.py
  class ScoreSdeVeScheduler (line 26) | class ScoreSdeVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 39) | def __init__(
    method set_timesteps (line 61) | def set_timesteps(self, num_inference_steps, sampling_eps=None):
    method set_sigmas (line 71) | def set_sigmas(self, num_inference_steps, sigma_min=None, sigma_max=No...
    method get_adjacent_sigma (line 89) | def get_adjacent_sigma(self, timesteps, t):
    method set_seed (line 98) | def set_seed(self, seed):
    method step_pred (line 107) | def step_pred(
    method step_correct (line 141) | def step_correct(
    method __len__ (line 171) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_sde_vp.py
  class ScoreSdeVpScheduler (line 24) | class ScoreSdeVpScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 27) | def __init__(self, num_train_timesteps=2000, beta_min=0.1, beta_max=20...
    method set_timesteps (line 33) | def set_timesteps(self, num_inference_steps):
    method step_pred (line 36) | def step_pred(self, score, x, t):
    method __len__ (line 58) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/diffusers/schedulers/scheduling_utils.py
  class SchedulerMixin (line 22) | class SchedulerMixin:
    method set_format (line 27) | def set_format(self, tensor_format="pd"):
    method clip (line 36) | def clip(self, tensor, min_value=None, max_value=None):
    method log (line 46) | def log(self, tensor):
    method match_shape (line 56) | def match_shape(self, values: Union[np.ndarray, paddle.Tensor], broadc...
    method norm (line 76) | def norm(self, tensor):
    method randn_like (line 85) | def randn_like(self, tensor, generator=None):
    method zeros_like (line 95) | def zeros_like(self, tensor):

FILE: modules/image/text_to_image/stable_diffusion_img2img/module.py
  class StableDiffusionImg2Img (line 54) | class StableDiffusionImg2Img:
    method __init__ (line 56) | def __init__(self):
    method generate_image (line 109) | def generate_image(self,
    method serving_method (line 309) | def serving_method(self, text_prompts, init_image, **kwargs):
    method run_cmd (line 318) | def run_cmd(self, argvs):
    method add_module_config_arg (line 347) | def add_module_config_arg(self):
    method add_module_input_arg (line 394) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/stable_diffusion_img2img/utils.py
  function preprocess (line 7) | def preprocess(image):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/clip/clip/layers.py
  function multi_head_attention_forward (line 12) | def multi_head_attention_forward(x: Tensor,
  class MultiHeadAttention (line 47) | class MultiHeadAttention(nn.Layer):  # without attention mask
    method __init__ (line 49) | def __init__(self, emb_dim: int, num_heads: int):
    method forward (line 61) | def forward(self, x, attn_mask=None):  # x is in shape[max_len,batch_s...
  class Identity (line 74) | class Identity(nn.Layer):
    method __init__ (line 76) | def __init__(self):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 83) | class Bottleneck(nn.Layer):
    method __init__ (line 86) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 111) | def forward(self, x):
  class AttentionPool2d (line 127) | class AttentionPool2d(nn.Layer):
    method __init__ (line 129) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 143) | def forward(self, x):
  class QuickGELU (line 155) | class QuickGELU(nn.Layer):
    method forward (line 157) | def forward(self, x):
  class ResidualAttentionBlock (line 161) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 163) | def __init__(self, d_model: int, n_head: int, attn_mask=None):
    method attention (line 173) | def attention(self, x):
    method forward (line 178) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/clip/clip/model.py
  class ModifiedResNet (line 15) | class ModifiedResNet(nn.Layer):
    method __init__ (line 23) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 48) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 57) | def forward(self, x):
  class Transformer (line 76) | class Transformer(nn.Layer):
    method __init__ (line 78) | def __init__(self, width: int, layers: int, heads: int, attn_mask=None):
    method forward (line 84) | def forward(self, x):
  class VisualTransformer (line 88) | class VisualTransformer(nn.Layer):
    method __init__ (line 90) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 113) | def forward(self, x):
  class TextTransformer (line 132) | class TextTransformer(nn.Layer):
    method __init__ (line 134) | def __init__(self, context_length: int, vocab_size: int, transformer_w...
    method build_attention_mask (line 148) | def build_attention_mask(self):
    method forward (line 159) | def forward(self, text):
  class CLIP (line 169) | class CLIP(nn.Layer):
    method __init__ (line 171) | def __init__(
    method build_attention_mask (line 217) | def build_attention_mask(self):
    method encode_image (line 228) | def encode_image(self, image):
    method encode_text (line 231) | def encode_text(self, text):
    method forward (line 245) | def forward(self, image, text):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/clip/clip/simple_tokenizer.py
  function default_bpe (line 11) | def default_bpe():
  function bytes_to_unicode (line 16) | def bytes_to_unicode():
  function get_pairs (line 38) | def get_pairs(word):
  function basic_clean (line 50) | def basic_clean(text):
  function whitespace_clean (line 56) | def whitespace_clean(text):
  class SimpleTokenizer (line 62) | class SimpleTokenizer(object):
    method __init__ (line 64) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/clip/clip/utils.py
  function tokenize (line 35) | def tokenize(texts: Union[str, List[str]], context_length: int = 77):
  function build_model (line 67) | def build_model(name='VITL14'):
  function build_vitl14_language_model (line 82) | def build_vitl14_language_model():

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/configuration_utils.py
  class ConfigMixin (line 38) | class ConfigMixin:
    method register_to_config (line 47) | def register_to_config(self, **kwargs):
    method save_config (line 69) | def save_config(self, save_directory: Union[str, os.PathLike], push_to...
    method from_config (line 92) | def from_config(cls, pretrained_model_name_or_path: Union[str, os.Path...
    method get_config_dict (line 105) | def get_config_dict(cls, pretrained_model_name_or_path: Union[str, os....
    method extract_init_dict (line 180) | def extract_init_dict(cls, config_dict, **kwargs):
    method _dict_from_json_file (line 208) | def _dict_from_json_file(cls, json_file: Union[str, os.PathLike]):
    method __repr__ (line 213) | def __repr__(self):
    method config (line 217) | def config(self) -> Dict[str, Any]:
    method to_json_string (line 220) | def to_json_string(self) -> str:
    method to_json_file (line 230) | def to_json_file(self, json_file_path: Union[str, os.PathLike]):
  class FrozenDict (line 242) | class FrozenDict(OrderedDict):
    method __init__ (line 244) | def __init__(self, *args, **kwargs):
    method __delitem__ (line 252) | def __delitem__(self, *args, **kwargs):
    method setdefault (line 255) | def setdefault(self, *args, **kwargs):
    method pop (line 258) | def pop(self, *args, **kwargs):
    method update (line 261) | def update(self, *args, **kwargs):
    method __setattr__ (line 264) | def __setattr__(self, name, value):
    method __setitem__ (line 269) | def __setitem__(self, name, value):
  function register_to_config (line 275) | def register_to_config(init):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/models/attention.py
  function finfo (line 23) | def finfo(dtype):
  class AttentionBlockNew (line 35) | class AttentionBlockNew(nn.Layer):
    method __init__ (line 43) | def __init__(
    method transpose_for_scores (line 66) | def transpose_for_scores(self, projection: paddle.Tensor) -> paddle.Te...
    method forward (line 72) | def forward(self, hidden_states):
    method set_weight (line 113) | def set_weight(self, attn_layer):
  class SpatialTransformer (line 162) | class SpatialTransformer(nn.Layer):
    method __init__ (line 168) | def __init__(self, in_channels, n_heads, d_head, depth=1, dropout=0.0,...
    method forward (line 185) | def forward(self, x, context=None):
    method set_weight (line 198) | def set_weight(self, layer):
  class BasicTransformerBlock (line 205) | class BasicTransformerBlock(nn.Layer):
    method __init__ (line 207) | def __init__(self, dim, n_heads, d_head, dropout=0.0, context_dim=None...
    method forward (line 222) | def forward(self, x, context=None):
  class CrossAttention (line 229) | class CrossAttention(nn.Layer):
    method __init__ (line 231) | def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, ...
    method reshape_heads_to_batch_dim (line 245) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 252) | def reshape_batch_dim_to_heads(self, tensor):
    method forward (line 259) | def forward(self, x, context=None, mask=None):
  class FeedForward (line 289) | class FeedForward(nn.Layer):
    method __init__ (line 291) | def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.0):
    method forward (line 299) | def forward(self, x):
  class GEGLU (line 304) | class GEGLU(nn.Layer):
    method __init__ (line 306) | def __init__(self, dim_in, dim_out):
    method forward (line 310) | def forward(self, x):
  class NIN (line 316) | class NIN(nn.Layer):
    method __init__ (line 318) | def __init__(self, in_dim, num_units, init_scale=0.1):
  function exists (line 328) | def exists(val):
  function default (line 332) | def default(val, d):
  class AttentionBlock (line 339) | class AttentionBlock(nn.Layer):
    method __init__ (line 347) | def __init__(
    method set_weights (line 403) | def set_weights(self, layer):
    method forward (line 430) | def forward(self, x, encoder_out=None):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/models/embeddings.py
  function get_timestep_embedding (line 22) | def get_timestep_embedding(timesteps,
  class TimestepEmbedding (line 61) | class TimestepEmbedding(nn.Layer):
    method __init__ (line 63) | def __init__(self, channel, time_embed_dim, act_fn="silu"):
    method forward (line 72) | def forward(self, sample):
  class Timesteps (line 82) | class Timesteps(nn.Layer):
    method __init__ (line 84) | def __init__(self, num_channels, flip_sin_to_cos, downscale_freq_shift):
    method forward (line 90) | def forward(self, timesteps):
  class GaussianFourierProjection (line 100) | class GaussianFourierProjection(nn.Layer):
    method __init__ (line 103) | def __init__(self, embedding_size=256, scale=1.0):
    method forward (line 112) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/models/resnet.py
  function pad_new (line 22) | def pad_new(x, pad, mode="constant", value=0):
  class Upsample2D (line 54) | class Upsample2D(nn.Layer):
    method __init__ (line 63) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 83) | def forward(self, x):
  class Downsample2D (line 100) | class Downsample2D(nn.Layer):
    method __init__ (line 109) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 133) | def forward(self, x):
  class FirUpsample2D (line 145) | class FirUpsample2D(nn.Layer):
    method __init__ (line 147) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _upsample_2d (line 156) | def _upsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 223) | def forward(self, x):
  class FirDownsample2D (line 233) | class FirDownsample2D(nn.Layer):
    method __init__ (line 235) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _downsample_2d (line 244) | def _downsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 286) | def forward(self, x):
  class ResnetBlock (line 296) | class ResnetBlock(nn.Layer):
    method __init__ (line 298) | def __init__(
    method forward (line 377) | def forward(self, x, temb, hey=False):
  class Mish (line 414) | class Mish(nn.Layer):
    method forward (line 416) | def forward(self, x):
  function upsample_2d (line 420) | def upsample_2d(x, k=None, factor=2, gain=1):
  function downsample_2d (line 451) | def downsample_2d(x, k=None, factor=2, gain=1):
  function upfirdn2d_native (line 483) | def upfirdn2d_native(input, kernel, up=1, down=1, pad=(0, 0)):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/models/unet_2d.py
  class UNet2DModel (line 30) | class UNet2DModel(nn.Layer, ConfigMixin):
    method __init__ (line 33) | def __init__(
    method forward (line 141) | def forward(self, sample: paddle.Tensor, timestep: Union[paddle.Tensor...

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/models/unet_2d_condition.py
  class UNet2DConditionModel (line 29) | class UNet2DConditionModel(nn.Layer, ConfigMixin):
    method __init__ (line 32) | def __init__(
    method forward (line 138) | def forward(

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/models/unet_blocks.py
  function get_down_block (line 27) | def get_down_block(
  function get_up_block (line 114) | def get_up_block(
  class UNetMidBlock2D (line 201) | class UNetMidBlock2D(nn.Layer):
    method __init__ (line 203) | def __init__(
    method forward (line 267) | def forward(self, hidden_states, temb=None, encoder_states=None):
  class UNetMidBlock2DCrossAttn (line 279) | class UNetMidBlock2DCrossAttn(nn.Layer):
    method __init__ (line 281) | def __init__(
    method forward (line 346) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class AttnDownBlock2D (line 355) | class AttnDownBlock2D(nn.Layer):
    method __init__ (line 357) | def __init__(
    method forward (line 418) | def forward(self, hidden_states, temb=None):
  class CrossAttnDownBlock2D (line 435) | class CrossAttnDownBlock2D(nn.Layer):
    method __init__ (line 437) | def __init__(
    method forward (line 499) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class DownBlock2D (line 516) | class DownBlock2D(nn.Layer):
    method __init__ (line 518) | def __init__(
    method forward (line 566) | def forward(self, hidden_states, temb=None):
  class DownEncoderBlock2D (line 582) | class DownEncoderBlock2D(nn.Layer):
    method __init__ (line 584) | def __init__(
    method forward (line 631) | def forward(self, hidden_states):
  class AttnDownEncoderBlock2D (line 642) | class AttnDownEncoderBlock2D(nn.Layer):
    method __init__ (line 644) | def __init__(
    method forward (line 702) | def forward(self, hidden_states):
  class AttnSkipDownBlock2D (line 714) | class AttnSkipDownBlock2D(nn.Layer):
    method __init__ (line 716) | def __init__(
    method forward (line 786) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class SkipDownBlock2D (line 806) | class SkipDownBlock2D(nn.Layer):
    method __init__ (line 808) | def __init__(
    method forward (line 866) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class AttnUpBlock2D (line 885) | class AttnUpBlock2D(nn.Layer):
    method __init__ (line 887) | def __init__(
    method forward (line 944) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class CrossAttnUpBlock2D (line 962) | class CrossAttnUpBlock2D(nn.Layer):
    method __init__ (line 964) | def __init__(
    method forward (line 1023) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, e...
  class UpBlock2D (line 1041) | class UpBlock2D(nn.Layer):
    method __init__ (line 1043) | def __init__(
    method forward (line 1087) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class UpDecoderBlock2D (line 1104) | class UpDecoderBlock2D(nn.Layer):
    method __init__ (line 1106) | def __init__(
    method forward (line 1147) | def forward(self, hidden_states):
  class AttnUpDecoderBlock2D (line 1158) | class AttnUpDecoderBlock2D(nn.Layer):
    method __init__ (line 1160) | def __init__(
    method forward (line 1212) | def forward(self, hidden_states):
  class AttnSkipUpBlock2D (line 1224) | class AttnSkipUpBlock2D(nn.Layer):
    method __init__ (line 1226) | def __init__(
    method forward (line 1307) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...
  class SkipUpBlock2D (line 1335) | class SkipUpBlock2D(nn.Layer):
    method __init__ (line 1337) | def __init__(
    method forward (line 1405) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/models/vae.py
  class Encoder (line 25) | class Encoder(nn.Layer):
    method __init__ (line 27) | def __init__(
    method forward (line 86) | def forward(self, x):
  class Decoder (line 105) | class Decoder(nn.Layer):
    method __init__ (line 107) | def __init__(
    method forward (line 166) | def forward(self, z):
  class VectorQuantizer (line 185) | class VectorQuantizer(nn.Layer):
    method __init__ (line 194) | def __init__(self, n_e, e_dim, beta, remap=None, unknown_index="random...
    method remap_to_used (line 219) | def remap_to_used(self, inds):
    method unmap_to_all (line 233) | def unmap_to_all(self, inds):
    method forward (line 243) | def forward(self, z):
    method get_codebook_entry (line 279) | def get_codebook_entry(self, indices, shape):
  class DiagonalGaussianDistribution (line 297) | class DiagonalGaussianDistribution(object):
    method __init__ (line 299) | def __init__(self, parameters, deterministic=False):
    method sample (line 309) | def sample(self):
    method kl (line 313) | def kl(self, other=None):
    method nll (line 326) | def nll(self, sample, dims=[1, 2, 3]):
    method mode (line 332) | def mode(self):
  class VQModel (line 336) | class VQModel(ConfigMixin):
    method __init__ (line 339) | def __init__(
    method encode (line 383) | def encode(self, x):
    method decode (line 388) | def decode(self, h, force_not_quantize=False):
    method forward (line 398) | def forward(self, sample):
  class AutoencoderKL (line 405) | class AutoencoderKL(nn.Layer, ConfigMixin):
    method __init__ (line 408) | def __init__(
    method encode (line 446) | def encode(self, x):
    method decode (line 452) | def decode(self, z):
    method forward (line 457) | def forward(self, sample, sample_posterior=False):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_ddim.py
  function betas_for_alpha_bar (line 27) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDIMScheduler (line 50) | class DDIMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 53) | def __init__(
    method _get_variance (line 93) | def _get_variance(self, timestep, prev_timestep):
    method set_timesteps (line 103) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 110) | def step(
    method add_noise (line 172) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 181) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_ddpm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDPMScheduler (line 49) | class DDPMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 90) | def set_timesteps(self, num_inference_steps):
    method _get_variance (line 97) | def _get_variance(self, t, predicted_variance=None, variance_type=None):
    method step (line 130) | def step(
    method add_noise (line 181) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 190) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_karras_ve.py
  class KarrasVeScheduler (line 24) | class KarrasVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 35) | def __init__(
    method set_timesteps (line 70) | def set_timesteps(self, num_inference_steps):
    method add_noise_to_input (line 79) | def add_noise_to_input(self, sample, sigma, generator=None):
    method step (line 96) | def step(
    method step_correct (line 109) | def step_correct(
    method add_noise (line 123) | def add_noise(self, original_samples, noise, timesteps):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_lms_discrete.py
  class LMSDiscreteScheduler (line 25) | class LMSDiscreteScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 28) | def __init__(
    method get_lms_coefficient (line 65) | def get_lms_coefficient(self, order, t, current_order):
    method set_timesteps (line 82) | def set_timesteps(self, num_inference_steps):
    method step (line 97) | def step(
    method add_noise (line 125) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 132) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_pndm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class PNDMScheduler (line 49) | class PNDMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 100) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 125) | def step(
    method step_prk (line 136) | def step_prk(
    method step_plms (line 170) | def step_plms(
    method _get_prev_sample (line 214) | def _get_prev_sample(self, sample, timestep, timestep_prev, model_outp...
    method add_noise (line 248) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 257) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_sde_ve.py
  class ScoreSdeVeScheduler (line 26) | class ScoreSdeVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 39) | def __init__(
    method set_timesteps (line 61) | def set_timesteps(self, num_inference_steps, sampling_eps=None):
    method set_sigmas (line 71) | def set_sigmas(self, num_inference_steps, sigma_min=None, sigma_max=No...
    method get_adjacent_sigma (line 89) | def get_adjacent_sigma(self, timesteps, t):
    method set_seed (line 98) | def set_seed(self, seed):
    method step_pred (line 107) | def step_pred(
    method step_correct (line 141) | def step_correct(
    method __len__ (line 171) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_sde_vp.py
  class ScoreSdeVpScheduler (line 24) | class ScoreSdeVpScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 27) | def __init__(self, num_train_timesteps=2000, beta_min=0.1, beta_max=20...
    method set_timesteps (line 33) | def set_timesteps(self, num_inference_steps):
    method step_pred (line 36) | def step_pred(self, score, x, t):
    method __len__ (line 58) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/diffusers/schedulers/scheduling_utils.py
  class SchedulerMixin (line 22) | class SchedulerMixin:
    method set_format (line 27) | def set_format(self, tensor_format="pd"):
    method clip (line 36) | def clip(self, tensor, min_value=None, max_value=None):
    method log (line 46) | def log(self, tensor):
    method match_shape (line 56) | def match_shape(self, values: Union[np.ndarray, paddle.Tensor], broadc...
    method norm (line 76) | def norm(self, tensor):
    method randn_like (line 85) | def randn_like(self, tensor, generator=None):
    method zeros_like (line 95) | def zeros_like(self, tensor):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/module.py
  class StableDiffusionInpainting (line 55) | class StableDiffusionInpainting:
    method __init__ (line 57) | def __init__(self):
    method generate_image (line 110) | def generate_image(self,
    method serving_method (line 329) | def serving_method(self, text_prompts, init_image, mask_image, **kwargs):
    method run_cmd (line 340) | def run_cmd(self, argvs):
    method add_module_config_arg (line 367) | def add_module_config_arg(self):
    method add_module_input_arg (line 414) | def add_module_input_arg(self):

FILE: modules/image/text_to_image/stable_diffusion_inpainting/utils.py
  function preprocess (line 7) | def preprocess(image):
  function preprocess_mask (line 19) | def preprocess_mask(mask):

FILE: modules/image/text_to_image/stable_diffusion_waifu/clip/clip/layers.py
  function multi_head_attention_forward (line 12) | def multi_head_attention_forward(x: Tensor,
  class MultiHeadAttention (line 47) | class MultiHeadAttention(nn.Layer):  # without attention mask
    method __init__ (line 49) | def __init__(self, emb_dim: int, num_heads: int):
    method forward (line 61) | def forward(self, x, attn_mask=None):  # x is in shape[max_len,batch_s...
  class Identity (line 74) | class Identity(nn.Layer):
    method __init__ (line 76) | def __init__(self):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 83) | class Bottleneck(nn.Layer):
    method __init__ (line 86) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 111) | def forward(self, x):
  class AttentionPool2d (line 127) | class AttentionPool2d(nn.Layer):
    method __init__ (line 129) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 143) | def forward(self, x):
  class QuickGELU (line 155) | class QuickGELU(nn.Layer):
    method forward (line 157) | def forward(self, x):
  class ResidualAttentionBlock (line 161) | class ResidualAttentionBlock(nn.Layer):
    method __init__ (line 163) | def __init__(self, d_model: int, n_head: int, attn_mask=None):
    method attention (line 173) | def attention(self, x):
    method forward (line 178) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion_waifu/clip/clip/model.py
  class ModifiedResNet (line 15) | class ModifiedResNet(nn.Layer):
    method __init__ (line 23) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 48) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 57) | def forward(self, x):
  class Transformer (line 76) | class Transformer(nn.Layer):
    method __init__ (line 78) | def __init__(self, width: int, layers: int, heads: int, attn_mask=None):
    method forward (line 84) | def forward(self, x):
  class VisualTransformer (line 88) | class VisualTransformer(nn.Layer):
    method __init__ (line 90) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 113) | def forward(self, x):
  class TextTransformer (line 132) | class TextTransformer(nn.Layer):
    method __init__ (line 134) | def __init__(self, context_length: int, vocab_size: int, transformer_w...
    method build_attention_mask (line 148) | def build_attention_mask(self):
    method forward (line 159) | def forward(self, text):
  class CLIP (line 169) | class CLIP(nn.Layer):
    method __init__ (line 171) | def __init__(
    method build_attention_mask (line 217) | def build_attention_mask(self):
    method encode_image (line 228) | def encode_image(self, image):
    method encode_text (line 231) | def encode_text(self, text):
    method forward (line 245) | def forward(self, image, text):

FILE: modules/image/text_to_image/stable_diffusion_waifu/clip/clip/simple_tokenizer.py
  function default_bpe (line 11) | def default_bpe():
  function bytes_to_unicode (line 16) | def bytes_to_unicode():
  function get_pairs (line 38) | def get_pairs(word):
  function basic_clean (line 50) | def basic_clean(text):
  function whitespace_clean (line 56) | def whitespace_clean(text):
  class SimpleTokenizer (line 62) | class SimpleTokenizer(object):
    method __init__ (line 64) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: modules/image/text_to_image/stable_diffusion_waifu/clip/clip/utils.py
  function tokenize (line 35) | def tokenize(texts: Union[str, List[str]], context_length: int = 77):
  function build_model (line 67) | def build_model(name='VITL14'):
  function build_vitl14_language_model (line 82) | def build_vitl14_language_model():

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/configuration_utils.py
  class ConfigMixin (line 38) | class ConfigMixin:
    method register_to_config (line 47) | def register_to_config(self, **kwargs):
    method save_config (line 69) | def save_config(self, save_directory: Union[str, os.PathLike], push_to...
    method from_config (line 92) | def from_config(cls, pretrained_model_name_or_path: Union[str, os.Path...
    method get_config_dict (line 105) | def get_config_dict(cls, pretrained_model_name_or_path: Union[str, os....
    method extract_init_dict (line 180) | def extract_init_dict(cls, config_dict, **kwargs):
    method _dict_from_json_file (line 208) | def _dict_from_json_file(cls, json_file: Union[str, os.PathLike]):
    method __repr__ (line 213) | def __repr__(self):
    method config (line 217) | def config(self) -> Dict[str, Any]:
    method to_json_string (line 220) | def to_json_string(self) -> str:
    method to_json_file (line 230) | def to_json_file(self, json_file_path: Union[str, os.PathLike]):
  class FrozenDict (line 242) | class FrozenDict(OrderedDict):
    method __init__ (line 244) | def __init__(self, *args, **kwargs):
    method __delitem__ (line 252) | def __delitem__(self, *args, **kwargs):
    method setdefault (line 255) | def setdefault(self, *args, **kwargs):
    method pop (line 258) | def pop(self, *args, **kwargs):
    method update (line 261) | def update(self, *args, **kwargs):
    method __setattr__ (line 264) | def __setattr__(self, name, value):
    method __setitem__ (line 269) | def __setitem__(self, name, value):
  function register_to_config (line 275) | def register_to_config(init):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/models/attention.py
  function finfo (line 23) | def finfo(dtype):
  class AttentionBlockNew (line 35) | class AttentionBlockNew(nn.Layer):
    method __init__ (line 43) | def __init__(
    method transpose_for_scores (line 66) | def transpose_for_scores(self, projection: paddle.Tensor) -> paddle.Te...
    method forward (line 72) | def forward(self, hidden_states):
    method set_weight (line 113) | def set_weight(self, attn_layer):
  class SpatialTransformer (line 162) | class SpatialTransformer(nn.Layer):
    method __init__ (line 168) | def __init__(self, in_channels, n_heads, d_head, depth=1, dropout=0.0,...
    method forward (line 185) | def forward(self, x, context=None):
    method set_weight (line 198) | def set_weight(self, layer):
  class BasicTransformerBlock (line 205) | class BasicTransformerBlock(nn.Layer):
    method __init__ (line 207) | def __init__(self, dim, n_heads, d_head, dropout=0.0, context_dim=None...
    method forward (line 222) | def forward(self, x, context=None):
  class CrossAttention (line 229) | class CrossAttention(nn.Layer):
    method __init__ (line 231) | def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, ...
    method reshape_heads_to_batch_dim (line 245) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 252) | def reshape_batch_dim_to_heads(self, tensor):
    method forward (line 259) | def forward(self, x, context=None, mask=None):
  class FeedForward (line 289) | class FeedForward(nn.Layer):
    method __init__ (line 291) | def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.0):
    method forward (line 299) | def forward(self, x):
  class GEGLU (line 304) | class GEGLU(nn.Layer):
    method __init__ (line 306) | def __init__(self, dim_in, dim_out):
    method forward (line 310) | def forward(self, x):
  class NIN (line 316) | class NIN(nn.Layer):
    method __init__ (line 318) | def __init__(self, in_dim, num_units, init_scale=0.1):
  function exists (line 328) | def exists(val):
  function default (line 332) | def default(val, d):
  class AttentionBlock (line 339) | class AttentionBlock(nn.Layer):
    method __init__ (line 347) | def __init__(
    method set_weights (line 403) | def set_weights(self, layer):
    method forward (line 430) | def forward(self, x, encoder_out=None):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/models/embeddings.py
  function get_timestep_embedding (line 22) | def get_timestep_embedding(timesteps,
  class TimestepEmbedding (line 61) | class TimestepEmbedding(nn.Layer):
    method __init__ (line 63) | def __init__(self, channel, time_embed_dim, act_fn="silu"):
    method forward (line 72) | def forward(self, sample):
  class Timesteps (line 82) | class Timesteps(nn.Layer):
    method __init__ (line 84) | def __init__(self, num_channels, flip_sin_to_cos, downscale_freq_shift):
    method forward (line 90) | def forward(self, timesteps):
  class GaussianFourierProjection (line 100) | class GaussianFourierProjection(nn.Layer):
    method __init__ (line 103) | def __init__(self, embedding_size=256, scale=1.0):
    method forward (line 112) | def forward(self, x):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/models/resnet.py
  function pad_new (line 22) | def pad_new(x, pad, mode="constant", value=0):
  class Upsample2D (line 54) | class Upsample2D(nn.Layer):
    method __init__ (line 63) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 83) | def forward(self, x):
  class Downsample2D (line 100) | class Downsample2D(nn.Layer):
    method __init__ (line 109) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 133) | def forward(self, x):
  class FirUpsample2D (line 145) | class FirUpsample2D(nn.Layer):
    method __init__ (line 147) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _upsample_2d (line 156) | def _upsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 223) | def forward(self, x):
  class FirDownsample2D (line 233) | class FirDownsample2D(nn.Layer):
    method __init__ (line 235) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _downsample_2d (line 244) | def _downsample_2d(self, x, w=None, k=None, factor=2, gain=1):
    method forward (line 286) | def forward(self, x):
  class ResnetBlock (line 296) | class ResnetBlock(nn.Layer):
    method __init__ (line 298) | def __init__(
    method forward (line 377) | def forward(self, x, temb, hey=False):
  class Mish (line 414) | class Mish(nn.Layer):
    method forward (line 416) | def forward(self, x):
  function upsample_2d (line 420) | def upsample_2d(x, k=None, factor=2, gain=1):
  function downsample_2d (line 451) | def downsample_2d(x, k=None, factor=2, gain=1):
  function upfirdn2d_native (line 483) | def upfirdn2d_native(input, kernel, up=1, down=1, pad=(0, 0)):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/models/unet_2d.py
  class UNet2DModel (line 30) | class UNet2DModel(nn.Layer, ConfigMixin):
    method __init__ (line 33) | def __init__(
    method forward (line 141) | def forward(self, sample: paddle.Tensor, timestep: Union[paddle.Tensor...

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/models/unet_2d_condition.py
  class UNet2DConditionModel (line 29) | class UNet2DConditionModel(nn.Layer, ConfigMixin):
    method __init__ (line 32) | def __init__(
    method forward (line 138) | def forward(

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/models/unet_blocks.py
  function get_down_block (line 27) | def get_down_block(
  function get_up_block (line 114) | def get_up_block(
  class UNetMidBlock2D (line 201) | class UNetMidBlock2D(nn.Layer):
    method __init__ (line 203) | def __init__(
    method forward (line 267) | def forward(self, hidden_states, temb=None, encoder_states=None):
  class UNetMidBlock2DCrossAttn (line 279) | class UNetMidBlock2DCrossAttn(nn.Layer):
    method __init__ (line 281) | def __init__(
    method forward (line 346) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class AttnDownBlock2D (line 355) | class AttnDownBlock2D(nn.Layer):
    method __init__ (line 357) | def __init__(
    method forward (line 418) | def forward(self, hidden_states, temb=None):
  class CrossAttnDownBlock2D (line 435) | class CrossAttnDownBlock2D(nn.Layer):
    method __init__ (line 437) | def __init__(
    method forward (line 499) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class DownBlock2D (line 516) | class DownBlock2D(nn.Layer):
    method __init__ (line 518) | def __init__(
    method forward (line 566) | def forward(self, hidden_states, temb=None):
  class DownEncoderBlock2D (line 582) | class DownEncoderBlock2D(nn.Layer):
    method __init__ (line 584) | def __init__(
    method forward (line 631) | def forward(self, hidden_states):
  class AttnDownEncoderBlock2D (line 642) | class AttnDownEncoderBlock2D(nn.Layer):
    method __init__ (line 644) | def __init__(
    method forward (line 702) | def forward(self, hidden_states):
  class AttnSkipDownBlock2D (line 714) | class AttnSkipDownBlock2D(nn.Layer):
    method __init__ (line 716) | def __init__(
    method forward (line 786) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class SkipDownBlock2D (line 806) | class SkipDownBlock2D(nn.Layer):
    method __init__ (line 808) | def __init__(
    method forward (line 866) | def forward(self, hidden_states, temb=None, skip_sample=None):
  class AttnUpBlock2D (line 885) | class AttnUpBlock2D(nn.Layer):
    method __init__ (line 887) | def __init__(
    method forward (line 944) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class CrossAttnUpBlock2D (line 962) | class CrossAttnUpBlock2D(nn.Layer):
    method __init__ (line 964) | def __init__(
    method forward (line 1023) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, e...
  class UpBlock2D (line 1041) | class UpBlock2D(nn.Layer):
    method __init__ (line 1043) | def __init__(
    method forward (line 1087) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
  class UpDecoderBlock2D (line 1104) | class UpDecoderBlock2D(nn.Layer):
    method __init__ (line 1106) | def __init__(
    method forward (line 1147) | def forward(self, hidden_states):
  class AttnUpDecoderBlock2D (line 1158) | class AttnUpDecoderBlock2D(nn.Layer):
    method __init__ (line 1160) | def __init__(
    method forward (line 1212) | def forward(self, hidden_states):
  class AttnSkipUpBlock2D (line 1224) | class AttnSkipUpBlock2D(nn.Layer):
    method __init__ (line 1226) | def __init__(
    method forward (line 1307) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...
  class SkipUpBlock2D (line 1335) | class SkipUpBlock2D(nn.Layer):
    method __init__ (line 1337) | def __init__(
    method forward (line 1405) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/models/vae.py
  class Encoder (line 25) | class Encoder(nn.Layer):
    method __init__ (line 27) | def __init__(
    method forward (line 86) | def forward(self, x):
  class Decoder (line 105) | class Decoder(nn.Layer):
    method __init__ (line 107) | def __init__(
    method forward (line 166) | def forward(self, z):
  class VectorQuantizer (line 185) | class VectorQuantizer(nn.Layer):
    method __init__ (line 194) | def __init__(self, n_e, e_dim, beta, remap=None, unknown_index="random...
    method remap_to_used (line 219) | def remap_to_used(self, inds):
    method unmap_to_all (line 233) | def unmap_to_all(self, inds):
    method forward (line 243) | def forward(self, z):
    method get_codebook_entry (line 279) | def get_codebook_entry(self, indices, shape):
  class DiagonalGaussianDistribution (line 297) | class DiagonalGaussianDistribution(object):
    method __init__ (line 299) | def __init__(self, parameters, deterministic=False):
    method sample (line 309) | def sample(self):
    method kl (line 313) | def kl(self, other=None):
    method nll (line 326) | def nll(self, sample, dims=[1, 2, 3]):
    method mode (line 332) | def mode(self):
  class VQModel (line 336) | class VQModel(ConfigMixin):
    method __init__ (line 339) | def __init__(
    method encode (line 383) | def encode(self, x):
    method decode (line 388) | def decode(self, h, force_not_quantize=False):
    method forward (line 398) | def forward(self, sample):
  class AutoencoderKL (line 405) | class AutoencoderKL(nn.Layer, ConfigMixin):
    method __init__ (line 408) | def __init__(
    method encode (line 446) | def encode(self, x):
    method decode (line 452) | def decode(self, z):
    method forward (line 457) | def forward(self, sample, sample_posterior=False):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_ddim.py
  function betas_for_alpha_bar (line 27) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDIMScheduler (line 50) | class DDIMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 53) | def __init__(
    method _get_variance (line 93) | def _get_variance(self, timestep, prev_timestep):
    method set_timesteps (line 103) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 110) | def step(
    method add_noise (line 172) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 181) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_ddpm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class DDPMScheduler (line 49) | class DDPMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 90) | def set_timesteps(self, num_inference_steps):
    method _get_variance (line 97) | def _get_variance(self, t, predicted_variance=None, variance_type=None):
    method step (line 130) | def step(
    method add_noise (line 181) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 190) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_karras_ve.py
  class KarrasVeScheduler (line 24) | class KarrasVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 35) | def __init__(
    method set_timesteps (line 70) | def set_timesteps(self, num_inference_steps):
    method add_noise_to_input (line 79) | def add_noise_to_input(self, sample, sigma, generator=None):
    method step (line 96) | def step(
    method step_correct (line 109) | def step_correct(
    method add_noise (line 123) | def add_noise(self, original_samples, noise, timesteps):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_lms_discrete.py
  class LMSDiscreteScheduler (line 25) | class LMSDiscreteScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 28) | def __init__(
    method get_lms_coefficient (line 65) | def get_lms_coefficient(self, order, t, current_order):
    method set_timesteps (line 82) | def set_timesteps(self, num_inference_steps):
    method step (line 97) | def step(
    method add_noise (line 125) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 132) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_pndm.py
  function betas_for_alpha_bar (line 26) | def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
  class PNDMScheduler (line 49) | class PNDMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_timesteps (line 100) | def set_timesteps(self, num_inference_steps, offset=0):
    method step (line 125) | def step(
    method step_prk (line 136) | def step_prk(
    method step_plms (line 170) | def step_plms(
    method _get_prev_sample (line 214) | def _get_prev_sample(self, sample, timestep, timestep_prev, model_outp...
    method add_noise (line 248) | def add_noise(self, original_samples, noise, timesteps):
    method __len__ (line 257) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_sde_ve.py
  class ScoreSdeVeScheduler (line 26) | class ScoreSdeVeScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 39) | def __init__(
    method set_timesteps (line 61) | def set_timesteps(self, num_inference_steps, sampling_eps=None):
    method set_sigmas (line 71) | def set_sigmas(self, num_inference_steps, sigma_min=None, sigma_max=No...
    method get_adjacent_sigma (line 89) | def get_adjacent_sigma(self, timesteps, t):
    method set_seed (line 98) | def set_seed(self, seed):
    method step_pred (line 107) | def step_pred(
    method step_correct (line 141) | def step_correct(
    method __len__ (line 171) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_sde_vp.py
  class ScoreSdeVpScheduler (line 24) | class ScoreSdeVpScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 27) | def __init__(self, num_train_timesteps=2000, beta_min=0.1, beta_max=20...
    method set_timesteps (line 33) | def set_timesteps(self, num_inference_steps):
    method step_pred (line 36) | def step_pred(self, score, x, t):
    method __len__ (line 58) | def __len__(self):

FILE: modules/image/text_to_image/stable_diffusion_waifu/diffusers/schedulers/scheduling_utils.py
  class SchedulerMixin (line 22) | class SchedulerMixin:
    method set_format (line 27) | def set_format(self, tensor_format="pd"):
    method clip (line 36) | def clip(self, tensor, min_value=None, max_value=None):
    method log (line 46) | def log(self, tensor):
    method match_shape (line 56) | def match_shape(self, values: Union[np.ndarray, paddle.Tensor], broadc...
    method norm (line 76) | def norm(self, tensor):
    method randn_like (line 85) | def randn_like(self, tensor, generator=None):
    method zeros_like (line 95) | def zeros_like(self, tensor):

FILE: modules/image/text_to_image/stable_diffusion_waifu/module.py
  class StableDiffusion (line 50) | class StableDiffusion:
    method __init__ (line 52) | def __init__(self):
    method generate_image (line 105) | def generate_image(self,
    method serving_method (line 253) | def serving_method(self, text_prompts, **kwargs):
    method run_cmd (line 261) | def run_cmd(self, argvs):
    method add_module_config_arg (line 289) | def add_module_config_arg(self):
    method add_module_input_arg (line 336) | def add_module_input_arg(self):

FILE: modules/text/embedding/fasttext_crawl_target_word-word_dim300_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/fasttext_wiki-news_target_word-word_dim300_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_twitter_target_word-word_dim100_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_twitter_target_word-word_dim200_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_twitter_target_word-word_dim25_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_twitter_target_word-word_dim50_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_wiki2014-gigaword_target_word-word_dim100_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_wiki2014-gigaword_target_word-word_dim200_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_wiki2014-gigaword_target_word-word_dim300_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/glove_wiki2014-gigaword_target_word-word_dim50_en/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-character_char1-1_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-character_char1-2_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-character_char1-4_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-ngram_1-2_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-ngram_1-3_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-ngram_2-2_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-wordLR_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-wordPosition_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_context_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-character_char1-1_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-character_char1-2_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-character_char1-4_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-ngram_1-2_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-ngram_1-3_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-ngram_2-2_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-wordLR_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-wordPosition_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_baidu_encyclopedia_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_financial_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_financial_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_financial_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_financial_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_literature_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_literature_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_literature_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_literature_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_mixed-large_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_mixed-large_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_people_daily_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_people_daily_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_people_daily_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_people_daily_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_sikuquanshu_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_sikuquanshu_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_sogou_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_sogou_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_sogou_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_sogou_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_weibo_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_weibo_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_weibo_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_weibo_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_wiki_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_wiki_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_wiki_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_wiki_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_zhihu_target_bigram-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_zhihu_target_word-bigram_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_zhihu_target_word-char_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/w2v_zhihu_target_word-word_dim300/module.py
  class Embedding (line 28) | class Embedding(TokenEmbedding):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):

FILE: modules/text/embedding/word2vec_skipgram/module.py
  function load_vocab (line 28) | def load_vocab(file_path):
  class Word2vecSkipGram (line 48) | class Word2vecSkipGram(hub.Module):
    method _initialize (line 49) | def _initialize(self):
    method context (line 57) | def context(self, trainable=False, max_seq_len=128, num_slots=1):
    method get_vocab_path (line 154) | def get_vocab_path(self):

FILE: modules/text/language_model/albert-base-v1/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 96) | def forward(self,
    method get_tokenizer (line 173) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-base-v2/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 96) | def forward(self,
    method get_tokenizer (line 173) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-chinese-base/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 94) | def forward(self,
    method get_tokenizer (line 171) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-chinese-large/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 94) | def forward(self,
    method get_tokenizer (line 171) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-chinese-small/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 94) | def forward(self,
    method get_tokenizer (line 171) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-chinese-tiny/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 94) | def forward(self,
    method get_tokenizer (line 171) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-chinese-xlarge/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 94) | def forward(self,
    method get_tokenizer (line 171) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-chinese-xxlarge/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 94) | def forward(self,
    method get_tokenizer (line 171) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-xxlarge-v1/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 95) | def forward(self,
    method get_tokenizer (line 172) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/albert-xxlarge-v2/module.py
  class Albert (line 39) | class Albert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 95) | def forward(self,
    method get_tokenizer (line 172) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/bert-base-cased/module.py
  class Bert (line 39) | class Bert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/bert-base-chinese/module.py
  class Bert (line 39) | class Bert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/bert-base-multilingual-cased/module.py
  class Bert (line 39) | class Bert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 95) | def forward(self,
    method get_tokenizer (line 172) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/bert-base-multilingual-uncased/module.py
  class Bert (line 39) | class Bert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 95) | def forward(self,
    method get_tokenizer (line 172) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/bert-base-uncased/module.py
  class Bert (line 39) | class Bert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/bert-large-cased/module.py
  class Bert (line 39) | class Bert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/bert-large-uncased/module.py
  class Bert (line 39) | class Bert(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/chinese_bert_wwm/module.py
  class BertWwm (line 39) | class BertWwm(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/chinese_bert_wwm_ext/module.py
  class BertWwm (line 39) | class BertWwm(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/chinese_electra_base/module.py
  class Electra (line 39) | class Electra(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 169) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/chinese_electra_small/module.py
  class Electra (line 39) | class Electra(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 169) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/electra_base/module.py
  class Electra (line 38) | class Electra(nn.Layer):
    method __init__ (line 43) | def __init__(
    method forward (line 92) | def forward(self,
    method get_tokenizer (line 168) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/electra_large/module.py
  class Electra (line 38) | class Electra(nn.Layer):
    method __init__ (line 43) | def __init__(
    method forward (line 92) | def forward(self,
    method get_tokenizer (line 168) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/electra_small/module.py
  class Electra (line 38) | class Electra(nn.Layer):
    method __init__ (line 43) | def __init__(
    method forward (line 92) | def forward(self,
    method get_tokenizer (line 168) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/ernie/module.py
  class Ernie (line 39) | class Ernie(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/ernie_tiny/module.py
  class ErnieTiny (line 38) | class ErnieTiny(nn.Layer):
    method __init__ (line 43) | def __init__(
    method forward (line 92) | def forward(self,
    method get_tokenizer (line 169) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/ernie_v2_eng_base/module.py
  class ErnieV2 (line 41) | class ErnieV2(nn.Layer):
    method __init__ (line 46) | def __init__(
    method forward (line 97) | def forward(self,
    method get_tokenizer (line 174) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/ernie_v2_eng_large/module.py
  class ErnieV2 (line 39) | class ErnieV2(nn.Layer):
    method __init__ (line 44) | def __init__(
    method forward (line 93) | def forward(self,
    method get_tokenizer (line 170) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/lda_news/config.py
  class ModelType (line 6) | class ModelType:
  class ModelConfig (line 11) | class ModelConfig:

FILE: modules/text/language_model/lda_news/document.py
  class Topic (line 4) | class Topic(object):
    method __init__ (line 9) | def __init__(self, tid, prob):
  class Token (line 14) | class Token(object):
    method __init__ (line 19) | def __init__(self, topic, id):
  class Sentence (line 24) | class Sentence(object):
    method __init__ (line 29) | def __init__(self, topic, tokens):
  class LDADoc (line 34) | class LDADoc(object):
    method __init__ (line 38) | def __init__(self):
    method init (line 46) | def init(self, num_topics):
    method add_token (line 55) | def add_token(self, token):
    method token (line 65) | def token(self, index):
    method set_topic (line 68) | def set_topic(self, index, new_topic):
    method set_alpha (line 81) | def set_alpha(self, alpha):
    method size (line 84) | def size(self):
    method topic_sum (line 89) | def topic_sum(self, topic_id):
    method sparse_topic_dist (line 92) | def sparse_topic_dist(self, sort=True):
    method dense_topic_dist (line 116) | def dense_topic_dist(self):
    method accumulate_topic_num (line 127) | def accumulate_topic_num(self):
  class SLDADoc (line 132) | class SLDADoc(LDADoc):
    method __init__ (line 137) | def __init__(self):
    method init (line 141) | def init(self, num_topics):
    method add_sentence (line 150) | def add_sentence(self, sent):
    method set_topic (line 160) | def set_topic(self, index, new_topic):
    method size (line 170) | def size(self):
    method sent (line 175) | def sent(self, index):

FILE: modules/text/language_model/lda_news/inference_engine.py
  class SamplerType (line 13) | class SamplerType:
  class InferenceEngine (line 18) | class InferenceEngine(object):
    method __init__ (line 19) | def __init__(self, model_dir, conf_file, type=SamplerType.MetropolisHa...
    method infer (line 33) | def infer(self, input, doc):
    method lda_infer (line 64) | def lda_infer(self, doc, burn_in_iter, total_iter):
    method slda_infer (line 74) | def slda_infer(self, doc, burn_in_iter, total_iter):
    method model_type (line 84) | def model_type(self):
    method get_model (line 87) | def get_model(self):
    method get_config (line 90) | def get_config(self):

FILE: modules/text/language_model/lda_news/model.py
  class TopicModel (line 11) | class TopicModel(object):
    method __init__ (line 15) | def __init__(self, model_dir, config):
    method term_id (line 35) | def term_id(self, term):
    method load_model (line 38) | def load_model(self, word_topic_path, vocab_path):
    method word_topic_value (line 49) | def word_topic_value(self, word_id, topic_id):
    method word_topic (line 57) | def word_topic(self, term_id):
    method topic_sum_value (line 62) | def topic_sum_value(self, topic_id):
    method topic_sum (line 65) | def topic_sum(self):
    method num_topics (line 68) | def num_topics(self):
    method vocab_size (line 71) | def vocab_size(self):
    method alpha (line 74) | def alpha(self):
    method alpha_sum (line 77) | def alpha_sum(self):
    method beta (line 80) | def beta(self):
    method beta_sum (line 83) | def beta_sum(self):
    method type (line 86) | def type(self):
    method __load_word_dict (line 89) | def __load_word_dict(self, word_dict_path):
    method get_vocab (line 119) | def get_vocab(self):
    method topic_words (line 122) | def topic_words(self):

FILE: modules/text/language_model/lda_news/module.py
  class TopicModel (line 23) | class TopicModel(hub.Module):
    method _initialize (line 24) | def _initialize(self):
    method cal_doc_distance (line 49) | def cal_doc_distance(self, doc_text1, doc_text2):
    method cal_doc_keywords_similarity (line 80) | def cal_doc_keywords_similarity(self, document, top_k=10):
    method cal_query_doc_similarity (line 126) | def cal_query_doc_similarity(self, query, document):
    method infer_doc_topic_distribution (line 150) | def infer_doc_topic_distribution(self, document):
    method show_topic_keywords (line 171) | def show_topic_keywords(self, topic_id, k=10):

FILE: modules/text/language_model/lda_news/sampler.py
  class Sampler (line 10) | class Sampler(object):
    method __init__ (line 11) | def __init__(self):
    method sample_doc (line 14) | def sample_doc(self, doc):
  class MHSampler (line 20) | class MHSampler(Sampler):
    method __init__ (line 21) | def __init__(self, model):
    method __construct_alias_table (line 32) | def __construct_alias_table(self):
    method sample_doc (line 64) | def sample_doc(self, doc):
    method __sample_token (line 74) | def __sample_token(self, doc, token):
    method __sample_sentence (line 81) | def __sample_sentence(self, doc, sent):
    method __doc_proposal (line 88) | def __doc_proposal(self, doc, token):
    method __word_proposal (line 132) | def __word_proposal(self, doc, token, old_topic):
    method __proportional_function (line 162) | def __proportional_function(self, doc, token, new_topic):
    method __word_proposal_distribution (line 192) | def __word_proposal_distribution(self, word_id, topic):
    method __doc_proposal_distribution (line 197) | def __doc_proposal_distribution(self, doc, topic):
    method __propose (line 200) | def __propose(self, word_id):
  class GibbsSampler (line 210) | class GibbsSampler(Sampler):
    method __init__ (line 211) | def __init__(self, model):
    method sample_doc (line 215) | def sample_doc(self, doc):
    method __sample_token (line 225) | def __sample_token(self, doc, token):
    method __sample_sentence (line 252) | def __sample_sentence(self, doc, sent):

FILE: modules/text/language_model/lda_news/semantic_matching.py
  class WordAndDis (line 8) | class WordAndDis(object):
    method __init__ (line 9) | def __init__(self):
  class SemanticMatching (line 14) | class SemanticMatching(object):
    method __init__ (line 15) | def __init__(self):
    method l2_norm (line 18) | def l2_norm(self, vec):
    method cosine_similarity (line 24) | def cosine_similarity(self, vec1, vec2):
    method likelihood_based_similarity (line 32) | def likelihood_based_similarity(self, terms, doc_topic_dist, model):
    method kullback_leibler_divergence (line 56) | def kullback_leibler_divergence(self, dist1, dist2):
    method jensen_shannon_divergence (line 62) | def jensen_shannon_divergence(self, dist1, dist2):
    method hellinger_distance (line 71) | def hellinger_distance(self, dist1, dist2):

FILE: modules/text/language_model/lda_news/tokenizer.py
  class Tokenizer (line 5) | class Tokenizer(object):
    method __init__ (line 9) | def __init__(self):
    method tokenize (line 12) | def tokenize(self, text):
  class SimpleTokenizer (line 16) | class SimpleTokenizer(Tokenizer):
    method __init__ (line 23) | def __init__(self, vocab_path):
    method tokenize (line 29) | def tokenize(self, text):
    method contains (line 59) | def contains(self, word):
    method __load_vocab (line 64) | def __load_vocab(self, vocab_path):
    method __is_eng_char (line 77) | def __is_eng_char(self, c):
    method __tolower (line 82) | def __tolower(self, c):
  class LACTokenizer (line 89) | class LACTokenizer(Tokenizer):
    method __init__ (line 90) | def __init__(self, vocab_path, lac):
    method __load_vocab (line 97) | def __load_vocab(self, vocab_path):
    method tokenize (line 110) | def tokenize(self, text):
    method contains (line 122) | def contains(self, word):

FILE: modules/text/language_model/lda_news/util.py
  function load_prototxt (line 10) | def load_prototxt(config_file, config):
  function fix_random_seed (line 32) | def fix_random_seed(seed=2147483647):
  function rand (line 36) | def rand(min_=0, max_=1):
  function rand_k (line 40) | def rand_k(k):
  function timeit (line 46) | def timeit(f):

FILE: modules/text/language_model/lda_news/vocab.py
  class WordCount (line 6) | class WordCount(object):
    method __init__ (line 7) | def __init__(self, word_id, count):
  class Vocab (line 12) | class Vocab(object):
    method __init__ (line 13) | def __init__(self):
    method get_id (line 17) | def get_id(self, word):
    method load (line 22) | def load(self, vocab_file):
    method size (line 37) | def size(self):
    method vocabulary (line 40) | def vocabulary(self):

FILE: modules/text/language_model/lda_news/vose_alias.py
  class VoseAlias (line 6) | class VoseAlias(object):
    method __init__ (line 10) | def __init__(self):
    method initialize (line 14) | def initialize(self, distribution):
    method generate (line 54) | def generate(self):
    method size (line 61) | def size(self):

FILE: modules/text/language_model/lda_novel/config.py
  class ModelType (line 6) | class ModelType:
  class ModelConfig (line 11) | class ModelConfig:

FILE: modules/text/language_model/lda_novel/document.py
  class Topic (line 4) | class Topic(object):
    method __init__ (line 9) | def __init__(self, tid, prob):
  class Token (line 14) | class Token(object):
    method __init__ (line 19) | def __init__(self, topic, id):
  class Sentence (line 24) | class Sentence(object):
    method __init__ (line 29) | def __init__(self, topic, tokens):
  class LDADoc (line 34) | class LDADoc(object):
    method __init__ (line 38) | def __init__(self):
    method init (line 46) | def init(self, num_topics):
    method add_token (line 55) | def add_token(self, token):
    method token (line 65) | def token(self, index):
    method set_topic (line 68) | def set_topic(self, index, new_topic):
    method set_alpha (line 81) | def set_alpha(self, alpha):
    method size (line 84) | def size(self):
    method topic_sum (line 89) | def topic_sum(self, topic_id):
    method sparse_topic_dist (line 92) | def sparse_topic_dist(self, sort=True):
    method dense_topic_dist (line 116) | def dense_topic_dist(self):
    method accumulate_topic_num (line 127) | def accumulate_topic_num(self):
  class SLDADoc (line 132) | class SLDADoc(LDADoc):
    method __init__ (line 137) | def __init__(self):
    method init (line 141) | def init(self, num_topics):
    method add_sentence (line 150) | def add_sentence(self, sent):
    method set_topic (line 160) | def set_topic(self, index, new_topic):
    method size (line 170) | def size(self):
    method sent (line 175) | def sent(self, index):

FILE: modules/text/language_model/lda_novel/inference_engine.py
  class SamplerType (line 13) | class SamplerType:
  class InferenceEngine (line 18) | class InferenceEngine(object):
    method __init__ (line 19) | def __init__(self, model_dir, conf_file, type=SamplerType.MetropolisHa...
    method infer (line 33) | def infer(self, input, doc):
    method lda_infer (line 64) | def lda_infer(self, doc, burn_in_iter, total_iter):
    method slda_infer (line 74) | def slda_infer(self, doc, burn_in_iter, total_iter):
    method model_type (line 84) | def model_type(self):
    method get_model (line 87) | def get_model(self):
    method get_config (line 90) | def get_config(self):

FILE: modules/text/language_model/lda_novel/model.py
  class TopicModel (line 11) | class TopicModel(object):
    method __init__ (line 15) | def __init__(self, model_dir, config):
    method term_id (line 35) | def term_id(self, term):
    method load_model (line 38) | def load_model(self, word_topic_path, vocab_path):
    method word_topic_value (line 49) | def word_topic_value(self, word_id, topic_id):
    method word_topic (line 57) | def word_topic(self, term_id):
    method topic_sum_value (line 62) | def topic_sum_value(self, topic_id):
    method topic_sum (line 65) | def topic_sum(self):
    method num_topics (line 68) | def num_topics(self):
    method vocab_size (line 71) | def vocab_size(self):
    method alpha (line 74) | def alpha(self):
    method alpha_sum (line 77) | def alpha_sum(self):
    method beta (line 80) | def beta(self):
    method beta_sum (line 83) | def beta_sum(self):
    method type (line 86) | def type(self):
    method __load_word_dict (line 89) | def __load_word_dict(self, word_dict_path):
    method get_vocab (line 119) | def get_vocab(self):
    method topic_words (line 122) | def topic_words(self):

FILE: modules/text/language_model/lda_novel/module.py
  class TopicModel (line 23) | class TopicModel(hub.Module):
    method _initialize (line 24) | def _initialize(self):
    method cal_doc_distance (line 49) | def cal_doc_distance(self, doc_text1, doc_text2):
    method cal_doc_keywords_similarity (line 80) | def cal_doc_keywords_similarity(self, document, top_k=10):
    method cal_query_doc_similarity (line 126) | def cal_query_doc_similarity(self, query, document):
    method infer_doc_topic_distribution (line 150) | def infer_doc_topic_distribution(self, document):
    method show_topic_keywords (line 171) | def show_topic_keywords(self, topic_id, k=10):

FILE: modules/text/language_model/lda_novel/sampler.py
  class Sampler (line 12) | class Sampler(object):
    method __init__ (line 13) | def __init__(self):
    method sample_doc (line 16) | def sample_doc(self, doc):
  class MHSampler (line 22) | class MHSampler(Sampler):
    method __init__ (line 23) | def __init__(self, model):
    method __construct_alias_table (line 34) | def __construct_alias_table(self):
    method sample_doc (line 66) | def sample_doc(self, doc):
    method __sample_token (line 76) | def __sample_token(self, doc, token):
    method __sample_sentence (line 83) | def __sample_sentence(self, doc, sent):
    method __doc_proposal (line 90) | def __doc_proposal(self, doc, token):
    method __word_proposal (line 134) | def __word_proposal(self, doc, token, old_topic):
    method __proportional_function (line 164) | def __proportional_function(self, doc, token, new_topic):
    method __word_proposal_distribution (line 194) | def __word_proposal_distribution(self, word_id, topic):
    method __doc_proposal_distribution (line 199) | def __doc_proposal_distribution(self, doc, topic):
    method __propose (line 202) | def __propose(self, word_id):
  class GibbsSampler (line 212) | class GibbsSampler(Sampler):
    method __init__ (line 213) | def __init__(self, model):
    method sample_doc (line 217) | def sample_doc(self, doc):
    method __sample_token (line 227) | def __sample_token(self, doc, token):
    method __sample_sentence (line 254) | def __sample_sentence(self, doc, sent):

FILE: modules/text/language_model/lda_novel/semantic_matching.py
  class WordAndDis (line 11) | class WordAndDis(object):
    method __init__ (line 12) | def __init__(self):
  class SemanticMatching (line 17) | class SemanticMatching(object):
    method __init__ (line 18) | def __init__(self):
    method l2_norm (line 21) | def l2_norm(self, vec):
    method cosine_similarity (line 27) | def cosine_similarity(self, vec1, vec2):
    method likelihood_based_similarity (line 33) | def likelihood_based_similarity(self, terms, doc_topic_dist, model):
    method kullback_leibler_divergence (line 57) | def kullback_leibler_divergence(self, dist1, dist2):
    method jensen_shannon_divergence (line 63) | def jensen_shannon_divergence(self, dist1, dist2):
    method hellinger_distance (line 72) | def hellinger_distance(self, dist1, dist2):

FILE: modules/text/language_model/lda_novel/tokenizer.py
  class Tokenizer (line 7) | class Tokenizer(object):
    method __init__ (line 11) | def __init__(self):
    method tokenize (line 14) | def tokenize(self, text):
  class SimpleTokenizer (line 18) | class SimpleTokenizer(Tokenizer):
    method __init__ (line 25) | def __init__(self, vocab_path):
    method tokenize (line 31) | def tokenize(self, text):
    method contains (line 61) | def contains(self, word):
    method __load_vocab (line 66) | def __load_vocab(self, vocab_path):
    method __is_eng_char (line 79) | def __is_eng_char(self, c):
    method __tolower (line 84) | def __tolower(self, c):
  class LACTokenizer (line 91) | class LACTokenizer(Tokenizer):
    method __init__ (line 92) | def __init__(self, vocab_path, lac):
    method __load_vocab (line 99) | def __load_vocab(self, vocab_path):
    method tokenize (line 112) | def tokenize(self, text):
    method contains (line 124) | def contains(self, word):

FILE: modules/text/language_model/lda_novel/util.py
  function load_prototxt (line 10) | def load_prototxt(config_file, config):
  function fix_random_seed (line 32) | def fix_random_seed(seed=2147483647):
  function rand (line 36) | def rand(min_=0, max_=1):
  function rand_k (line 40) | def rand_k(k):
  function timeit (line 46) | def timeit(f):

FILE: modules/text/language_model/lda_novel/vocab.py
  class WordCount (line 6) | class WordCount(object):
    method __init__ (line 7) | def __init__(self, word_id, count):
  class Vocab (line 12) | class Vocab(object):
    method __init__ (line 13) | def __init__(self):
    method get_id (line 17) | def get_id(self, word):
    method load (line 22) | def load(self, vocab_file):
    method size (line 37) | def size(self):
    method vocabulary (line 40) | def vocabulary(self):

FILE: modules/text/language_model/lda_novel/vose_alias.py
  class VoseAlias (line 9) | class VoseAlias(object):
    method __init__ (line 13) | def __init__(self):
    method initialize (line 17) | def initialize(self, distribution):
    method generate (line 57) | def generate(self):
    method size (line 64) | def size(self):

FILE: modules/text/language_model/lda_webpage/config.py
  class ModelType (line 6) | class ModelType:
  class ModelConfig (line 11) | class ModelConfig:

FILE: modules/text/language_model/lda_webpage/document.py
  class Topic (line 4) | class Topic(object):
    method __init__ (line 9) | def __init__(self, tid, prob):
  class Token (line 14) | class Token(object):
    method __init__ (line 19) | def __init__(self, topic, id):
  class Sentence (line 24) | class Sentence(object):
    method __init__ (line 29) | def __init__(self, topic, tokens):
  class LDADoc (line 34) | class LDADoc(object):
    method __init__ (line 38) | def __init__(self):
    method init (line 46) | def init(self, num_topics):
    method add_token (line 55) | def add_token(self, token):
    method token (line 65) | def token(self, index):
    method set_topic (line 68) | def set_topic(self, index, new_topic):
    method set_alpha (line 81) | def set_alpha(self, alpha):
    method size (line 84) | def size(self):
    method topic_sum (line 89) | def topic_sum(self, topic_id):
    method sparse_topic_dist (line 92) | def sparse_topic_dist(self, sort=True):
    method dense_topic_dist (line 116) | def dense_topic_dist(self):
    method accumulate_topic_num (line 127) | def accumulate_topic_num(self):
  class SLDADoc (line 132) | class SLDADoc(LDADoc):
    method __init__ (line 137) | def __init__(self):
    method init (line 141) | def init(self, num_topics):
    method add_sentence (line 150) | def add_sentence(self, sent):
    method set_topic (line 160) | def set_topic(self, index, new_topic):
    method size (line 170) | def size(self):
    method sent (line 175) | def sent(self, index):

FILE: modules/text/language_model/lda_webpage/inference_engine.py
  class SamplerType (line 13) | class SamplerType:
  class InferenceEngine (line 18) | class InferenceEngine(object):
    method __init__ (line 19) | def __init__(self, model_dir, conf_file, type=SamplerType.MetropolisHa...
    method infer (line 33) | def infer(self, input, doc):
    method lda_infer (line 64) | def lda_infer(self, doc, burn_in_iter, total_iter):
    method slda_infer (line 74) | def slda_infer(self, doc, burn_in_iter, total_iter):
    method model_type (line 84) | def model_type(self):
    method get_model (line 87) | def get_model(self):
    method get_config (line 90) | def get_config(self):

FILE: modules/text/language_model/lda_webpage/model.py
  class TopicModel (line 11) | class TopicModel(object):
    method __init__ (line 15) | def __init__(self, model_dir, config):
    method term_id (line 35) | def term_id(self, term):
    method load_model (line 38) | def load_model(self, word_topic_path, vocab_path):
    method word_topic_value (line 49) | def word_topic_value(self, word_id, topic_id):
    method word_topic (line 57) | def word_topic(self, term_id):
    method topic_sum_value (line 62) | def topic_sum_value(self, topic_id):
    method topic_sum (line 65) | def topic_sum(self):
    method num_topics (line 68) | def num_topics(self):
    method vocab_size (line 71) | def vocab_size(self):
    method alpha (line 74) | def alpha(self):
    method alpha_sum (line 77) | def alpha_sum(self):
    method beta (line 80) | def beta(self):
    method beta_sum (line 83) | def beta_sum(self):
    method type (line 86) | def type(self):
    method __load_word_dict (line 89) | def __load_word_dict(self, word_dict_path):
    method get_vocab (line 119) | def get_vocab(self):
    method topic_words (line 122) | def topic_words(self):

FILE: modules/text/language_model/lda_webpage/module.py
  class TopicModel (line 23) | class TopicModel(hub.Module):
    method _initialize (line 24) | def _initialize(self):
    method cal_doc_distance (line 49) | def cal_doc_distance(self, doc_text1, doc_text2):
    method cal_doc_keywords_similarity (line 80) | def cal_doc_keywords_similarity(self, document, top_k=10):
    method cal_query_doc_similarity (line 126) | def cal_query_doc_similarity(self, query, document):
    method infer_doc_topic_distribution (line 149) | def infer_doc_topic_distribution(self, document):
    method show_topic_keywords (line 170) | def show_topic_keywords(self, topic_id, k=10):

FILE: modules/text/language_model/lda_webpage/sampler.py
  class Sampler (line 12) | class Sampler(object):
    method __init__ (line 13) | def __init__(self):
    method sample_doc (line 16) | def sample_doc(self, doc):
  class MHSampler (line 22) | class MHSampler(Sampler):
    method __init__ (line 23) | def __init__(self, model):
    method __construct_alias_table (line 34) | def __construct_alias_table(self):
    method sample_doc (line 66) | def sample_doc(self, doc):
    method __sample_token (line 76) | def __sample_token(self, doc, token):
    method __sample_sentence (line 83) | def __sample_sentence(self, doc, sent):
    method __doc_proposal (line 90) | def __doc_proposal(self, doc, token):
    method __word_proposal (line 134) | def __word_proposal(self, doc, token, old_topic):
    method __proportional_function (line 164) | def __proportional_function(self, doc, token, new_topic):
    method __word_proposal_distribution (line 194) | def __word_proposal_distribution(self, word_id, topic):
    method __doc_proposal_distribution (line 199) | def __doc_proposal_distribution(self, doc, topic):
    method __propose (line 202) | def __propose(self, word_id):
  class GibbsSampler (line 212) | class GibbsSampler(Sampler):
    method __init__ (line 213) | def __init__(self, model):
    method sample_doc (line 217) | def sample_doc(self, doc):
    method __sample_token (line 227) | def __sample_token(self, doc, token):
    method __sample_sentence (line 254) | def __sample_sentence(self, doc, sent):

FILE: modules/text/language_model/lda_webpage/semantic_matching.py
  class WordAndDis (line 11) | class WordAndDis(object):
    method __init__ (line 12) | def __init__(self):
  class SemanticMatching (line 17) | class SemanticMatching(object):
    method __init__ (line 18) | def __init__(self):
    method l2_norm (line 21) | def l2_norm(self, vec):
    method cosine_similarity (line 27) | def cosine_similarity(self, vec1, vec2):
    method likelihood_based_similarity (line 33) | def likelihood_based_similarity(self, terms, doc_topic_dist, model):
    method kullback_leibler_divergence (line 57) | def kullback_leibler_divergence(self, dist1, dist2):
    method jensen_shannon_divergence (line 63) | def jensen_shannon_divergence(self, dist1, dist2):
    method hellinger_distance (line 72) | def hellinger_distance(self, dist1, dist2):

FILE: modules/text/language_model/lda_webpage/tokenizer.py
  class Tokenizer (line 7) | class Tokenizer(object):
    method __init__ (line 11) | def __init__(self):
    method tokenize (line 14) | def tokenize(self, text):
  class SimpleTokenizer (line 18) | class SimpleTokenizer(Tokenizer):
    method __init__ (line 25) | def __init__(self, vocab_path):
    method tokenize (line 31) | def tokenize(self, text):
    method contains (line 61) | def contains(self, word):
    method __load_vocab (line 66) | def __load_vocab(self, vocab_path):
    method __is_eng_char (line 79) | def __is_eng_char(self, c):
    method __tolower (line 84) | def __tolower(self, c):
  class LACTokenizer (line 91) | class LACTokenizer(Tokenizer):
    method __init__ (line 92) | def __init__(self, vocab_path, lac):
    method __load_vocab (line 99) | def __load_vocab(self, vocab_path):
    method tokenize (line 112) | def tokenize(self, text):
    method contains (line 124) | def contains(self, word):

FILE: modules/text/language_model/lda_webpage/util.py
  function load_prototxt (line 10) | def load_prototxt(config_file, config):
  function fix_random_seed (line 32) | def fix_random_seed(seed=2147483647):
  function rand (line 36) | def rand(min_=0, max_=1):
  function rand_k (line 40) | def rand_k(k):
  function timeit (line 46) | def timeit(f):

FILE: modules/text/language_model/lda_webpage/vocab.py
  class WordCount (line 6) | class WordCount(object):
    method __init__ (line 7) | def __init__(self, word_id, count):
  class Vocab (line 12) | class Vocab(object):
    method __init__ (line 13) | def __init__(self):
    method get_id (line 17) | def get_id(self, word):
    method load (line 22) | def load(self, vocab_file):
    method size (line 37) | def size(self):
    method vocabulary (line 40) | def vocabulary(self):

FILE: modules/text/language_model/lda_webpage/vose_alias.py
  class VoseAlias (line 9) | class VoseAlias(object):
    method __init__ (line 13) | def __init__(self):
    method initialize (line 17) | def initialize(self, distribution):
    method generate (line 57) | def generate(self):
    method size (line 64) | def size(self):

FILE: modules/text/language_model/rbt3/module.py
  class Roberta (line 41) | class Roberta(nn.Layer):
    method __init__ (line 46) | def __init__(
    method forward (line 98) | def forward(self,
    method get_tokenizer (line 175) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/rbtl3/module.py
  class Roberta (line 41) | class Roberta(nn.Layer):
    method __init__ (line 46) | def __init__(
    method forward (line 98) | def forward(self,
    method get_tokenizer (line 175) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/roberta-wwm-ext-large/module.py
  class Roberta (line 42) | class Roberta(nn.Layer):
    method __init__ (line 47) | def __init__(
    method forward (line 97) | def forward(self,
    method get_tokenizer (line 174) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/roberta-wwm-ext/module.py
  class Roberta (line 42) | class Roberta(nn.Layer):
    method __init__ (line 47) | def __init__(
    method forward (line 97) | def forward(self,
    method get_tokenizer (line 174) | def get_tokenizer(*args, **kwargs):

FILE: modules/text/language_model/simnet_bow/module.py
  class DataFormatError (line 30) | class DataFormatError(Exception):
    method __init__ (line 32) | def __init__(self, *args):
  class SimnetBow (line 42) | class SimnetBow(hub.Module):
    method _initialize (line 44) | def _initialize(self):
    method word_seg_module (line 57) | def word_seg_module(self):
    method _set_config (line 65) | def _set_config(self):
    method _texts_process (line 87) | def _texts_process(self, texts):
    method to_unicode (line 95) | def to_unicode(self, texts):
    method check_data (line 114) | def check_data(self, texts=[], data={}):
    method similarity (line 144) | def similarity(self, texts=[], data={}, use_gpu=False, batch_size=1):
    method run_cmd (line 208) | def run_cmd(self, argvs):
    method add_module_config_arg (line 236) | def add_module_config_arg(self):
    method add_module_input_arg (line 247) | def add_module_input_arg(self):
    method check_input_data (line 255) | def check_input_data(self, args):
    method get_vocab_path (line 281) | def get_vocab_path(self):

FILE: modules/text/language_model/simnet_bow/processor.py
  function load_vocab (line 5) | def load_vocab(file_path):
  function preprocess (line 24) | def preprocess(lac, word_dict, data_dict, use_gpu=False, batch_size=1):
  function postprocess (line 49) | def postprocess(pred, data_info):

FILE: modules/text/language_model/slda_news/config.py
  class ModelType (line 6) | class ModelType:
  class ModelConfig (line 11) | class ModelConfig:

FILE: modules/text/language_model/slda_news/document.py
  class Topic (line 4) | class Topic(object):
    method __init__ (line 9) | def __init__(self, tid, prob):
  class Token (line 14) | class Token(object):
    method __init__ (line 19) | def __init__(self, topic, id):
  class Sentence (line 24) | class Sentence(object):
    method __init__ (line 29) | def __init__(self, topic, tokens):
  class LDADoc (line 34) | class LDADoc(object):
    method __init__ (line 38) | def __init__(self):
    method init (line 46) | def init(self, num_topics):
    method add_token (line 55) | def add_token(self, token):
    method token (line 65) | def token(self, index):
    method set_topic (line 68) | def set_topic(self, index, new_topic):
    method set_alpha (line 81) | def set_alpha(self, alpha):
    method size (line 84) | def size(self):
    method topic_sum (line 89) | def topic_sum(self, topic_id):
    method sparse_topic_dist (line 92) | def sparse_topic_dist(self, sort=True):
    method dense_topic_dist (line 116) | def dense_topic_dist(self):
    method accumulate_topic_num (line 127) | def accumulate_topic_num(self):
  class SLDADoc (line 132) | class SLDADoc(LDADoc):
    method __init__ (line 137) | def __init__(self):
    method init (line 141) | def init(self, num_topics):
    method add_sentence (line 150) | def add_sentence(self, sent):
    method set_topic (line 160) | def set_topic(self, index, new_topic):
    method size (line 170) | def size(self):
    method sent (line 175) | def sent(self, index):

FILE: modules/text/language_model/slda_news/inference_engine.py
  class SamplerType (line 13) | class SamplerType:
  class InferenceEngine (line 18) | class InferenceEngine(object):
    method __init__ (line 19) | def __init__(self, model_dir, conf_file, type=SamplerType.MetropolisHa...
    method infer (line 33) | def infer(self, input, doc):
    method lda_infer (line 64) | def lda_infer(self, doc, burn_in_iter, total_iter):
    method slda_infer (line 74) | def slda_infer(self, doc, burn_in_iter, total_iter):
    method model_type (line 84) | def model_type(self):
    method get_model (line 87) | def get_model(self):
    method get_config (line 90) | def get_config(self):

FILE: modules/text/language_model/slda_news/model.py
  class TopicModel (line 11) | class TopicModel(object):
    method __init__ (line 15) | def __init__(self, model_dir, config):
    method term_id (line 35) | def term_id(self, term):
    method load_model (line 38) | def load_model(self, word_topic_path, vocab_path):
    method word_topic_value (line 49) | def word_topic_value(self, word_id, topic_id):
    method word_topic (line 57) | def word_topic(self, term_id):
    method topic_sum_value (line 62) | def topic_sum_value(self, topic_id):
    method topic_sum (line 65) | def topic_sum(self):
    method num_topics (line 68) | def num_topics(self):
    method vocab_size (line 71) | def vocab_size(self):
    method alpha (line 74) | def alpha(self):
    method alpha_sum (line 77) | def alpha_sum(self):
    method beta (line 80) | def beta(self):
    method beta_sum (line 83) | def beta_sum(self):
    method type (line 86) | def type(self):
    method __load_word_dict (line 89) | def __load_word_dict(self, word_dict_path):
    method get_vocab (line 119) | def get_vocab(self):
    method topic_words (line 122) | def topic_words(self):

FILE: modules/text/language_model/slda_news/module.py
  class TopicModel (line 23) | class TopicModel(hub.Module):
    method _initialize (line 24) | def _initialize(self):
    method infer_doc_topic_distribution (line 48) | def infer_doc_topic_distribution(self, document):
    method show_topic_keywords (line 78) | def show_topic_keywords(self, topic_id, k=10):

FILE: modules/text/language_model/slda_news/sampler.py
  class Sampler (line 12) | class Sampler(object):
    method __init__ (line 13) | def __init__(self):
    method sample_doc (line 16) | def sample_doc(self, doc):
  class MHSampler (line 22) | class MHSampler(Sampler):
    method __init__ (line 23) | def __init__(self, model):
    method __construct_alias_table (line 34) | def __construct_alias_table(self):
    method sample_doc (line 66) | def sample_doc(self, doc):
    method __sample_token (line 76) | def __sample_token(self, doc, token):
    method __sample_sentence (line 83) | def __sample_sentence(self, doc, sent):
    method __doc_proposal (line 90) | def __doc_proposal(self, doc, token):
    method __word_proposal (line 134) | def __word_proposal(self, doc, token, old_topic):
    method __proportional_function (line 164) | def __proportional_function(self, doc, token, new_topic):
    method __word_proposal_distribution (line 194) | def __word_proposal_distribution(self, word_id, topic):
    method __doc_proposal_distribution (line 199) | def __doc_proposal_distribution(self, doc, topic):
    method __propose (line 202) | def __propose(self, word_id):
  class GibbsSampler (line 212) | class GibbsSampler(Sampler):
    method __init__ (line 213) | def __init__(self, model):
    method sample_doc (line 217) | def sample_doc(self, doc):
    method __sample_token (line 227) | def __sample_token(self, doc, token):
    method __sample_sentence (line 254) | def __sample_sentence(self, doc, sent):

FILE: modules/text/language_model/slda_news/semantic_matching.py
  class WordAndDis (line 11) | class WordAndDis(object):
    method __init__ (line 12) | def __init__(self):
  class SemanticMatching (line 17) | class SemanticMatching(object):
    method __init__ (line 18) | def __init__(self):
    method l2_norm (line 21) | def l2_norm(self, vec):
    method cosine_similarity (line 27) | def cosine_similarity(self, vec1, vec2):
    method likelihood_based_similarity (line 33) | def likelihood_based_similarity(self, terms, doc_topic_dist, model):
    method kullback_leibler_divergence (line 57) | def kullback_leibler_divergence(self, dist1, dist2):
    method jensen_shannon_divergence (line 63) | def jensen_shannon_divergence(self, dist1, dist2):
    method hellinger_distance (line 72) | def hellinger_distance(self, dist1, dist2):

FILE: modules/text/language_model/slda_news/tokenizer.py
  class Tokenizer (line 7) | class Tokenizer(object):
    method __init__ (line 11) | def __init__(self):
    method tokenize (line 14) | def tokenize(self, text):
  class SimpleTokenizer (line 18) | class SimpleTokenizer(Tokenizer):
    method __init__ (line 25) | def __init__(self, vocab_path):
    method tokenize (line 31) | def tokenize(self, text):
    method contains (line 61) | def contains(self, word):
    method __load_vocab (line 66) | def __load_vocab(self, vocab_path):
    method __is_eng_char (line 79) | def __is_eng_char(self, c):
    method __tolower (line 84) | def __tolower(self, c):
  class LACTokenizer (line 91) | class LACTokenizer(Tokenizer):
    method __init__ (line 92) | def __init__(self, vocab_path, lac):
    method __load_vocab (line 99) | def __load_vocab(self, vocab_path):
    method tokenize (line 112) | def tokenize(self, text):
    method contains (line 124) | def contains(self, word):

FILE: modules/text/language_model/slda_news/util.py
  function load_prototxt (line 10) | def load_prototxt(config_file, config):
  function fix_random_seed (line 32) | def fix_random_seed(seed=2147483647):
  function rand (line 36) | def rand(min_=0, max_=1):
  function rand_k (line 40) | def rand_k(k):
  function timeit (line 46) | def timeit(f):

FILE: modules/text/language_model/slda_news/vocab.py
  class WordCount (line 6) | class WordCount(object):
    method __init__ (line 7) | def __init__(self, word_id, count):
  class Vocab (line 12) | class Vocab(object):
    method __init__ (line 13) | def __init__(self):
    method get_id (line 17) | def get_id(self, word):
    method load (line 22) | def load(self, vocab_file):
    method size (line 37) | def size(self):
    method vocabulary (line 40) | def vocabulary(self):

FILE: modules/text/language_model/slda_news/vose_alias.py
  class VoseAlias (line 9) | class VoseAlias(object):
    method __init__ (line 13) | def __init__(self):
    method initialize (line 17) | def initialize(self, distribution):
    method generate (line 57) | def generate(self):
    method size (line 64) | def size(self):

FILE: modules/text/language_model/slda_novel/config.py
  class ModelType (line 6) | class ModelType:
  class ModelConfig (line 11) | class ModelConfig:

FILE: modules/text/language_model/slda_novel/document.py
  class Topic (line 4) | class Topic(object):
    method __init__ (line 9) | def __init__(self, tid, prob):
  class Token (line 14) | class Token(object):
    method __init__ (line 19) | def __init__(self, topic, id):
  class Sentence (line 24) | class Sentence(object):
    method __init__ (line 29) | def __init__(self, topic, tokens):
  class LDADoc (line 34) | class LDADoc(object):
    method __init__ (line 38) | def __init__(self):
    method init (line 46) | def init(self, num_topics):
    method add_token (line 55) | def add_token(self, token):
    method token (line 65) | def token(self, index):
    method set_topic (line 68) | def set_topic(self, index, new_topic):
    method set_alpha (line 81) | def set_alpha(self, alpha):
    method size (line 84) | def size(self):
    method topic_sum (line 89) | def topic_sum(self, topic_id):
    method sparse_topic_dist (line 92) | def sparse_topic_dist(self, sort=True):
    method dense_topic_dist (line 116) | def dense_topic_dist(self):
    method accumulate_topic_num (line 127) | def accumulate_topic_num(self):
  class SLDADoc (line 132) | class SLDADoc(LDADoc):
    method __init__ (line 137) | def __init__(self):
    method init (line 141) | def init(self, num_topics):
    method add_sentence (line 150) | def add_sentence(self, sent):
    method set_topic (line 160) | def set_topic(self, index, new_topic):
    method size (line 170) | def size(self):
    method sent (line 175) | def sent(self, index):

FILE: modules/text/language_model/slda_novel/inference_engine.py
  class SamplerType (line 13) | class SamplerType:
  class InferenceEngine (line 18) | class InferenceEngine(object):
    method __init__ (line 19) | def __init__(self, model_dir, conf_file, type=SamplerType.MetropolisHa...
    method infer (line 33) | def infer(self, input, doc):
    method lda_infer (line 64) | def lda_infer(self, doc, burn_in_iter, total_iter):
    method slda_infer (line 74) | def slda_infer(self, doc, burn_in_iter, total_iter):
    method model_type (line 84) | def model_type(self):
    method get_model (line 87) | def get_model(self):
    method get_config (line 90) | def get_config(self):

FILE: modules/text/language_model/slda_novel/model.py
  class TopicModel (line 11) | class TopicModel(object):
    method __init__ (line 15) | def __init__(self, model_dir, config):
    method term_id (line 35) | def term_id(self, term):
    method load_model (line 38) | def load_model(self, word_topic_path, vocab_path):
    method word_topic_value (line 49) | def word_topic_value(self, word_id, topic_id):
    method word_topic (line 57) | def word_topic(self, term_id):
    method topic_sum_value (line 62) | def topic_sum_value(self, topic_id):
    method topic_sum (line 65) | def topic_sum(self):
    method num_topics (line 68) | def num_topics(self):
    method vocab_size (line 71) | def vocab_size(self):
    method alpha (line 74) | def alpha(self):
    method alpha_sum (line 77) | def alpha_sum(self):
    method beta (line 80) | def beta(self):
    method beta_sum (line 83) | def beta_sum(self):
    method type (line 86) | def type(self):
    method __load_word_dict (line 89) | def __load_word_dict(self, word_dict_path):
    method get_vocab (line 119) | def get_vocab(self):
    method topic_words (line 122) | def topic_words(self):

FILE: modules/text/language_model/slda_novel/module.py
  class TopicModel (line 23) | class TopicModel(hub.Module):
    method _initialize (line 24) | def _initialize(self):
    method infer_doc_topic_distribution (line 49) | def infer_doc_topic_distribution(self, document):
    method show_topic_keywords (line 80) | def show_topic_keywords(self, topic_id, k=10):

FILE: modules/text/language_model/slda_novel/sampler.py
  class Sampler (line 12) | class Sampler(object):
    method __init__ (line 13) | def __init__(self):
    method sample_doc (line 16) | def sample_doc(self, doc):
  class MHSampler (line 22) | class MHSampler(Sampler):
    method __init__ (line 23) | def __init__(self, model):
    method __construct_alias_table (line 34) | def __construct_alias_table(self):
    method sample_doc (line 66) | def sample_doc(self, doc):
    method __sample_token (line 76) | def __sample_token(self, doc, token):
    method __sample_sentence (line 83) | def __sample_sentence(self, doc, sent):
    method __doc_proposal (line 90) | def __doc_proposal(self, doc, token):
    method __word_proposal (line 134) | def __word_proposal(self, doc, token, old_topic):
    method __proportional_function (line 164) | def __proportional_function(self, doc, token, new_topic):
    method __word_proposal_distribution (line 194) | def __word_proposal_distribution(self, word_id, topic):
    method __doc_proposal_distribution (line 199) | def __doc_proposal_distribution(self, doc, topic):
    method __propose (line 202) | def __propose(self, word_id):
  class GibbsSampler (line 212) | class GibbsSampler(Sampler):
    method __init__ (line 213) | def __init__(self, model):
    method sample_doc (line 217) | def sample_doc(self, doc):
    method __sample_token (line 227) | def __sample_token(self, doc, token):
    method __sample_sentence (line 254) | def __sample_sentence(self, doc, sent):

FILE: modules/text/language_model/slda_novel/semantic_matching.py
  class WordAndDis (line 11) | class WordAndDis(object):
    method __init__ (line 12) | def __init__(self):
  class SemanticMatching (line 17) | class SemanticMatching(object):
    method __init__ (line 18) | def __init__(self):
    method l2_norm (line 21) | def l2_norm(self, vec):
    method cosine_similarity (line 27) | def cosine_similarity(self, vec1, vec2):
    method likelihood_based_similarity (line 33) | def likelihood_based_similarity(self, terms, doc_topic_dist, model):
    method kullback_leibler_divergence (line 57) | def kullback_leibler_divergence(self, dist1, dist2):
    method jensen_shannon_divergence (line 63) | def jensen_shannon_divergence(self, dist1, dist2):
    method hellinger_distance (line 72) | def hellinger_distance(self, dist1, dist2):

FILE: modules/text/language_model/slda_novel/tokenizer.py
  class Tokenizer (line 7) | class Tokenizer(object):
    method __init__ (line 11) | def __init__(self):
    method tokenize (line 14) | def tokenize(self, text):
  class SimpleTokenizer (line 18) | class SimpleTokenizer(Tokenizer):
    method __init__ (line 25) | def __init__(self, vocab_path):
    method tokenize (line 31) | def tokenize(self, text):
    method contains (line 61) | def contains(self, word):
    method __load_vocab (line 66) | def __load_vocab(self, vocab_path):
    method __is_eng_char (line 79) | def __is_eng_char(self, c):
    method __tolower (line 84) | def __tolower(self, c):
  class LACTokenizer (line 91) | class LACTokenizer(Tokenizer):
    method __init__ (line 92) | def __init__(self, vocab_path, lac):
    method __load_vocab (line 99) | def __load_vocab(self, vocab_path):
    method tokenize (line 112) | def tokenize(self, text):
    method contains (line 124) | def contains(self, word):

FILE: modules/text/language_model/slda_novel/util.py
  function load_prototxt (line 10) | def load_prototxt(config_file, config):
  function fix_random_seed (line 32) | def fix_random_seed(seed=2147483647):
  function rand (line 36) | def rand(min_=0, max_=1):
  function rand_k (line 40) | def rand_k(k):
  function timeit (line 46) | def timeit(f):

FILE: modules/text/language_model/slda_novel/vocab.py
  class WordCount (line 6) | class WordCount(object):
    method __init__ (line 7) | def __init__(self, word_id, count):
  class Vocab (line 12) | class Vocab(object):
    method __init__ (line 13) | def __init__(self):
    method get_id (line 17) | def get_id(self, word):
    method load (line 22) | def load(self, vocab_file):
    method size (line 37) | def size(self):
    method vocabulary (line 40) | def vocabulary(self):

FILE: modules/text/language_model/slda_novel/vose_alias.py
  class VoseAlias (line 9) | class VoseAlias(object):
    method __init__ (line 13) | def __init__(self):
    method initialize (line 17) | def initialize(self, distribution):
    method generate (line 57) | def generate(self):
    method size (line 64) | def size(self):

FILE: modules/text/language_model/slda_webpage/config.py
  class ModelType (line 6) | class ModelType:
  class ModelConfig (line 11) | class ModelConfig:

FILE: modules/text/language_model/slda_webpage/document.py
  class Topic (line 4) | class Topic(object):
    method __init__ (line 9) | def __init__(self, tid, prob):
  class Token (line 14) | class Token(object):
    method __init__ (line 19) | def __init__(self, topic, id):
  class Sentence (line 24) | class Sentence(object):
    method __init__ (line 29) | def __init__(self, topic, tokens):
  class LDADoc (line 34) | class LDADoc(object):
    method __init__ (line 38) | def __init__(self):
    method init (line 46) | def init(self, num_topics):
    method add_token (line 55) | def add_token(self, token):
    method token (line 65) | def token(self, index):
    method set_topic (line 68) | def set_topic(self, index, new_topic):
    method set_alpha (line 81) | def set_alpha(self, alpha):
    method size (line 84) | def size(self):
    method topic_sum (line 89) | def topic_sum(self, topic_id):
    method sparse_topic_dist (line 92) | def sparse_topic_dist(self, sort=True):
    method dense_topic_dist (line 116) | def dense_topic_dist(self):
    method accumulate_topic_num (line 127) | def accumulate_topic_num(self):
  class SLDADoc (line 132) | class SLDADoc(LDADoc):
    method __init__ (line 137) | def __init__(self):
    method init (line 141) | def init(self, num_topics):
    method add_sentence (line 150) | def add_sentence(self, sent):
    method set_topic (line 160) | def set_topic(self, index, new_topic):
    method size (line 170) | def size(self):
    method sent (line 175) | def sent(self, index):

FILE: modules/text/language_model/slda_webpage/inference_engine.py
  class SamplerType (line 13) | class SamplerType:
  class InferenceEngine (line 18) | class InferenceEngine(object):
    method __init__ (line 19) | def __init__(self, model_dir, conf_file, type=SamplerType.MetropolisHa...
    method infer (line 33) | def infer(self, input, doc):
    method lda_infer (line 64) | def lda_infer(self, doc, burn_in_iter, total_iter):
    method slda_infer (line 74) | def slda_infer(self, doc, burn_in_iter, total_iter):
    method model_type (line 84) | def model_type(self):
    method get_model (line 87) | def get_model(self):
    method get_config (line 90) | def get_config(self):

FILE: modules/text/language_model/slda_webpage/model.py
  class TopicModel (line 11) | class TopicModel(object):
    method __init__ (line 15) | def __init__(self, model_dir, config):
    method term_id (line 35) | def term_id(self, term):
    method load_model (line 38) | def load_model(self, word_topic_path, vocab_path):
    method word_topic_value (line 49) | def word_topic_value(self, word_id, topic_id):
    method word_topic (line 57) | def word_topic(self, term_id):
    method topic_sum_value (line 62) | def topic_sum_value(self, topic_id):
    method topic_sum (line 65) | def topic_sum(self):
    method num_topics (line 68) | def num_topics(self):
    method vocab_size (line 71) | def vocab_size(self):
    method alpha (line 74) | def alpha(self):
    method alpha_sum (line 77) | def alpha_sum(self):
    method beta (line 80) | def beta(self):
    method beta_sum (line 83) | def beta_sum(self):
    method type (line 86) | def type(self):
    method __load_word_dict (line 89) | def __load_word_dict(self, word_dict_path):
    method get_vocab (line 119) | def get_vocab(self):
    method topic_words (line 122) | def topic_words(self):

FILE: modules/text/language_model/slda_webpage/module.py
  class TopicModel (line 23) | class TopicModel(hub.Module):
    method _initialize (line 24) | def _initialize(self):
    method infer_doc_topic_distribution (line 49) | def infer_doc_topic_distribution(self, document):
    method show_topic_keywords (line 80) | def show_topic_keywords(self, topic_id, k=10):

FILE: modules/text/language_model/slda_webpage/sampler.py
  class Sampler (line 12) | class Sampler(object):
    method __init__ (line 13) | def __init__(self):
    method sample_doc (line 16) | def sample_doc(self, doc):
  class MHSampler (line 22) | class MHSampler(Sampler):
    method __init__ (line 23) | def __init__(self, model):
    method __construct_alias_table (line 34) | def __construct_alias_table(self):
    method sample_doc (line 66) | def sample_doc(self, doc):
    method __sample_token (line 76) | def __sample_token(self, doc, token):
    method __sample_sentence (line 83) | def __sample_sentence(self, doc, sent):
    method __doc_proposal (line 90) | def __doc_proposal(self, doc, token):
    method __word_proposal (line 134) | def __word_proposal(self, doc, token, old_topic):
    method __proportional_function (line 164) | def __proportional_function(self, doc, token, new_topic):
    method __word_proposal_distribution (line 194) | def __word_proposal_distribution(self, word_id, topic):
    method __doc_proposal_distribution (line 199) | def __doc_proposal_distribution(self, doc, topic):
    method __propose (line 202) | def __propose(self, word_id):
  class GibbsSampler (line 212) | class GibbsSampler(Sampler):
    method __init__ (line 213) | def __init__(self, model):
    method sample_doc (line 217) | def sample_doc(self, doc):
    method __sample_token (line 227) | def __sample_token(self, doc, token):
    method __sample_sentence (line 254) | def __sample_sentence(self, doc, sent):

FILE: modules/text/language_model/slda_webpage/semantic_matching.py
  class WordAndDis (line 11) | class WordAndDis(object):
    method __init__ (line 12) | def __init__(self):
  class SemanticMatching (line 17) | class SemanticMatching(object):
    method __init__ (line 18) | def __init__(self):
    method l2_norm (line 21) | def l2_norm(self, vec):
    method cosine_similarity (line 27) | def cosine_similarity(self, vec1, vec2):
    method likelihood_based_similarity (line 33) | def likelihood_based_similarity(self, terms, doc_topic_dist, model):
    method kullback_leibler_divergence (line 57) | def kullback_leibler_divergence(self, dist1, dist2):
    method jensen_shannon_divergence (line 63) | def jensen_shannon_divergence(self, dist1, dist2):
    method hellinger_distance (line 72) | def hellinger_distance(self, dist1, dist2):

FILE: modules/text/language_model/slda_webpage/tokenizer.py
  class Tokenizer (line 7) | class Tokenizer(object):
    method __init__ (line 11) | def __init__(self):
    method tokenize (line 14) | def tokenize(self, text):
  class SimpleTokenizer (line 18) | class SimpleTokenizer(Tokenizer):
    method __init__ (line 25) | def __init__(self, vocab_path):
    method tokenize (line 31) | def tokenize(self, text):
    method contains (line 61) | def contains(self, word):
    method __load_vocab (line 66) | def __load_vocab(self, vocab_path):
    method __is_eng_char (line 79) | def __is_eng_char(self, c):
    method __tolower (line 84) | def __tolower(self, c):
  class LACTokenizer (line 91) | class LACTokenizer(Tokenizer):
    method __init__ (line 92) | def __init__(self, vocab_path, lac):
    method __load_vocab (line 99) | def __load_vocab(self, vocab_path):
    method tokenize (line 112) | def tokenize(self, text):
    method contains (line 124) | def contains(self, word):

FILE: modules/text/language_model/slda_webpage/util.py
  function load_prototxt (line 10) | def load_prototxt(config_file, config):
  function fix_random_seed (line 32) | def fix_random_seed(seed=2147483647):
  function rand (line 36) | def rand(min_=0, max_=1):
  function rand_k (line 40) | def rand_k(k):
  function timeit (line 46) | def timeit(f):

FILE: modules/text/language_model/slda_webpage/vocab.py
  class WordCount (line 6) | class WordCount(object):
    method __init__ (line 7) | def __init__(self, word_id, count):
  class Vocab (line 12) | class Vocab(object):
    method __init__ (line 13) | def __init__(self):
    method get_id (line 17) | def get_id(self, word):
    method load (line 22) | def load(self, vocab_file):
    method size (line 37) | def size(self):
    method vocabulary (line 40) | def vocabulary(self):

FILE: modules/text/language_model/slda_webpage/vose_alias.py
  class VoseAlias (line 9) | class VoseAlias(object):
    method __init__ (line 13) | def __init__(self):
    method initialize (line 17) | def initialize(self, distribution):
    method generate (line 57) | def generate(self):
    method size (line 64) | def size(self):

FILE: modules/text/language_model/slda_weibo/config.py
  class ModelType (line 6) | class ModelType:
  class ModelConfig (line 11) | class ModelConfig:

FILE: modules/text/language_model/slda_weibo/document.py
  class Topic (line 4) | class Topic(object):
    method __init__ (line 9) | def __init__(self, tid, prob):
  class Token (line 14) | class Token(object):
    method __init__ (line 19) | def __init__(self, topic, id):
  class Sentence (line 24) | class Sentence(object):
    method __init__ (line 29) | def __init__(self, topic, tokens):
  class LDADoc (line 34) | class LDADoc(object):
    method __init__ (line 38) | def __init__(self):
    method init (line 46) | def init(self, num_topics):
    method add_token (line 55) | def add_token(self, token):
    method token (line 65) | def token(self, index):
    method set_topic (line 68) | def set_topic(self, index, new_topic):
    method set_alpha (line 81) | def set_alpha(self, alpha):
    method size (line 84) | def size(self):
    method topic_sum (line 89) | def topic_sum(self, topic_id):
    method sparse_topic_dist (line 92) | def sparse_topic_dist(self, sort=True):
    method dense_topic_dist (line 116) | def dense_topic_dist(self):
    method accumulate_topic_num (line 127) | def accumulate_topic_num(self):
  class SLDADoc (line 132) | class SLDADoc(LDADoc):
    method __init__ (line 137) | def __init__(self):
    method init (line 141) | def init(self, num_topics):
    method add_sentence (line 150) | def add_sentence(self, sent):
    method set_topic (line 160) | def set_topic(self, index, new_topic):
    method size (line 170) | def size(self):
    method sent (line 175) | def sent(self, index):

FILE: modules/text/language_model/slda_weibo/inference_engine.py
  class SamplerType (line 13) | class SamplerType:
  class InferenceEngine (line 18) | class InferenceEngine(object):
    method __init__ (line 19) | def __init__(self, model_dir, conf_file, type=SamplerType.MetropolisHa...
    method infer (line 33) | def infer(self, input, doc):
    method lda_infer (line 64) | def lda_infer(self, doc, burn_in_iter, total_iter):
    method slda_infer (line 74) | def slda_infer(self, doc, burn_in_iter, total_iter):
    method model_type (line 84) | def model_type(self):
    method get_model (line 87) | def get_model(self):
    method get_config (line 90) | def get_config(self):

FILE: modules/text/language_model/slda_weibo/model.py
  class TopicModel (line 11) | class TopicModel(object):
    method __init__ (line 15) | def __init__(self, model_dir, config):
    method term_id (line 35) | def term_id(self, term):
    method load_model (line 38) | def load_model(self, word_topic_path, vocab_path):
    method word_topic_value (line 49) | def word_topic_value(self, word_id, topic_id):
    method word_topic (line 57) | def word_topic(self, term_id):
    method topic_sum_value (line 62) | def topic_sum_value(self, topic_id):
    method topic_sum (line 65) | def topic_sum(self):
    method num_topics (line 68) | def num_topics(self):
    method vocab_size (line 71) | def vocab_size(self):
    method alpha (line 74) | def alpha(self):
    method alpha_sum (line 77) | def alpha_sum(self):
    method beta (line 80) | def beta(self):
    method beta_sum (line 83) | def beta_sum(self):
    method type (line 86) | def type(self):
    method __load_word_dict (line 89) | def __load_word_dict(self, word_dict_path):
    method get_vocab (line 119) | def get_vocab(self):
    method topic_words (line 122) | def topic_words(self):

FILE: modules/text/language_model/slda_weibo/module.py
  class TopicModel (line 23) | class TopicModel(hub.Module):
    method _initialize (line 24) | def _initialize(self):
    method infer_doc_topic_distribution (line 49) | def infer_doc_topic_distribution(self, document):
    method show_topic_keywords (line 80) | def show_topic_keywords(self, topic_id, k=10):

FILE: modules/text/language_model/slda_weibo/sampler.py
  class Sampler (line 12) | class Sampler(object):
    method __init__ (line 13) | def __init__(self):
    method sample_doc (line 16) | def sample_doc(self, doc):
  class MHSampler (line 22) | class MHSampler(Sampler):
    method __init__ (line 23) | def __init__(self, model):
    method __construct_alias_table (line 34) | def __construct_alias_table(self):
    method sample_doc (line 66) | def sample_doc(self, doc):
    method __sample_token (line 76) | def __sample_token(self, doc, token):
    method __sample_sentence (line 83) | def __sample_sentence(self, doc, sent):
    method __doc_proposal (line 90) | def __doc_proposal(self, doc, token):
    method __word_proposal (line 134) | def __word_proposal(self, doc, token, old_topic):
    method __proportional_function (line 164) | def __proportional_function(self, doc, token, new_topic):
    method __word_proposal_distribution (line 194) | def __word_proposal_distribution(self, word_id, topic):
    method __doc_proposal_distribution (line 199) | def __doc_proposal_distribution(self, doc, topic):
    method __propose (line 202) | def __propose(self, word_id):
  class GibbsSampler (line 212) | class GibbsSampler(Sampler):
    method __init__ (line 213) | def __init__(self, model):
    method sample_doc (line 217) | def sample_doc(self, doc):
    method __sample_token (line 227) | def __sample_token(self, doc, token):
    method __sample_sentence (line 254) | def __sample_sentence(self, doc, sent):

FILE: modules/text/language_model/slda_weibo/semantic_matching.py
  class WordAndDis (line 11) | class WordAndDis(object):
    method __init__ (line 12) | def __init__(self):
  class SemanticMatching (line 17) | class SemanticMatching(object):
    method __init__ (line 18) | def __init__(self):
    method l2_norm (line 21) | def l2_norm(self, vec):
    method cosine_similarity (line 27) | def cosine_similarity(self, vec1, vec2):
    method likelihood_based_similarity (line 33) | def likelihood_based_similarity(self, terms, doc_topic_dist, model):
    method kullback_leibler_divergence (line 57) | def kullback_leibler_divergence(self, dist1, dist2):
    method jensen_shannon_divergence (line 63) | def jensen_shannon_divergence(self, dist1, dist2):
    method hellinger_distance (line 72) | def hellinger_distance(self, dist1, dist2):

FILE: modules/text/language_model/slda_weibo/tokenizer.py
  class Tokenizer (line 7) | class Tokenizer(object):
    method __init__ (line 11) | def __init__(self):
    method tokenize (line 14) | def tokenize(self, text):
  class SimpleTokenizer (line 18) | class SimpleTokenizer(Tokenizer):
    method __init__ (line 25) | def __init__(self, vocab_path):
    method tokenize (line 31) | def tokenize(self, text):
    method contains (line 61) | def contains(self, word):
    method __load_vocab (line 66) | def __load_vocab(self, vocab_path):
    method __is_eng_char (line 79) | def __is_eng_char(self, c):
    method __tolower (line 84) | def __tolower(self, c):
  class LACTokenizer (line 91) | class LACTokenizer(Tokenizer):
    method __init__ (line 92) | def __init__(self, vocab_path, lac):
    method __load_vocab (line 99) | def __load_vocab(self, vocab_path):
    method tokenize (line 112) | def tokenize(self, text):
    method contains (line 124) | def contains(self, word):

FILE: modules/text/language_model/slda_weibo/util.py
  function load_prototxt (line 10) | def load_prototxt(config_file, config):
  function fix_random_seed (line 32) | def fix_random_seed(seed=2147483647):
  function rand (line 36) | def rand(min_=0, max_=1):
  function rand_k (line 40) | def rand_k(k):
  function timeit (line 46) | def timeit(f):

FILE: modules/text/language_model/slda_weibo/vocab.py
  class WordCount (line 6) | class WordCount(object):
    method __init__ (line 7) | def __init__(self, word_id, count):
  class Vocab (line 12) | class Vocab(object):
    method __init__ (line 13) | def __init__(self):
    method get_id (line 17) | def get_id(self, word):
    method load (line 22) | def load(self, vocab_file):
    method size (line 37) | def size(self):
    method vocabulary (line 40) | def vocabulary(self):

FILE: modules/text/language_model/slda_weibo/vose_alias.py
  class VoseAlias (line 9) | class VoseAlias(object):
    method __init__ (line 13) | def __init__(self):
    method initialize (line 17) | def initialize(self, distribution):
    method generate (line 57) | def generate(self):
    method size (line 64) | def size(self):

FILE: modules/text/lexical_analysis/jieba_paddle/module.py
  class JiebaPaddle (line 23) | class JiebaPaddle(hub.Module):
    method _initialize (line 25) | def _initialize(self):
    method cut (line 29) | def cut(self, sentence, use_paddle=True, cut_all=False, HMM=True):
    method create_gradio_app (line 57) | def create_gradio_app(self):
    method check_dependency (line 75) | def check_dependency(self):
    method cut_for_search (line 87) | def cut_for_search(self, sentence, HMM=True):
    method load_userdict (line 104) | def load_userdict(self, user_dict):
    method extract_tags (line 122) | def extract_tags(self, sentence, topK=20, withWeight=False, allowPOS=(...
    method textrank (line 148) | def textrank(self, sentence, topK=20, withWeight=False, allowPOS=('ns'...

FILE: modules/text/lexical_analysis/lac/ahocorasick.py
  class Node (line 6) | class Node(object):
    method __init__ (line 16) | def __init__(self):
  class Ahocorasick (line 23) | class Ahocorasick(object):
    method __init__ (line 30) | def __init__(self):
    method add_word (line 34) | def add_word(self, word):
    method make (line 41) | def make(self):
    method search (line 70) | def search(self, content):
    method search_all (line 100) | def search_all(self, content):

FILE: modules/text/lexical_analysis/lac/custom.py
  class Customization (line 9) | class Customization(object):
    method __init__ (line 14) | def __init__(self):
    method load_customization (line 19) | def load_customization(self, filename, sep=None):
    method parse_customization (line 51) | def parse_customization(self, query, lac_tags):

FILE: modules/text/lexical_analysis/lac/module.py
  class DataFormatError (line 27) | class DataFormatError(Exception):
    method __init__ (line 29) | def __init__(self, *args):
  class LAC (line 41) | class LAC:
    method __init__ (line 43) | def __init__(self, user_dict=None):
    method _set_config (line 65) | def _set_config(self):
    method set_user_dict (line 88) | def set_user_dict(self, dict_path, sep=None):
    method del_user_dict (line 101) | def del_user_dict(self):
    method to_unicode (line 110) | def to_unicode(self, texts):
    method preprocess (line 130) | def preprocess(self, texts):
    method _get_index (line 146) | def _get_index(self, data_list, item=""):
    method cut (line 157) | def cut(self, text, use_gpu=False, batch_size=1, return_tag=True):
    method lexical_analysis (line 246) | def lexical_analysis(self, texts=[], data={}, use_gpu=False, batch_siz...
    method run_cmd (line 320) | def run_cmd(self, argvs):
    method get_tags (line 354) | def get_tags(self):
    method add_module_config_arg (line 368) | def add_module_config_arg(self):
    method add_module_input_arg (line 387) | def add_module_input_arg(self):
    method check_input_data (line 394) | def check_input_data(self, args):
    method create_gradio_app (line 415) | def create_gradio_app(self):

FILE: modules/text/lexical_analysis/lac/processor.py
  class Query (line 7) | class Query(object):
    method __init__ (line 9) | def __init__(self, lac_query):
    method set_query (line 12) | def set_query(self, lac_query):
  class Bound (line 37) | class Bound(object):
    method __init__ (line 39) | def __init__(self, start_index=0, end_index=0, left_bound=0, right_bou...
  class Interventer (line 48) | class Interventer(object):
    method __init__ (line 50) | def __init__(self, ngram_dict_path, user_dict_path):
    method init_pos_types (line 56) | def init_pos_types(self):
    method load_dict (line 61) | def load_dict(self):
    method find_min_bound (line 96) | def find_min_bound(self, match_info, query):
    method calc_lm_score (line 123) | def calc_lm_score(self, phrase_list):
    method get_new_phrase_list (line 132) | def get_new_phrase_list(self, match_info, bound, query):
    method run (line 152) | def run(self, query):
  function load_kv_dict (line 220) | def load_kv_dict(dict_path, reverse=False, delimiter="\t", key_func=None...
  function word_to_ids (line 243) | def word_to_ids(words, word2id_dict, word_replace_dict, oov_id=None):
  function parse_result (line 254) | def parse_result(lines, crf_decode, id2label_dict, interventer=None):

FILE: modules/text/lexical_analysis/lac/test.py
  class TestHubModule (line 10) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 13) | def setUpClass(cls) -> None:
    method tearDownClass (line 19) | def tearDownClass(cls) -> None:
    method test_cut1 (line 22) | def test_cut1(self):
    method test_cut2 (line 26) | def test_cut2(self):
    method test_cut3 (line 36) | def test_cut3(self):
    method test_cut4 (line 46) | def test_cut4(self):
    method test_cut5 (line 56) | def test_cut5(self):
    method test_save_inference_model (line 69) | def test_save_inference_model(self):

FILE: modules/text/machine_translation/transformer/en-de/module.py
  class MTTransformer (line 37) | class MTTransformer(nn.Layer):
    method __init__ (line 79) | def __init__(self, max_length: int = 256, max_out_len: int = 256, beam...
    method forward (line 117) | def forward(self, src_words: paddle.Tensor):
    method _convert_text_to_input (line 120) | def _convert_text_to_input(self, text: str):
    method _batchify (line 129) | def _batchify(self, data: List[str], batch_size: int):
    method predict (line 153) | def predict(self, data: List[str], batch_size: int = 1, n_best: int = ...

FILE: modules/text/machine_translation/transformer/en-de/utils.py
  class MTTokenizer (line 23) | class MTTokenizer(object):
    method __init__ (line 24) | def __init__(self, bpe_codes_file: str, lang_src: str = 'en', lang_trg...
    method tokenize (line 34) | def tokenize(self, text: str):
    method detokenize (line 44) | def detokenize(self, tokens: List[str]):
  function post_process_seq (line 56) | def post_process_seq(seq, bos_idx, eos_idx, output_bos=False, output_eos...

FILE: modules/text/machine_translation/transformer/zh-en/module.py
  class MTTransformer (line 39) | class MTTransformer(nn.Layer):
    method __init__ (line 81) | def __init__(self, max_length: int = 256, max_out_len: int = 256, beam...
    method forward (line 125) | def forward(self, src_words: paddle.Tensor):
    method _convert_text_to_input (line 128) | def _convert_text_to_input(self, text: str):
    method _batchify (line 137) | def _batchify(self, data: List[str], batch_size: int):
    method predict (line 161) | def predict(self, data: List[str], batch_size: int = 1, n_best: int = ...
    method create_gradio_app (line 188) | def create_gradio_app(self):

FILE: modules/text/machine_translation/transformer/zh-en/utils.py
  class MTTokenizer (line 27) | class MTTokenizer(object):
    method __init__ (line 29) | def __init__(self, bpe_codes_file: str, lang_src: str = 'zh', lang_trg...
    method tokenize (line 37) | def tokenize(self, text: str):
    method detokenize (line 48) | def detokenize(self, tokens: List[str]):
  function post_process_seq (line 60) | def post_process_seq(seq, bos_idx, eos_idx, output_bos=False, output_eos...

FILE: modules/text/punctuation_restoration/auto_punc/module.py
  class Ernie (line 35) | class Ernie(paddle.nn.Layer):
    method __init__ (line 36) | def __init__(self):
    method _load_dict (line 49) | def _load_dict(dict_path):
    method _clean_text (line 60) | def _clean_text(text, punc_list):
    method forward (line 66) | def forward(self, text: str):
    method add_puncs (line 81) | def add_puncs(self, texts: Union[str, List[str]], max_length=256, devi...

FILE: modules/text/sentiment_analysis/emotion_detection_textcnn/module.py
  class EmotionDetectionTextCNN (line 18) | class EmotionDetectionTextCNN(hub.NLPPredictionModule):
    method _initialize (line 20) | def _initialize(self):
    method word_seg_module (line 34) | def word_seg_module(self):
    method emotion_classify (line 43) | def emotion_classify(self, texts=[], data={}, use_gpu=False, batch_siz...
    method get_labels (line 92) | def get_labels(self):

FILE: modules/text/sentiment_analysis/emotion_detection_textcnn/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function get_predict_label (line 26) | def get_predict_label(probs):
  function preprocess (line 37) | def preprocess(lac, predicted_data, word_dict, use_gpu=False, batch_size...
  function postprocess (line 55) | def postprocess(prediction, texts):

FILE: modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/ernie.py
  class ErnieConfig (line 27) | class ErnieConfig(object):
    method __init__ (line 30) | def __init__(self, config_path):
    method _parse (line 36) | def _parse(self, config_path):
    method __getitem__ (line 49) | def __getitem__(self, key):
    method has (line 56) | def has(self, key):
    method get (line 65) | def get(self, key, default_value):
    method print_config (line 75) | def print_config(self):

FILE: modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/module.py
  class ErnieSkepSentimentAnalysis (line 45) | class ErnieSkepSentimentAnalysis(TransformerModule):
    method _initialize (line 52) | def _initialize(self):
    method _set_config (line 68) | def _set_config(self):
    method array2tensor (line 92) | def array2tensor(self, arr_data):
    method predict_sentiment (line 100) | def predict_sentiment(self, texts=[], use_gpu=False):
    method _convert_text_to_feature (line 151) | def _convert_text_to_feature(self, text):
    method run_cmd (line 189) | def run_cmd(self, argvs):
    method add_module_config_arg (line 209) | def add_module_config_arg(self):
    method add_module_input_arg (line 218) | def add_module_input_arg(self):

FILE: modules/text/sentiment_analysis/senta_bilstm/module.py
  class SentaBiLSTM (line 27) | class SentaBiLSTM(hub.NLPPredictionModule):
    method _initialize (line 29) | def _initialize(self):
    method word_seg_module (line 43) | def word_seg_module(self):
    method sentiment_classify (line 52) | def sentiment_classify(self, texts=[], data={}, use_gpu=False, batch_s...
    method get_labels (line 103) | def get_labels(self):

FILE: modules/text/sentiment_analysis/senta_bilstm/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function preprocess (line 20) | def preprocess(lac, texts, word_dict, use_gpu=False, batch_size=1):
  function postprocess (line 42) | def postprocess(predict_out, texts):

FILE: modules/text/sentiment_analysis/senta_bow/module.py
  class SentaBow (line 27) | class SentaBow(hub.NLPPredictionModule):
    method _initialize (line 29) | def _initialize(self):
    method word_seg_module (line 43) | def word_seg_module(self):
    method sentiment_classify (line 52) | def sentiment_classify(self, texts=[], data={}, use_gpu=False, batch_s...
    method get_labels (line 103) | def get_labels(self):

FILE: modules/text/sentiment_analysis/senta_bow/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function preprocess (line 20) | def preprocess(lac, texts, word_dict, use_gpu=False, batch_size=1):
  function postprocess (line 42) | def postprocess(predict_out, texts):

FILE: modules/text/sentiment_analysis/senta_cnn/module.py
  class SentaCNN (line 27) | class SentaCNN(hub.NLPPredictionModule):
    method _initialize (line 29) | def _initialize(self, user_dict=None):
    method word_seg_module (line 43) | def word_seg_module(self):
    method sentiment_classify (line 52) | def sentiment_classify(self, texts=[], data={}, use_gpu=False, batch_s...
    method get_labels (line 103) | def get_labels(self):

FILE: modules/text/sentiment_analysis/senta_cnn/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function preprocess (line 20) | def preprocess(lac, texts, word_dict, use_gpu=False, batch_size=1):
  function postprocess (line 42) | def postprocess(predict_out, texts):

FILE: modules/text/sentiment_analysis/senta_gru/module.py
  class SentaGRU (line 27) | class SentaGRU(hub.NLPPredictionModule):
    method _initialize (line 29) | def _initialize(self, user_dict=None):
    method word_seg_module (line 43) | def word_seg_module(self):
    method sentiment_classify (line 52) | def sentiment_classify(self, texts=[], data={}, use_gpu=False, batch_s...
    method get_labels (line 103) | def get_labels(self):

FILE: modules/text/sentiment_analysis/senta_gru/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function preprocess (line 20) | def preprocess(lac, texts, word_dict, use_gpu=False, batch_size=1):
  function postprocess (line 42) | def postprocess(predict_out, texts):

FILE: modules/text/sentiment_analysis/senta_lstm/module.py
  class SentaLSTM (line 27) | class SentaLSTM(hub.NLPPredictionModule):
    method _initialize (line 29) | def _initialize(self, user_dict=None):
    method word_seg_module (line 43) | def word_seg_module(self):
    method sentiment_classify (line 52) | def sentiment_classify(self, texts=[], data={}, use_gpu=False, batch_s...
    method get_labels (line 103) | def get_labels(self):

FILE: modules/text/sentiment_analysis/senta_lstm/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function preprocess (line 20) | def preprocess(lac, texts, word_dict, use_gpu=False, batch_size=1):
  function postprocess (line 42) | def postprocess(predict_out, texts):

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_1/model.py
  class DecoderLayer (line 23) | class DecoderLayer(nn.TransformerDecoderLayer):
    method __init__ (line 24) | def __init__(self, *args, **kwargs):
    method forward (line 27) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class Decoder (line 73) | class Decoder(nn.TransformerDecoder):
    method forward (line 79) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class SimultaneousTransformer (line 103) | class SimultaneousTransformer(nn.Layer):
    method __init__ (line 107) | def __init__(self,
    method forward (line 180) | def forward(self, src_word, trg_word):
    method beam_search (line 239) | def beam_search(self, src_word, beam_size=4, max_len=256, waitk=-1):
    method greedy_search (line 243) | def greedy_search(self,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_1/module.py
  class STTransformer (line 36) | class STTransformer():
    method __init__ (line 53) | def __init__(self,
    method translate (line 89) | def translate(self, text, use_gpu=False):

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_1/processor.py
  class STACLTokenizer (line 20) | class STACLTokenizer:
    method __init__ (line 25) | def __init__(self,
    method tokenize (line 53) | def tokenize(self, text):
  function post_process_seq (line 59) | def post_process_seq(seq,
  function predict (line 79) | def predict(tokenized_src,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_3/model.py
  class DecoderLayer (line 23) | class DecoderLayer(nn.TransformerDecoderLayer):
    method __init__ (line 24) | def __init__(self, *args, **kwargs):
    method forward (line 27) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class Decoder (line 73) | class Decoder(nn.TransformerDecoder):
    method forward (line 79) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class SimultaneousTransformer (line 103) | class SimultaneousTransformer(nn.Layer):
    method __init__ (line 107) | def __init__(self,
    method forward (line 180) | def forward(self, src_word, trg_word):
    method beam_search (line 239) | def beam_search(self, src_word, beam_size=4, max_len=256, waitk=-1):
    method greedy_search (line 243) | def greedy_search(self,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_3/module.py
  class STTransformer (line 36) | class STTransformer():
    method __init__ (line 53) | def __init__(self,
    method translate (line 89) | def translate(self, text, use_gpu=False):

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_3/processor.py
  class STACLTokenizer (line 20) | class STACLTokenizer:
    method __init__ (line 25) | def __init__(self,
    method tokenize (line 53) | def tokenize(self, text):
  function post_process_seq (line 59) | def post_process_seq(seq,
  function predict (line 79) | def predict(tokenized_src,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_5/model.py
  class DecoderLayer (line 23) | class DecoderLayer(nn.TransformerDecoderLayer):
    method __init__ (line 24) | def __init__(self, *args, **kwargs):
    method forward (line 27) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class Decoder (line 73) | class Decoder(nn.TransformerDecoder):
    method forward (line 79) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class SimultaneousTransformer (line 103) | class SimultaneousTransformer(nn.Layer):
    method __init__ (line 107) | def __init__(self,
    method forward (line 180) | def forward(self, src_word, trg_word):
    method beam_search (line 239) | def beam_search(self, src_word, beam_size=4, max_len=256, waitk=-1):
    method greedy_search (line 243) | def greedy_search(self,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_5/module.py
  class STTransformer (line 36) | class STTransformer():
    method __init__ (line 53) | def __init__(self,
    method translate (line 89) | def translate(self, text, use_gpu=False):

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_5/processor.py
  class STACLTokenizer (line 20) | class STACLTokenizer:
    method __init__ (line 25) | def __init__(self,
    method tokenize (line 53) | def tokenize(self, text):
  function post_process_seq (line 59) | def post_process_seq(seq,
  function predict (line 79) | def predict(tokenized_src,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_7/model.py
  class DecoderLayer (line 23) | class DecoderLayer(nn.TransformerDecoderLayer):
    method __init__ (line 24) | def __init__(self, *args, **kwargs):
    method forward (line 27) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class Decoder (line 73) | class Decoder(nn.TransformerDecoder):
    method forward (line 79) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class SimultaneousTransformer (line 103) | class SimultaneousTransformer(nn.Layer):
    method __init__ (line 107) | def __init__(self,
    method forward (line 180) | def forward(self, src_word, trg_word):
    method beam_search (line 239) | def beam_search(self, src_word, beam_size=4, max_len=256, waitk=-1):
    method greedy_search (line 243) | def greedy_search(self,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_7/module.py
  class STTransformer (line 36) | class STTransformer():
    method __init__ (line 53) | def __init__(self,
    method translate (line 89) | def translate(self, text, use_gpu=False):

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_7/processor.py
  class STACLTokenizer (line 20) | class STACLTokenizer:
    method __init__ (line 25) | def __init__(self,
    method tokenize (line 53) | def tokenize(self, text):
  function post_process_seq (line 59) | def post_process_seq(seq,
  function predict (line 79) | def predict(tokenized_src,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_all/model.py
  class DecoderLayer (line 23) | class DecoderLayer(nn.TransformerDecoderLayer):
    method __init__ (line 24) | def __init__(self, *args, **kwargs):
    method forward (line 27) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class Decoder (line 73) | class Decoder(nn.TransformerDecoder):
    method forward (line 79) | def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, cache=...
  class SimultaneousTransformer (line 103) | class SimultaneousTransformer(nn.Layer):
    method __init__ (line 107) | def __init__(self,
    method forward (line 180) | def forward(self, src_word, trg_word):
    method beam_search (line 239) | def beam_search(self, src_word, beam_size=4, max_len=256, waitk=-1):
    method greedy_search (line 243) | def greedy_search(self,

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_all/module.py
  class STTransformer (line 36) | class STTransformer():
    method __init__ (line 53) | def __init__(self,
    method translate (line 89) | def translate(self, text, use_gpu=False):

FILE: modules/text/simultaneous_translation/stacl/transformer_nist_wait_all/processor.py
  class STACLTokenizer (line 20) | class STACLTokenizer:
    method __init__ (line 25) | def __init__(self,
    method tokenize (line 53) | def tokenize(self, text):
  function post_process_seq (line 59) | def post_process_seq(seq,
  function predict (line 79) | def predict(tokenized_src,

FILE: modules/text/syntactic_analysis/DDParser/module.py
  class ddparser (line 17) | class ddparser(hub.NLPPredictionModule):
    method __init__ (line 18) | def __init__(self,
    method serving_parse (line 34) | def serving_parse(self, texts):
    method parse (line 41) | def parse(self, texts):
    method run_cmd (line 62) | def run_cmd(self, argvs):
    method visualize (line 84) | def visualize(self, text):

FILE: modules/text/text_correction/ernie-csc/module.py
  class Ernie_CSC (line 19) | class Ernie_CSC(paddle.nn.Layer):
    method __init__ (line 20) | def __init__(self,
    method predict (line 25) | def predict(self, texts):
    method run_cmd (line 47) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/GPT2_Base_CN/module.py
  class GPT2_Base_CN (line 16) | class GPT2_Base_CN(nn.Layer):
    method __init__ (line 17) | def __init__(self):
    method greedy_search (line 32) | def greedy_search(self, text, max_len=32, end_word=None):
    method top_k_top_p_filtering (line 60) | def top_k_top_p_filtering(logits, top_k=0, top_p=1.0, filter_value=-fl...
    method nucleus_sample (line 92) | def nucleus_sample(self,
    method serving_method (line 140) | def serving_method(self, text, mode='search', **kwargs):

FILE: modules/text/text_generation/GPT2_CPM_LM/module.py
  class GPT2_CPM_LM (line 17) | class GPT2_CPM_LM(nn.Layer):
    method __init__ (line 18) | def __init__(self):
    method greedy_search (line 58) | def greedy_search(self, text, max_len=32, end_word=None):
    method top_k_top_p_filtering (line 86) | def top_k_top_p_filtering(logits, top_k=0, top_p=1.0, filter_value=-fl...
    method nucleus_sample (line 118) | def nucleus_sample(self,
    method serving_method (line 168) | def serving_method(self, text, mode='search', **kwargs):

FILE: modules/text/text_generation/Rumor_prediction/module.py
  class Rumorprediction (line 38) | class Rumorprediction(hub.Module):
    method _initialize (line 39) | def _initialize(self):
    method Rumor (line 46) | def Rumor(self, texts, use_gpu=False):
    method add_module_config_arg (line 102) | def add_module_config_arg(self):
    method add_module_input_arg (line 109) | def add_module_input_arg(self):
    method run_cmd (line 116) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/ernie_gen/decode.py
  function gen_bias (line 34) | def gen_bias(encoder_inputs, decoder_inputs, step):
  function greedy_search_infilling (line 55) | def greedy_search_infilling(model,
  function log_softmax (line 120) | def log_softmax(x):
  function mask_prob (line 125) | def mask_prob(p, onehot_eos, finished):
  function hyp_score (line 131) | def hyp_score(log_probs, length, length_penalty):
  function beam_search_step (line 136) | def beam_search_step(state, logits, eos_id, beam_width, is_first_step, l...
  function beam_search_infilling (line 179) | def beam_search_infilling(model,
  function post_process (line 278) | def post_process(token):

FILE: modules/text/text_generation/ernie_gen/encode.py
  function convert_example (line 20) | def convert_example(tokenizer,
  function gen_mask (line 63) | def gen_mask(batch_ids, mask_type='bidi', query_len=None, pad_value=0):
  function after_padding (line 87) | def after_padding(args):

FILE: modules/text/text_generation/ernie_gen/model.py
  class StackModel (line 20) | class StackModel(nn.Layer):
    method __init__ (line 21) | def __init__(self, model):
    method forward (line 25) | def forward(self, src_ids, src_sids, src_pids, tgt_ids, tgt_sids, tgt_...

FILE: modules/text/text_generation/ernie_gen/module.py
  class ErnieGen (line 45) | class ErnieGen():
    method __init__ (line 46) | def __init__(self):
    method model (line 56) | def model(self):
    method finetune (line 61) | def finetune(
    method export (line 236) | def export(self,
    method _evaluate (line 292) | def _evaluate(self, model, data_loader, tokenizer, rouge1, rouge2, att...
    method _load_dataset (line 349) | def _load_dataset(self, datafiles):

FILE: modules/text/text_generation/ernie_gen/template/decode.py
  function gen_bias (line 34) | def gen_bias(encoder_inputs, decoder_inputs, step):
  function greedy_search_infilling (line 55) | def greedy_search_infilling(model,
  function log_softmax (line 120) | def log_softmax(x):
  function mask_prob (line 125) | def mask_prob(p, onehot_eos, finished):
  function hyp_score (line 131) | def hyp_score(log_probs, length, length_penalty):
  function beam_search_step (line 136) | def beam_search_step(state, logits, eos_id, beam_width, is_first_step, l...
  function beam_search_infilling (line 179) | def beam_search_infilling(model,
  function post_process (line 278) | def post_process(token):

FILE: modules/text/text_generation/ernie_gen_acrostic_poetry/decode.py
  function gen_bias (line 34) | def gen_bias(encoder_inputs, decoder_inputs, step):
  function greedy_search_infilling (line 55) | def greedy_search_infilling(model,
  function log_softmax (line 120) | def log_softmax(x):
  function mask_prob (line 125) | def mask_prob(p, onehot_eos, finished):
  function hyp_score (line 131) | def hyp_score(log_probs, length, length_penalty):
  function beam_search_step (line 136) | def beam_search_step(state, logits, eos_id, beam_width, is_first_step, l...
  function beam_search_infilling (line 179) | def beam_search_infilling(model,
  function post_process (line 278) | def post_process(token):

FILE: modules/text/text_generation/ernie_gen_acrostic_poetry/module.py
  class ErnieGen (line 41) | class ErnieGen(hub.NLPPredictionModule):
    method __init__ (line 42) | def __init__(self, line=4, word=7):
    method generate (line 64) | def generate(self, texts, use_gpu=False, beam_width=5):
    method add_module_config_arg (line 132) | def add_module_config_arg(self):
    method run_cmd (line 142) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/ernie_gen_couplet/decode.py
  function gen_bias (line 34) | def gen_bias(encoder_inputs, decoder_inputs, step):
  function greedy_search_infilling (line 55) | def greedy_search_infilling(model,
  function log_softmax (line 120) | def log_softmax(x):
  function mask_prob (line 125) | def mask_prob(p, onehot_eos, finished):
  function hyp_score (line 131) | def hyp_score(log_probs, length, length_penalty):
  function beam_search_step (line 136) | def beam_search_step(state, logits, eos_id, beam_width, is_first_step, l...
  function beam_search_infilling (line 179) | def beam_search_infilling(model,
  function post_process (line 278) | def post_process(token):

FILE: modules/text/text_generation/ernie_gen_couplet/module.py
  class ErnieGen (line 41) | class ErnieGen(hub.NLPPredictionModule):
    method __init__ (line 42) | def __init__(self):
    method generate (line 58) | def generate(self, texts, use_gpu=False, beam_width=5):
    method add_module_config_arg (line 121) | def add_module_config_arg(self):
    method run_cmd (line 131) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/ernie_gen_lover_words/decode.py
  function gen_bias (line 34) | def gen_bias(encoder_inputs, decoder_inputs, step):
  function greedy_search_infilling (line 55) | def greedy_search_infilling(model,
  function log_softmax (line 120) | def log_softmax(x):
  function mask_prob (line 125) | def mask_prob(p, onehot_eos, finished):
  function hyp_score (line 131) | def hyp_score(log_probs, length, length_penalty):
  function beam_search_step (line 136) | def beam_search_step(state, logits, eos_id, beam_width, is_first_step, l...
  function beam_search_infilling (line 179) | def beam_search_infilling(model,
  function post_process (line 278) | def post_process(token):

FILE: modules/text/text_generation/ernie_gen_lover_words/module.py
  class ErnieGen (line 41) | class ErnieGen(hub.NLPPredictionModule):
    method __init__ (line 42) | def __init__(self):
    method generate (line 58) | def generate(self, texts, use_gpu=False, beam_width=5):
    method add_module_config_arg (line 113) | def add_module_config_arg(self):
    method run_cmd (line 123) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/ernie_gen_poetry/decode.py
  function gen_bias (line 34) | def gen_bias(encoder_inputs, decoder_inputs, step):
  function greedy_search_infilling (line 55) | def greedy_search_infilling(model,
  function log_softmax (line 114) | def log_softmax(x):
  function mask_prob (line 119) | def mask_prob(p, onehot_eos, finished):
  function hyp_score (line 125) | def hyp_score(log_probs, length, length_penalty):
  function beam_search_step (line 130) | def beam_search_step(state, logits, eos_id, beam_width, is_first_step, l...
  function beam_search_infilling (line 173) | def beam_search_infilling(model,
  function post_process (line 267) | def post_process(token):

FILE: modules/text/text_generation/ernie_gen_poetry/module.py
  class ErnieGen (line 41) | class ErnieGen(hub.NLPPredictionModule):
    method __init__ (line 42) | def __init__(self):
    method generate (line 58) | def generate(self, texts, use_gpu=False, beam_width=5):
    method add_module_config_arg (line 130) | def add_module_config_arg(self):
    method run_cmd (line 140) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/ernie_tiny_couplet/module.py
  class ErnieTinyCouplet (line 32) | class ErnieTinyCouplet(hub.NLPPredictionModule):
    method _initialize (line 33) | def _initialize(self, use_gpu=False):
    method generate (line 66) | def generate(self, texts):
    method add_module_config_arg (line 80) | def add_module_config_arg(self):
    method run_cmd (line 88) | def run_cmd(self, argvs):
    method serving_method (line 118) | def serving_method(self, texts):

FILE: modules/text/text_generation/ernie_zeus/module.py
  function get_access_token (line 12) | def get_access_token(ak: str = None, sk: str = None) -> str:
  class ERNIEZeus (line 51) | class ERNIEZeus:
    method __init__ (line 53) | def __init__(self, ak: str = None, sk: str = None) -> None:
    method custom_generation (line 57) | def custom_generation(self,
    method text_generation (line 128) | def text_generation(self,
    method text_summarization (line 151) | def text_summarization(self,
    method copywriting_generation (line 175) | def copywriting_generation(self,
    method novel_continuation (line 199) | def novel_continuation(self,
    method answer_generation (line 223) | def answer_generation(self,
    method couplet_continuation (line 247) | def couplet_continuation(self,
    method composition_generation (line 271) | def composition_generation(self,
    method text_cloze (line 295) | def text_cloze(self,
    method cmd (line 319) | def cmd(self, argvs):
    method create_gradio_app (line 385) | def create_gradio_app(self):

FILE: modules/text/text_generation/ernie_zeus/test.py
  class TestHubModule (line 6) | class TestHubModule(unittest.TestCase):
    method setUpClass (line 9) | def setUpClass(cls) -> None:
    method test_custom_generation (line 12) | def test_custom_generation(self):
    method test_text_generation (line 16) | def test_text_generation(self):
    method test_text_summarization (line 20) | def test_text_summarization(self):
    method test_copywriting_generation (line 26) | def test_copywriting_generation(self):
    method test_modulenovel_continuation (line 30) | def test_modulenovel_continuation(self):
    method test_answer_generation (line 34) | def test_answer_generation(self):
    method test_couplet_continuation (line 38) | def test_couplet_continuation(self):
    method test_composition_generation (line 42) | def test_composition_generation(self):
    method test_text_cloze (line 46) | def test_text_cloze(self):

FILE: modules/text/text_generation/plato-mini/module.py
  class UnifiedTransformer (line 37) | class UnifiedTransformer(nn.Layer):
    method __init__ (line 38) | def __init__(self):
    method _convert_text_to_input (line 45) | def _convert_text_to_input(self, texts: List[str], max_seq_len: int):
    method _batchify (line 52) | def _batchify(self, data: List[List[str]], max_seq_len: int, batch_siz...
    method interactive_mode (line 101) | def interactive_mode(self, max_turn=3):
    method forward (line 112) | def forward(self,
    method predict (line 147) | def predict(self,

FILE: modules/text/text_generation/plato-mini/utils.py
  function post_process_response (line 18) | def post_process_response(token_ids: List[int], tokenizer):
  function get_in_turn_repetition (line 33) | def get_in_turn_repetition(pred: List[str], is_cn: bool = False):
  function select_response (line 52) | def select_response(ids,

FILE: modules/text/text_generation/plato2_en_base/model.py
  function post_process_context (line 21) | def post_process_context(token_ids, reader, merge=True):
  function post_process_response (line 37) | def post_process_response(token_ids, reader, merge=True):
  function get_cross_turn_repetition (line 54) | def get_cross_turn_repetition(context, pred_tokens, eos_idx, is_cn=False):
  function get_in_turn_repetition (line 74) | def get_in_turn_repetition(pred, is_cn=False):
  class Plato2EncoderLayer (line 91) | class Plato2EncoderLayer(nn.Layer):
    method __init__ (line 93) | def __init__(self, n_head, hidden_size, attn_dropout, act_dropout):
    method forward (line 105) | def forward(self, x, attn_mask, cache):
    method gen_cache (line 122) | def gen_cache(self, key):
  class Plato2Encoder (line 126) | class Plato2Encoder(nn.Layer):
    method __init__ (line 128) | def __init__(self, vocab_size, type_size, max_position_seq_len, num_la...
    method forward (line 147) | def forward(self, caches, token_ids, type_ids, pos_ids, generation_mas...
    method gen_input (line 158) | def gen_input(self, token_ids, type_ids, pos_ids, input_mask, aux_emb=...
    method gen_caches (line 178) | def gen_caches(self, key):
  class NSP (line 183) | class NSP(nn.Layer):
    method __init__ (line 185) | def __init__(self, vocab_size, type_size, max_position_seq_len, num_la...
    method forward (line 207) | def forward(self, inputs):
    method gen_input (line 230) | def gen_input(self, token_ids, type_ids, pos_ids, input_mask, aux_emb=...
  class Plato2InferModel (line 251) | class Plato2InferModel(nn.Layer):
    method __init__ (line 253) | def __init__(self,
    method forward (line 300) | def forward(self, inputs):
    method decode (line 326) | def decode(self, inputs, caches):
    method gen_nsp_input (line 374) | def gen_nsp_input(self, token_ids, pred_ids):
    method get_results (line 409) | def get_results(self, data_id, token_ids, pred_ids, probs):

FILE: modules/text/text_generation/plato2_en_base/module.py
  class Plato2 (line 46) | class Plato2(nn.Layer, hub.NLPPredictionModule):
    method __init__ (line 48) | def __init__(self):
    method setup_args (line 75) | def setup_args(self):
    method generate (line 111) | def generate(self, texts):
    method interactive_mode (line 149) | def interactive_mode(self, max_turn=6):
    method run_cmd (line 164) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/plato2_en_base/readers/dialog_reader.py
  class DialogReader (line 29) | class DialogReader(object):
    method add_cmdline_args (line 33) | def add_cmdline_args(cls, parser):
    method __init__ (line 64) | def __init__(self, args):
    method get_train_progress (line 106) | def get_train_progress(self):
    method _convert_example_to_record (line 110) | def _convert_example_to_record(self, example, is_infer):
    method _read_tsv (line 208) | def _read_tsv(self, fp, phase, is_infer, delimiter="\t", quotechar=None):
    method _read_numerical_file (line 223) | def _read_numerical_file(self, fp, delimiter=";"):
    method _read_file (line 234) | def _read_file(self, input_file, phase, is_infer):
    method _read_files (line 247) | def _read_files(self, filelist, phase, is_infer, shuffle_files):
    method _batch_reader (line 267) | def _batch_reader(self,
    method _distributed_batch_reader (line 353) | def _distributed_batch_reader(self,
    method data_generator (line 372) | def data_generator(self,
    method _gen_self_attn_mask (line 421) | def _gen_self_attn_mask(self,
    method _pad_batch_records (line 445) | def _pad_batch_records(self, batch_records, is_infer):
  function open_file (line 491) | def open_file(filename):

FILE: modules/text/text_generation/plato2_en_base/readers/nsp_reader.py
  class NSPReader (line 26) | class NSPReader(DialogReader):
    method add_cmdline_args (line 30) | def add_cmdline_args(cls, parser):
    method __init__ (line 42) | def __init__(self, args):
    method _convert_example_to_record (line 53) | def _convert_example_to_record(self, example, is_infer):
    method _mix_negative_sample (line 60) | def _mix_negative_sample(self, reader, neg_pool_size=2**16):
    method _batch_reader (line 105) | def _batch_reader(self,
    method _pad_batch_records (line 118) | def _pad_batch_records(self, batch_records, is_infer):

FILE: modules/text/text_generation/plato2_en_base/readers/plato_reader.py
  class PlatoReader (line 23) | class PlatoReader(DialogReader):
    method __init__ (line 26) | def __init__(self, args):
    method _pad_batch_records (line 31) | def _pad_batch_records(self, batch_records, is_infer):

FILE: modules/text/text_generation/plato2_en_base/utils/__init__.py
  function repeat_array (line 21) | def repeat_array(array, times):
  function gen_inputs (line 29) | def gen_inputs(inputs, latent_type_size):
  function pad_batch_data (line 53) | def pad_batch_data(insts, pad_id=0):

FILE: modules/text/text_generation/plato2_en_base/utils/args.py
  function str2bool (line 20) | def str2bool(v):
  class Args (line 30) | class Args(dict):
    method __getattr__ (line 36) | def __getattr__(self, name):
    method get (line 45) | def get(self, key, default_value=None):
    method __setattr__ (line 55) | def __setattr__(self, name, value):
    method save (line 58) | def save(self, filename):
    method load (line 62) | def load(self, filename, group_name=None):
  function parse_args (line 77) | def parse_args(parser: argparse.ArgumentParser, allow_unknown=False) -> ...

FILE: modules/text/text_generation/plato2_en_base/utils/masking.py
  function mask (line 19) | def mask(batch_tokens,

FILE: modules/text/text_generation/plato2_en_base/utils/tokenization.py
  function clean_text (line 23) | def clean_text(text):
  function preprocess_text (line 42) | def preprocess_text(inputs, remove_space=True, lower=False):
  function encode_pieces (line 56) | def encode_pieces(spm_model, text, return_unicode=True, sample=False):
  function encode_ids (line 69) | def encode_ids(spm_model, text, sample=False):
  function convert_to_unicode (line 76) | def convert_to_unicode(text):
  function load_vocab (line 86) | def load_vocab(vocab_file):
  function convert_by_vocab (line 101) | def convert_by_vocab(vocab, items):
  class SentencePieceTokenizer (line 109) | class SentencePieceTokenizer(object):
    method add_cmdline_args (line 113) | def add_cmdline_args(cls, parser):
    method __init__ (line 121) | def __init__(self, args):
    method tokenize (line 128) | def tokenize(self, text):
    method convert_tokens_to_ids (line 133) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 144) | def convert_ids_to_tokens(self, ids):
    method merge_subword (line 148) | def merge_subword(self, tokens):
    method convert_ids_to_str (line 163) | def convert_ids_to_str(self, ids):
  function _is_whitespace (line 172) | def _is_whitespace(char):
  function _is_control (line 184) | def _is_control(char):

FILE: modules/text/text_generation/plato2_en_large/model.py
  function post_process_context (line 21) | def post_process_context(token_ids, reader, merge=True):
  function post_process_response (line 37) | def post_process_response(token_ids, reader, merge=True):
  function get_cross_turn_repetition (line 54) | def get_cross_turn_repetition(context, pred_tokens, eos_idx, is_cn=False):
  function get_in_turn_repetition (line 74) | def get_in_turn_repetition(pred, is_cn=False):
  class Plato2EncoderLayer (line 91) | class Plato2EncoderLayer(nn.Layer):
    method __init__ (line 93) | def __init__(self, n_head, hidden_size, attn_dropout, act_dropout):
    method forward (line 105) | def forward(self, x, attn_mask, cache):
    method gen_cache (line 122) | def gen_cache(self, key):
  class Plato2Encoder (line 126) | class Plato2Encoder(nn.Layer):
    method __init__ (line 128) | def __init__(self, vocab_size, type_size, max_position_seq_len, num_la...
    method forward (line 147) | def forward(self, caches, token_ids, type_ids, pos_ids, generation_mas...
    method gen_input (line 158) | def gen_input(self, token_ids, type_ids, pos_ids, input_mask, aux_emb=...
    method gen_caches (line 178) | def gen_caches(self, key):
  class NSP (line 183) | class NSP(nn.Layer):
    method __init__ (line 185) | def __init__(self, vocab_size, type_size, max_position_seq_len, num_la...
    method forward (line 207) | def forward(self, inputs):
    method gen_input (line 230) | def gen_input(self, token_ids, type_ids, pos_ids, input_mask, aux_emb=...
  class Plato2InferModel (line 251) | class Plato2InferModel(nn.Layer):
    method __init__ (line 253) | def __init__(self,
    method forward (line 300) | def forward(self, inputs):
    method decode (line 326) | def decode(self, inputs, caches):
    method gen_nsp_input (line 374) | def gen_nsp_input(self, token_ids, pred_ids):
    method get_results (line 409) | def get_results(self, data_id, token_ids, pred_ids, probs):

FILE: modules/text/text_generation/plato2_en_large/module.py
  class Plato2 (line 46) | class Plato2(nn.Layer, hub.NLPPredictionModule):
    method __init__ (line 48) | def __init__(self):
    method setup_args (line 75) | def setup_args(self):
    method generate (line 111) | def generate(self, texts):
    method interactive_mode (line 149) | def interactive_mode(self, max_turn=6):
    method run_cmd (line 164) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/plato2_en_large/readers/dialog_reader.py
  class DialogReader (line 29) | class DialogReader(object):
    method add_cmdline_args (line 33) | def add_cmdline_args(cls, parser):
    method __init__ (line 64) | def __init__(self, args):
    method get_train_progress (line 106) | def get_train_progress(self):
    method _convert_example_to_record (line 110) | def _convert_example_to_record(self, example, is_infer):
    method _read_tsv (line 208) | def _read_tsv(self, fp, phase, is_infer, delimiter="\t", quotechar=None):
    method _read_numerical_file (line 223) | def _read_numerical_file(self, fp, delimiter=";"):
    method _read_file (line 234) | def _read_file(self, input_file, phase, is_infer):
    method _read_files (line 247) | def _read_files(self, filelist, phase, is_infer, shuffle_files):
    method _batch_reader (line 267) | def _batch_reader(self,
    method _distributed_batch_reader (line 353) | def _distributed_batch_reader(self,
    method data_generator (line 372) | def data_generator(self,
    method _gen_self_attn_mask (line 421) | def _gen_self_attn_mask(self,
    method _pad_batch_records (line 445) | def _pad_batch_records(self, batch_records, is_infer):
  function open_file (line 491) | def open_file(filename):

FILE: modules/text/text_generation/plato2_en_large/readers/nsp_reader.py
  class NSPReader (line 26) | class NSPReader(DialogReader):
    method add_cmdline_args (line 30) | def add_cmdline_args(cls, parser):
    method __init__ (line 42) | def __init__(self, args):
    method _convert_example_to_record (line 53) | def _convert_example_to_record(self, example, is_infer):
    method _mix_negative_sample (line 60) | def _mix_negative_sample(self, reader, neg_pool_size=2**16):
    method _batch_reader (line 105) | def _batch_reader(self,
    method _pad_batch_records (line 118) | def _pad_batch_records(self, batch_records, is_infer):

FILE: modules/text/text_generation/plato2_en_large/readers/plato_reader.py
  class PlatoReader (line 23) | class PlatoReader(DialogReader):
    method __init__ (line 26) | def __init__(self, args):
    method _pad_batch_records (line 31) | def _pad_batch_records(self, batch_records, is_infer):

FILE: modules/text/text_generation/plato2_en_large/utils/__init__.py
  function repeat_array (line 21) | def repeat_array(array, times):
  function gen_inputs (line 29) | def gen_inputs(inputs, latent_type_size):
  function pad_batch_data (line 53) | def pad_batch_data(insts, pad_id=0):

FILE: modules/text/text_generation/plato2_en_large/utils/args.py
  function str2bool (line 20) | def str2bool(v):
  class Args (line 30) | class Args(dict):
    method __getattr__ (line 36) | def __getattr__(self, name):
    method get (line 45) | def get(self, key, default_value=None):
    method __setattr__ (line 55) | def __setattr__(self, name, value):
    method save (line 58) | def save(self, filename):
    method load (line 62) | def load(self, filename, group_name=None):
  function parse_args (line 77) | def parse_args(parser: argparse.ArgumentParser, allow_unknown=False) -> ...

FILE: modules/text/text_generation/plato2_en_large/utils/masking.py
  function mask (line 19) | def mask(batch_tokens,

FILE: modules/text/text_generation/plato2_en_large/utils/tokenization.py
  function clean_text (line 23) | def clean_text(text):
  function preprocess_text (line 42) | def preprocess_text(inputs, remove_space=True, lower=False):
  function encode_pieces (line 56) | def encode_pieces(spm_model, text, return_unicode=True, sample=False):
  function encode_ids (line 69) | def encode_ids(spm_model, text, sample=False):
  function convert_to_unicode (line 76) | def convert_to_unicode(text):
  function load_vocab (line 86) | def load_vocab(vocab_file):
  function convert_by_vocab (line 101) | def convert_by_vocab(vocab, items):
  class SentencePieceTokenizer (line 109) | class SentencePieceTokenizer(object):
    method add_cmdline_args (line 113) | def add_cmdline_args(cls, parser):
    method __init__ (line 121) | def __init__(self, args):
    method tokenize (line 128) | def tokenize(self, text):
    method convert_tokens_to_ids (line 133) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 144) | def convert_ids_to_tokens(self, ids):
    method merge_subword (line 148) | def merge_subword(self, tokens):
    method convert_ids_to_str (line 163) | def convert_ids_to_str(self, ids):
  function _is_whitespace (line 172) | def _is_whitespace(char):
  function _is_control (line 184) | def _is_control(char):

FILE: modules/text/text_generation/reading_pictures_writing_poems/module.py
  class ReadingPicturesWritingPoems (line 18) | class ReadingPicturesWritingPoems:
    method __init__ (line 20) | def __init__(self):
    method is_chinese (line 28) | def is_chinese(self, string):
    method WritingPoem (line 45) | def WritingPoem(self, image, use_gpu=False):
    method run_cmd (line 78) | def run_cmd(self, argvs):
    method add_module_config_arg (line 106) | def add_module_config_arg(self):
    method add_module_input_arg (line 115) | def add_module_input_arg(self):
    method check_input_data (line 121) | def check_input_data(self, args):

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/MidAutumnDetection/module.py
  function base64_to_cv2 (line 15) | def base64_to_cv2(b64str):
  function cv2_to_base64 (line 22) | def cv2_to_base64(image):
  function read_images (line 28) | def read_images(paths):
  class MODULE (line 42) | class MODULE(hub.Module):
    method _initialize (line 43) | def _initialize(self, **kwargs):
    method predict (line 47) | def predict(self, images=None, paths=None, data=None, batch_size=1, us...
    method serving_method (line 66) | def serving_method(self, images, **kwargs):
    method run_cmd (line 95) | def run_cmd(self, argvs):
    method add_module_config_arg (line 113) | def add_module_config_arg(self):
    method add_module_input_arg (line 119) | def add_module_input_arg(self):

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/MidAutumnPoetry/model/decode.py
  function gen_bias (line 24) | def gen_bias(encoder_inputs, decoder_inputs, step):
  function greedy_search_infilling (line 40) | def greedy_search_infilling(model,
  function log_softmax (line 94) | def log_softmax(x):
  function mask_prob (line 99) | def mask_prob(p, onehot_eos, finished):
  function hyp_score (line 105) | def hyp_score(log_probs, length, length_penalty):
  function beam_search_step (line 110) | def beam_search_step(state, logits, eos_id, beam_width, is_first_step, l...
  function beam_search_infilling (line 157) | def beam_search_infilling(model,
  function post_process (line 251) | def post_process(token):

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/MidAutumnPoetry/model/file_utils.py
  function _fetch_from_remote (line 21) | def _fetch_from_remote(url, force_download=False):
  function add_docstring (line 60) | def add_docstring(doc):

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/MidAutumnPoetry/model/modeling_ernie.py
  function _build_linear (line 29) | def _build_linear(n_in, n_out, name, init, act=None):
  function _build_ln (line 38) | def _build_ln(n_in, name):
  function append_name (line 48) | def append_name(name, postfix):
  class AttentionLayer (line 57) | class AttentionLayer(D.Layer):
    method __init__ (line 58) | def __init__(self, cfg, name=None):
    method forward (line 78) | def forward(self, queries, keys, values, attn_bias, past_cache):
  class PositionwiseFeedForwardLayer (line 113) | class PositionwiseFeedForwardLayer(D.Layer):
    method __init__ (line 114) | def __init__(self, cfg, name=None):
    method forward (line 129) | def forward(self, inputs):
  class ErnieBlock (line 136) | class ErnieBlock(D.Layer):
    method __init__ (line 137) | def __init__(self, cfg, name=None):
    method forward (line 153) | def forward(self, inputs, attn_bias=None, past_cache=None):
  class ErnieEncoderStack (line 166) | class ErnieEncoderStack(D.Layer):
    method __init__ (line 167) | def __init__(self, cfg, name=None):
    method forward (line 172) | def forward(self, inputs, attn_bias=None, past_cache=None):
  class ErnieModel (line 192) | class ErnieModel(D.Layer):
    method __init__ (line 193) | def __init__(self, cfg, name=None):
    method eval (line 233) | def eval(self):
    method train (line 240) | def train(self):
    method forward (line 247) | def forward(self,

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/MidAutumnPoetry/model/modeling_ernie_gen.py
  class ErnieModelForGeneration (line 22) | class ErnieModelForGeneration(ErnieModel):
    method __init__ (line 23) | def __init__(self, cfg, name=None):
    method forward (line 42) | def forward(self, src_ids, *args, **kwargs):

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/MidAutumnPoetry/model/tokenizing_ernie.py
  function _wordpiece (line 31) | def _wordpiece(token, vocab, unk_token, prefix='##', sentencepiece_prefi...
  class ErnieTokenizer (line 66) | class ErnieTokenizer(object):
    method __init__ (line 67) | def __init__(self,
    method tokenize (line 102) | def tokenize(self, text):
    method convert_tokens_to_ids (line 127) | def convert_tokens_to_ids(self, tokens):
    method truncate (line 130) | def truncate(self, id1, id2, seqlen):
    method build_for_ernie (line 140) | def build_for_ernie(self, text_id, pair_id=[]):
    method encode (line 152) | def encode(self, text, pair=None, truncate_to=None):

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/MidAutumnPoetry/module.py
  class ErnieGen (line 43) | class ErnieGen(hub.NLPPredictionModule):
    method _initialize (line 44) | def _initialize(self):
    method generate (line 70) | def generate(self, texts, use_gpu=False, beam_width=5):
    method add_module_config_arg (line 125) | def add_module_config_arg(self):
    method run_cmd (line 135) | def run_cmd(self, argvs):

FILE: modules/text/text_generation/reading_pictures_writing_poems_for_midautumn/module.py
  class ReadingPicturesWritingPoems (line 25) | class ReadingPicturesWritingPoems(hub.Module):
    method _initialize (line 26) | def _initialize(self):
    method WritingPoem (line 37) | def WritingPoem(self, images, use_gpu=False):
    method run_cmd (line 68) | def run_cmd(self, argvs):
    method add_module_config_arg (line 97) | def add_module_config_arg(self):
    method add_module_input_arg (line 104) | def add_module_input_arg(self):
    method check_input_data (line 110) | def check_input_data(self, args):

FILE: modules/text/text_generation/unified_transformer-12L-cn-luge/module.py
  class UnifiedTransformer (line 37) | class UnifiedTransformer(nn.Layer):
    method __init__ (line 38) | def __init__(self):
    method _convert_text_to_input (line 45) | def _convert_text_to_input(self, texts: List[str], max_seq_len: int):
    method _batchify (line 52) | def _batchify(self, data: List[List[str]], max_seq_len: int, batch_siz...
    method interactive_mode (line 101) | def interactive_mode(self, max_turn=3):
    method forward (line 112) | def forward(self,
    method predict (line 147) | def predict(self,

FILE: modules/text/text_generation/unified_transformer-12L-cn-luge/utils.py
  function post_process_response (line 18) | def post_process_response(token_ids: List[int], tokenizer):
  function get_in_turn_repetition (line 33) | def get_in_turn_repetition(pred: List[str], is_cn: bool = False):
  function select_response (line 52) | def select_response(ids,

FILE: modules/text/text_generation/unified_transformer-12L-cn/module.py
  class UnifiedTransformer (line 37) | class UnifiedTransformer(nn.Layer):
    method __init__ (line 38) | def __init__(self):
    method _convert_text_to_input (line 45) | def _convert_text_to_input(self, texts: List[str], max_seq_len: int):
    method _batchify (line 52) | def _batchify(self, data: List[List[str]], max_seq_len: int, batch_siz...
    method interactive_mode (line 101) | def interactive_mode(self, max_turn=3):
    method forward (line 112) | def forward(self,
    method predict (line 147) | def predict(self,

FILE: modules/text/text_generation/unified_transformer-12L-cn/utils.py
  function post_process_response (line 18) | def post_process_response(token_ids: List[int], tokenizer):
  function get_in_turn_repetition (line 33) | def get_in_turn_repetition(pred: List[str], is_cn: bool = False):
  function select_response (line 52) | def select_response(ids,

FILE: modules/text/text_review/porn_detection_cnn/module.py
  class PornDetectionCNN (line 19) | class PornDetectionCNN(hub.NLPPredictionModule):
    method __init__ (line 21) | def __init__(self):
    method detection (line 39) | def detection(self, texts=[], data={}, use_gpu=False, batch_size=1):
    method get_labels (line 87) | def get_labels(self):

FILE: modules/text/text_review/porn_detection_cnn/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function get_predict_label (line 17) | def get_predict_label(pos_prob):
  function preprocess (line 30) | def preprocess(predicted_data, tokenizer, vocab, sequence_max_len=256):
  function postprocess (line 50) | def postprocess(predict_out, texts):

FILE: modules/text/text_review/porn_detection_gru/module.py
  class PornDetectionGRU (line 20) | class PornDetectionGRU(hub.NLPPredictionModule):
    method __init__ (line 22) | def __init__(self):
    method detection (line 40) | def detection(self, texts=[], data={}, use_gpu=False, batch_size=1):
    method get_labels (line 88) | def get_labels(self):

FILE: modules/text/text_review/porn_detection_gru/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function get_predict_label (line 17) | def get_predict_label(pos_prob):
  function preprocess (line 30) | def preprocess(predicted_data, tokenizer, vocab, sequence_max_len=256):
  function postprocess (line 50) | def postprocess(predict_out, texts):

FILE: modules/text/text_review/porn_detection_lstm/module.py
  class PornDetectionLSTM (line 19) | class PornDetectionLSTM(hub.NLPPredictionModule):
    method __init__ (line 21) | def __init__(self):
    method detection (line 39) | def detection(self, texts=[], data={}, use_gpu=False, batch_size=1):
    method get_labels (line 87) | def get_labels(self):

FILE: modules/text/text_review/porn_detection_lstm/processor.py
  function load_vocab (line 6) | def load_vocab(file_path):
  function get_predict_label (line 17) | def get_predict_label(pos_prob):
  function preprocess (line 30) | def preprocess(predicted_data, tokenizer, vocab, sequence_max_len=256):
  function postprocess (line 50) | def postprocess(predict_out, texts):

FILE: modules/text/text_to_knowledge/nptag/module.py
  class NPTag (line 19) | class NPTag(paddle.nn.Layer):
    method __init__ (line 20) | def __init__(self,
    method predict (line 28) | def predict(self, texts):
    method run_cmd (line 52) | def run_cmd(self, argvs):

FILE: modules/text/text_to_knowledge/wordtag/module.py
  class WordTag (line 19) | class WordTag(paddle.nn.Layer):
    method __init__ (line 20) | def __init__(self,
    method predict (line 28) | def predict(self, texts):
    method run_cmd (line 52) | def run_cmd(self, argvs):

FILE: modules/video/Video_editing/SkyAR/module.py
  class SkyAR (line 8) | class SkyAR(nn.Layer):
    method __init__ (line 9) | def __init__(self, model_path=None):
    method MagicSky (line 20) | def MagicSky(self,

FILE: modules/video/Video_editing/SkyAR/rain.py
  class Rain (line 7) | class Rain():
    method __init__ (line 8) | def __init__(self, rain_cap_path, rain_intensity=1.0, haze_intensity=4...
    method _get_rain_layer (line 17) | def _get_rain_layer(self):
    method _create_haze_layer (line 31) | def _create_haze_layer(self, rain_layer):
    method forward (line 34) | def forward(self, img):

FILE: modules/video/Video_editing/SkyAR/skybox.py
  class SkyBox (line 8) | class SkyBox():
    method __init__ (line 9) | def __init__(self, out_size, skybox_img, skybox_video, halo_effect, au...
    method tile_skybox_img (line 36) | def tile_skybox_img(self, imgtile):
    method load_skybox (line 44) | def load_skybox(self):
    method skymask_refinement (line 70) | def skymask_refinement(self, G_pred, img):
    method get_skybg_from_box (line 78) | def get_skybg_from_box(self, m):
    method skybox_tracking (line 92) | def skybox_tracking(self, frame, frame_prev, skymask):
    method relighting (line 135) | def relighting(self, img, skybg, skymask):
    method halo (line 156) | def halo(self, syneth, skybg, skymask):
    method skyblend (line 164) | def skyblend(self, img, img_prev, skymask):

FILE: modules/video/Video_editing/SkyAR/skyfilter.py
  class SkyFilter (line 10) | class SkyFilter():
    method __init__ (line 11) | def __init__(self, model_path, video_path, save_path, in_size, halo_ef...
    method synthesize (line 43) | def synthesize(self, img_HD, img_HD_prev):
    method run (line 64) | def run(self, preview_frames_num=0):

FILE: modules/video/Video_editing/SkyAR/utils.py
  function build_transformation_matrix (line 11) | def build_transformation_matrix(transform):
  function update_transformation_matrix (line 29) | def update_transformation_matrix(M, m):
  function estimate_partial_transform (line 41) | def estimate_partial_transform(matched_keypoints):
  function removeOutliers (line 63) | def removeOutliers(prev_pts, curr_pts):
  function boxfilter (line 77) | def boxfilter(img, r):
  function guidedfilter (line 94) | def guidedfilter(img, p, r, eps):

FILE: modules/video/classification/videotag_tsn_lstm/module.py
  class VideoTag (line 45) | class VideoTag(hub.Module):
    method _initialize (line 46) | def _initialize(self):
    method _extractor (line 57) | def _extractor(self, args, exe, place):
    method _predictor (line 81) | def _predictor(self, args, exe, place):
    method run_cmd (line 107) | def run_cmd(self, argsv):
    method classify (line 112) | def classify(self, paths, use_gpu=False, threshold=0.5, top_k=10):

FILE: modules/video/classification/videotag_tsn_lstm/resource/metrics/metrics_util.py
  class Metrics (line 30) | class Metrics(object):
    method __init__ (line 31) | def __init__(self, name, mode, metrics_args):
    method calculate_and_log_out (line 35) | def calculate_and_log_out(self, fetch_list, info=''):
    method accumulate (line 39) | def accumulate(self, fetch_list, info=''):
    method finalize_and_log_out (line 43) | def finalize_and_log_out(self, info='', savedir='./'):
    method reset (line 47) | def reset(self):
  class Youtube8mMetrics (line 52) | class Youtube8mMetrics(Metrics):
    method __init__ (line 53) | def __init__(self, name, mode, metrics_args):
    method calculate_and_log_out (line 64) | def calculate_and_log_out(self, fetch_list, info=''):
    method accumulate (line 74) | def accumulate(self, fetch_list, info=''):
    method finalize_and_log_out (line 89) | def finalize_and_log_out(self, info='', label_file='./label_3396.txt'):
    method reset (line 116) | def reset(self):
  class MetricsZoo (line 122) | class MetricsZoo(object):
    method __init__ (line 123) | def __init__(self):
    method regist (line 126) | def regist(self, name, metrics):
    method get (line 130) | def get(self, name, mode, cfg):
  function regist_metrics (line 141) | def regist_metrics(name, metrics):
  function get_metrics (line 145) | def get_metrics(name, mode, cfg):

FILE: modules/video/classification/videotag_tsn_lstm/resource/metrics/youtube8m/average_precision_calculator.py
  class AveragePrecisionCalculator (line 60) | class AveragePrecisionCalculator(object):
    method __init__ (line 63) | def __init__(self, top_n=None):
    method heap_size (line 83) | def heap_size(self):
    method num_accumulated_positives (line 88) | def num_accumulated_positives(self):
    method accumulate (line 92) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 133) | def clear(self):
    method peek_ap_at_n (line 138) | def peek_ap_at_n(self):
    method ap (line 154) | def ap(predictions, actuals):
    method ap_at_n (line 174) | def ap_at_n(predictions, actuals, n=20, total_num_positives=None):
    method _shuffle (line 237) | def _shuffle(predictions, actuals):
    method _zero_one_normalize (line 245) | def _zero_one_normalize(predictions, epsilon=1e-7):

FILE: modules/video/classification/videotag_tsn_lstm/resource/metrics/youtube8m/eval_util.py
  function flatten (line 22) | def flatten(l):
  function calculate_hit_at_one (line 27) | def calculate_hit_at_one(predictions, actuals):
  function calculate_precision_at_equal_recall_rate (line 44) | def calculate_precision_at_equal_recall_rate(predictions, actuals):
  function calculate_gap (line 71) | def calculate_gap(predictions, actuals, top_k=20):
  function top_k_by_class (line 92) | def top_k_by_class(predictions, labels, k=20):
  function top_k_triplets (line 129) | def top_k_triplets(predictions, labels, k=20):
  class EvaluationMetrics (line 138) | class EvaluationMetrics(object):
    method __init__ (line 141) | def __init__(self, num_class, top_k):
    method accumulate (line 161) | def accumulate(self, loss, predictions, labels):
    method get (line 195) | def get(self):
    method clear (line 218) | def clear(self):

FILE: modules/video/classification/videotag_tsn_lstm/resource/metrics/youtube8m/mean_average_precision_calculator.py
  class MeanAveragePrecisionCalculator (line 43) | class MeanAveragePrecisionCalculator(object):
    method __init__ (line 47) | def __init__(self, num_class):
    method accumulate (line 69) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 93) | def clear(self):
    method is_empty (line 97) | def is_empty(self):
    method peek_map_at_n (line 100) | def peek_map_at_n(self):

FILE: modules/video/classification/videotag_tsn_lstm/resource/models/attention_lstm/attention_lstm.py
  class AttentionLSTM (line 27) | class AttentionLSTM(ModelBase):
    method __init__ (line 28) | def __init__(self, name, cfg, mode='train'):
    method get_config (line 32) | def get_config(self):
    method build_input (line 46) | def build_input(self, use_dataloader):
    method build_model (line 58) | def build_model(self):
    method optimizer (line 91) | def optimizer(self):
    method loss (line 101) | def loss(self):
    method outputs (line 109) | def outputs(self):
    method feeds (line 112) | def feeds(self):
    method fetches (line 115) | def fetches(self):
    method weights_info (line 119) | def weights_info(self):
    method load_pretrain_params (line 123) | def load_pretrain_params(self, exe, pretrain, prog, place):

FILE: modules/video/classification/videotag_tsn_lstm/resource/models/attention_lstm/lstm_attention.py
  class LSTMAttentionModel (line 18) | class LSTMAttentionModel(object):
    method __init__ (line 21) | def __init__(self, bias_attr, embedding_size=512, lstm_size=1024, drop...
    method forward (line 26) | def forward(self, input, is_training):

FILE: modules/video/classification/videotag_tsn_lstm/resource/models/model.py
  function is_parameter (line 29) | def is_parameter(var):
  class NotImplementError (line 33) | class NotImplementError(Exception):
    method __init__ (line 36) | def __init__(self, model, function):
    method __str__ (line 41) | def __str__(self):
  class ModelNotFoundError (line 45) | class ModelNotFoundError(Exception):
    method __init__ (line 48) | def __init__(self, model_name, avail_models):
    method __str__ (line 53) | def __str__(self):
  class ModelBase (line 60) | class ModelBase(object):
    method __init__ (line 61) | def __init__(self, name, cfg, mode='train'):
    method build_model (line 70) | def build_model(self):
    method build_input (line 74) | def build_input(self, use_dataloader):
    method optimizer (line 78) | def optimizer(self):
    method outputs (line 82) | def outputs(self):
    method loss (line 86) | def loss(self):
    method feeds (line 90) | def feeds(self):
    method fetches (line 94) | def fetches(self):
    method weights_info (line 98) | def weights_info(self):
    method dataloader (line 102) | def dataloader(self):
    method epoch_num (line 105) | def epoch_num(self):
    method pretrain_info (line 109) | def pretrain_info(self):
    method load_pretrain_params (line 113) | def load_pretrain_params(self, exe, pretrain, prog, place):
    method load_test_weights (line 118) | def load_test_weights(self, exe, weights, prog):
    method get_config_from_sec (line 122) | def get_config_from_sec(self, sec, item, default=None):
  class ModelZoo (line 128) | class ModelZoo(object):
    method __init__ (line 129) | def __init__(self):
    method regist (line 132) | def regist(self, name, model):
    method get (line 136) | def get(self, name, cfg, mode='train'):
  function regist_model (line 147) | def regist_model(name, model):
  function get_model (line 151) | def get_model(name, cfg, mode='train'):

FILE: modules/video/classification/videotag_tsn_lstm/resource/models/tsn/tsn.py
  class TSN (line 29) | class TSN(ModelBase):
    method __init__ (line 30) | def __init__(self, name, cfg, mode='train'):
    method get_config (line 34) | def get_config(self):
    method build_input (line 53) | def build_input(self, use_dataloader=True):
    method create_model_args (line 73) | def create_model_args(self):
    method build_model (line 80) | def build_model(self):
    method optimizer (line 87) | def optimizer(self):
    method loss (line 105) | def loss(self):
    method outputs (line 112) | def outputs(self):
    method feeds (line 115) | def feeds(self):
    method fetches (line 120) | def fetches(self):
    method pretrain_info (line 134) | def pretrain_info(self):
    method weights_info (line 138) | def weights_info(self):
    method load_pretrain_params (line 141) | def load_pretrain_params(self, exe, pretrain, prog, place):

FILE: modules/video/classification/videotag_tsn_lstm/resource/models/tsn/tsn_res_model.py
  class TSN_ResNet (line 22) | class TSN_ResNet():
    method __init__ (line 23) | def __init__(self, layers=50, seg_num=7, is_training=True):
    method conv_bn_layer (line 28) | def conv_bn_layer(self, input, num_filters, filter_size, stride=1, gro...
    method shortcut (line 53) | def shortcut(self, input, ch_out, stride, name):
    method bottleneck_block (line 60) | def bottleneck_block(self, input, num_filters, stride, name):
    method net (line 72) | def net(self, input, class_dim=101):

FILE: modules/video/classification/videotag_tsn_lstm/resource/reader/kinetics_reader.py
  class KineticsReader (line 37) | class KineticsReader(DataReader):
    method __init__ (line 56) | def __init__(self, name, mode, cfg):
    method create_reader (line 75) | def create_reader(self):
    method _reader_creator (line 95) | def _reader_creator(self,
  function imgs_transform (line 144) | def imgs_transform(imgs, mode, seg_num, seglen, short_size, target_size,...
  function group_center_crop (line 156) | def group_center_crop(np_imgs, target_size):
  function group_scale (line 169) | def group_scale(imgs, target_size):
  function mp4_loader (line 190) | def mp4_loader(filepath, nsample, seglen, mode):

FILE: modules/video/classification/videotag_tsn_lstm/resource/reader/reader_utils.py
  class ReaderNotFoundError (line 16) | class ReaderNotFoundError(Exception):
    method __init__ (line 19) | def __init__(self, reader_name, avail_readers):
    method __str__ (line 24) | def __str__(self):
  class DataReader (line 31) | class DataReader(object):
    method __init__ (line 34) | def __init__(self, model_name, mode, cfg):
    method create_reader (line 39) | def create_reader(self):
    method get_config_from_sec (line 43) | def get_config_from_sec(self, sec, item, default=None):
  class ReaderZoo (line 49) | class ReaderZoo(object):
    method __init__ (line 50) | def __init__(self):
    method regist (line 53) | def regist(self, name, reader):
    method get (line 57) | def get(self, name, mode, cfg):
  function regist_reader (line 68) | def regist_reader(name, reader):
  function get_reader (line 72) | def get_reader(name, mode, cfg):

FILE: modules/video/classification/videotag_tsn_lstm/resource/utils/config_utils.py
  function parse_config (line 29) | def parse_config(cfg_file):
  function create_attr_dict (line 38) | def create_attr_dict(yaml_config):
  function merge_configs (line 55) | def merge_configs(cfg, sec, args_dict):
  function print_configs (line 69) | def print_configs(cfg, mode):

FILE: modules/video/classification/videotag_tsn_lstm/resource/utils/train_utils.py
  function log_lr_and_step (line 27) | def log_lr_and_step():
  function test_with_dataloader (line 49) | def test_with_dataloader(exe,
  function train_with_dataloader (line 71) | def train_with_dataloader(exe, train_prog, compiled_train_prog, train_da...
  function save_model (line 126) | def save_model(exe, program, save_dir, model_name, postfix=None, save_ty...

FILE: modules/video/classification/videotag_tsn_lstm/resource/utils/utility.py
  function _term (line 27) | def _term(sig_num, addition):
  class AttrDict (line 36) | class AttrDict(dict):
    method __getattr__ (line 37) | def __getattr__(self, key):
    method __setattr__ (line 40) | def __setattr__(self, key, value):
  function check_cuda (line 46) | def check_cuda(use_cuda, err = \
  function check_version (line 58) | def check_version():

FILE: modules/video/multiple_object_tracking/fairmot_dla34/dataset.py
  function default_collate_fn (line 38) | def default_collate_fn(batch):
  class MOTVideoStream (line 88) | class MOTVideoStream:
    method __init__ (line 98) | def __init__(self, video_stream=None, keep_ori_im=False, **kwargs):
    method set_kwargs (line 118) | def set_kwargs(self, **kwargs):
    method set_transform (line 123) | def set_transform(self, transform):
    method set_epoch (line 126) | def set_epoch(self, epoch_id):
    method parse_dataset (line 129) | def parse_dataset(self):
    method __iter__ (line 132) | def __iter__(self):
  class MOTImageStream (line 156) | class MOTImageStream:
    method __init__ (line 165) | def __init__(self, sample_num=-1, keep_ori_im=False, **kwargs):
    method add_image (line 175) | def add_image(self, image):
    method set_kwargs (line 178) | def set_kwargs(self, **kwargs):
    method set_transform (line 183) | def set_transform(self, transform):
    method set_epoch (line 186) | def set_epoch(self, epoch_id):
    method parse_dataset (line 189) | def parse_dataset(self):
    method __iter__ (line 192) | def __iter__(self):
  class MOTVideoStreamReader (line 215) | class MOTVideoStreamReader:
    method __init__ (line 218) | def __init__(self, sample_transforms=[], batch_size=1, drop_last=False...
    method __call__ (line 225) | def __call__(
    method __len__ (line 239) | def __len__(self):
    method __iter__ (line 242) | def __iter__(self):
    method to_tensor (line 245) | def to_tensor(self, batch):
    method __next__ (line 253) | def __next__(self):
    method next (line 264) | def next(self):

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/matching/deepsort_matching.py
  function iou_1toN (line 36) | def iou_1toN(bbox, candidates):
  function iou_cost (line 68) | def iou_cost(tracks, detections, track_indices=None, detection_indices=N...
  function _nn_euclidean_distance (line 102) | def _nn_euclidean_distance(s, q):
  function _nn_cosine_distance (line 124) | def _nn_cosine_distance(s, q):
  class NearestNeighborDistanceMetric (line 143) | class NearestNeighborDistanceMetric(object):
    method __init__ (line 160) | def __init__(self, metric, matching_threshold, budget=None):
    method partial_fit (line 171) | def partial_fit(self, features, targets, active_targets):
    method distance (line 187) | def distance(self, features, targets):
  function min_cost_matching (line 206) | def min_cost_matching(distance_metric, max_distance, tracks, detections,...
  function matching_cascade (line 267) | def matching_cascade(distance_metric,
  function gate_cost_matrix (line 329) | def gate_cost_matrix(kf,

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/matching/jde_matching.py
  function merge_matches (line 44) | def merge_matches(m1, m2, shape):
  function linear_assignment (line 61) | def linear_assignment(cost_matrix, thresh):
  function bbox_ious (line 81) | def bbox_ious(atlbrs, btlbrs):
  function iou_distance (line 102) | def iou_distance(atracks, btracks):
  function embedding_distance (line 119) | def embedding_distance(tracks, detections, metric='euclidean'):
  function fuse_motion (line 132) | def fuse_motion(kf, cost_matrix, tracks, detections, only_position=False...

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/motion/kalman_filter.py
  class KalmanFilter (line 31) | class KalmanFilter(object):
    method __init__ (line 48) | def __init__(self):
    method initiate (line 63) | def initiate(self, measurement):
    method predict (line 88) | def predict(self, mean, covariance):
    method project (line 118) | def project(self, mean, covariance):
    method multi_predict (line 139) | def multi_predict(self, mean, covariance):
    method update (line 174) | def update(self, mean, covariance, measurement):
    method gating_distance (line 200) | def gating_distance(self, mean, covariance, measurements, only_positio...

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/tracker/base_jde_tracker.py
  class TrackState (line 33) | class TrackState(object):
  class BaseTrack (line 40) | class BaseTrack(object):
    method end_frame (line 59) | def end_frame(self):
    method next_id (line 63) | def next_id():
    method activate (line 67) | def activate(self, *args):
    method predict (line 70) | def predict(self):
    method update (line 73) | def update(self, *args, **kwargs):
    method mark_lost (line 76) | def mark_lost(self):
    method mark_removed (line 79) | def mark_removed(self):
  class STrack (line 83) | class STrack(BaseTrack):
    method __init__ (line 84) | def __init__(self, tlwh, score, temp_feat, buffer_size=30):
    method update_features (line 99) | def update_features(self, feat):
    method predict (line 109) | def predict(self):
    method multi_predict (line 116) | def multi_predict(stracks, kalman_filter):
    method activate (line 128) | def activate(self, kalman_filter, frame_id):
    method re_activate (line 141) | def re_activate(self, new_track, frame_id, new_id=False):
    method update (line 153) | def update(self, new_track, frame_id, update_feature=True):
    method tlwh (line 167) | def tlwh(self):
    method tlbr (line 180) | def tlbr(self):
    method tlwh_to_xyah (line 190) | def tlwh_to_xyah(tlwh):
    method to_xyah (line 200) | def to_xyah(self):
    method tlbr_to_tlwh (line 204) | def tlbr_to_tlwh(tlbr):
    method tlwh_to_tlbr (line 210) | def tlwh_to_tlbr(tlwh):
    method __repr__ (line 215) | def __repr__(self):
  function joint_stracks (line 219) | def joint_stracks(tlista, tlistb):
  function sub_stracks (line 233) | def sub_stracks(tlista, tlistb):
  function remove_duplicate_stracks (line 244) | def remove_duplicate_stracks(stracksa, stracksb):

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/tracker/base_sde_tracker.py
  class TrackState (line 23) | class TrackState(object):
  class Track (line 36) | class Track(object):
    method __init__ (line 64) | def __init__(self, mean, covariance, track_id, n_init, max_age, featur...
    method to_tlwh (line 80) | def to_tlwh(self):
    method to_tlbr (line 87) | def to_tlbr(self):
    method predict (line 93) | def predict(self, kalman_filter):
    method update (line 102) | def update(self, kalman_filter, detection):
    method mark_missed (line 115) | def mark_missed(self):
    method is_tentative (line 123) | def is_tentative(self):
    method is_confirmed (line 127) | def is_confirmed(self):
    method is_deleted (line 131) | def is_deleted(self):

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/tracker/jde_tracker.py
  class FrozenJDETracker (line 33) | class FrozenJDETracker(object):
    method __init__ (line 57) | def __init__(self,
    method update (line 88) | def update(self, pred_dets, pred_embs):

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/utils.py
  class Timer (line 32) | class Timer(object):
    method __init__ (line 37) | def __init__(self):
    method tic (line 45) | def tic(self):
    method toc (line 50) | def toc(self, average=True):
    method clear (line 61) | def clear(self):
  class Detection (line 70) | class Detection(object):
    method __init__ (line 82) | def __init__(self, tlwh, confidence, feature):
    method to_tlbr (line 87) | def to_tlbr(self):
    method to_xyah (line 96) | def to_xyah(self):
  function load_det_results (line 107) | def load_det_results(det_file, num_frames):
  function scale_coords (line 122) | def scale_coords(coords, input_shape, im_shape, scale_factor):
  function clip_box (line 135) | def clip_box(xyxy, input_shape, im_shape, scale_factor):
  function get_crops (line 145) | def get_crops(xyxy, ori_img, pred_scores, w, h):
  function preprocess_reid (line 164) | def preprocess_reid(imgs, w=64, h=192, mean=[0.485, 0.456, 0.406], std=[...

FILE: modules/video/multiple_object_tracking/fairmot_dla34/modeling/mot/visualization.py
  function tlwhs_to_tlbrs (line 19) | def tlwhs_to_tlbrs(tlwhs):
  function get_color (line 28) | def get_color(idx):
  function resize_image (line 34) | def resize_image(image, max_size=800):
  function plot_tracking (line 41) | def plot_tracking(image, tlwhs, obj_ids, scores=None, frame_id=0, fps=0....
  function plot_trajectory (line 87) | def plot_trajectory(image, tlwhs, track_ids):
  function plot_detections (line 97) | def plot_detections(image, tlbrs, scores=None, color=(255, 0, 0), ids=No...

FILE: modules/video/multiple_object_tracking/fairmot_dla34/module.py
  class FairmotTracker_1088x608 (line 44) | class FairmotTracker_1088x608:
    method __init__ (line 46) | def __init__(self):
    method tracking (line 49) | def tracking(self, video_stream, output_dir='mot_result', visualizatio...
    method stream_mode (line 85) | def stream_mode(self, output_dir='mot_result', visualization=True, dra...
    method __enter__ (line 113) | def __enter__(self):
    method __exit__ (line 121) | def __exit__(self, exc_type, exc_value, traceback):
    method predict (line 149) | def predict(self, images: list = []):
    method run_cmd (line 174) | def run_cmd(self, argvs: list):
    method signalhandler (line 197) | def signalhandler(self, signum, frame):
    method add_module_config_arg (line 227) | def add_module_config_arg(self):
    method add_module_input_arg (line 245) | def add_module_input_arg(self):

FILE: modules/video/multiple_object_tracking/fairmot_dla34/tracker.py
  class StreamTracker (line 36) | class StreamTracker(object):
    method __init__ (line 37) | def __init__(self, cfg, mode='eval'):
    method load_weights_jde (line 51) | def load_weights_jde(self, weights):
    method _eval_seq_jde (line 54) | def _eval_seq_jde(self, dataloader, save_dir=None, show_image=False, f...
    method _eval_seq_jde_single_image (line 97) | def _eval_seq_jde_single_image(self, iterator, save_dir=None, show_ima...
    method imagestream_predict (line 136) | def imagestream_predict(self, output_dir, data_type='mot', model_type=...
    method videostream_predict (line 169) | def videostream_predict(self,
    method write_mot_results (line 228) | def write_mot_results(self, filename, results, data_type='mot'):
    method save_results (line 250) | def save_results(self, data, frame_id, online_ids, online_tlwhs, onlin...

FILE: modules/video/multiple_object_tracking/fairmot_dla34/utils.py
  class Timer (line 4) | class Timer(object):
    method __init__ (line 9) | def __init__(self):
    method tic (line 17) | def tic(self):
    method toc (line 22) | def toc(self, average=True):
    method clear (line 33) | def clear(self):

FILE: modules/video/multiple_object_tracking/jde_darknet53/dataset.py
  function default_collate_fn (line 39) | def default_collate_fn(batch):
  class MOTVideoStream (line 89) | class MOTVideoStream:
    method __init__ (line 99) | def __init__(self, video_stream=None, keep_ori_im=False, **kwargs):
    method set_kwargs (line 119) | def set_kwargs(self, **kwargs):
    method set_transform (line 124) | def set_transform(self, transform):
    method set_epoch (line 127) | def set_epoch(self, epoch_id):
    method parse_dataset (line 130) | def parse_dataset(self):
    method __iter__ (line 133) | def __iter__(self):
  class MOTImageStream (line 157) | class MOTImageStream:
    method __init__ (line 166) | def __init__(self, sample_num=-1, keep_ori_im=False, **kwargs):
    method add_image (line 176) | def add_image(self, image):
    method set_kwargs (line 179) | def set_kwargs(self, **kwargs):
    method set_transform (line 184) | def set_transform(self, transform):
    method set_epoch (line 187) | def set_epoch(self, epoch_id):
    method parse_dataset (line 190) | def parse_dataset(self):
    method __iter__ (line 193) | def __iter__(self):
  class MOTVideoStreamReader (line 216) | class MOTVideoStreamReader:
    method __init__ (line 219) | def __init__(self, sample_transforms=[], batch_size=1, drop_last=False...
    method __call__ (line 226) | def __call__(
    method __len__ (line 240) | def __len__(self):
    method __iter__ (line 243) | def __iter__(self):
    method to_tensor (line 246) | def to_tensor(self, batch):
    method __next__ (line 254) | def __next__(self):
    method next (line 265) | def next(self):

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/matching/deepsort_matching.py
  function iou_1toN (line 36) | def iou_1toN(bbox, candidates):
  function iou_cost (line 68) | def iou_cost(tracks, detections, track_indices=None, detection_indices=N...
  function _nn_euclidean_distance (line 102) | def _nn_euclidean_distance(s, q):
  function _nn_cosine_distance (line 124) | def _nn_cosine_distance(s, q):
  class NearestNeighborDistanceMetric (line 143) | class NearestNeighborDistanceMetric(object):
    method __init__ (line 160) | def __init__(self, metric, matching_threshold, budget=None):
    method partial_fit (line 171) | def partial_fit(self, features, targets, active_targets):
    method distance (line 187) | def distance(self, features, targets):
  function min_cost_matching (line 206) | def min_cost_matching(distance_metric, max_distance, tracks, detections,...
  function matching_cascade (line 267) | def matching_cascade(distance_metric,
  function gate_cost_matrix (line 329) | def gate_cost_matrix(kf,

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/matching/jde_matching.py
  function merge_matches (line 44) | def merge_matches(m1, m2, shape):
  function linear_assignment (line 61) | def linear_assignment(cost_matrix, thresh):
  function bbox_ious (line 81) | def bbox_ious(atlbrs, btlbrs):
  function iou_distance (line 102) | def iou_distance(atracks, btracks):
  function embedding_distance (line 119) | def embedding_distance(tracks, detections, metric='euclidean'):
  function fuse_motion (line 132) | def fuse_motion(kf, cost_matrix, tracks, detections, only_position=False...

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/motion/kalman_filter.py
  class KalmanFilter (line 31) | class KalmanFilter(object):
    method __init__ (line 48) | def __init__(self):
    method initiate (line 63) | def initiate(self, measurement):
    method predict (line 88) | def predict(self, mean, covariance):
    method project (line 118) | def project(self, mean, covariance):
    method multi_predict (line 139) | def multi_predict(self, mean, covariance):
    method update (line 174) | def update(self, mean, covariance, measurement):
    method gating_distance (line 200) | def gating_distance(self, mean, covariance, measurements, only_positio...

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/tracker/base_jde_tracker.py
  class TrackState (line 33) | class TrackState(object):
  class BaseTrack (line 40) | class BaseTrack(object):
    method end_frame (line 59) | def end_frame(self):
    method next_id (line 63) | def next_id():
    method activate (line 67) | def activate(self, *args):
    method predict (line 70) | def predict(self):
    method update (line 73) | def update(self, *args, **kwargs):
    method mark_lost (line 76) | def mark_lost(self):
    method mark_removed (line 79) | def mark_removed(self):
  class STrack (line 83) | class STrack(BaseTrack):
    method __init__ (line 84) | def __init__(self, tlwh, score, temp_feat, buffer_size=30):
    method update_features (line 99) | def update_features(self, feat):
    method predict (line 109) | def predict(self):
    method multi_predict (line 116) | def multi_predict(stracks, kalman_filter):
    method activate (line 128) | def activate(self, kalman_filter, frame_id):
    method re_activate (line 141) | def re_activate(self, new_track, frame_id, new_id=False):
    method update (line 153) | def update(self, new_track, frame_id, update_feature=True):
    method tlwh (line 167) | def tlwh(self):
    method tlbr (line 180) | def tlbr(self):
    method tlwh_to_xyah (line 190) | def tlwh_to_xyah(tlwh):
    method to_xyah (line 200) | def to_xyah(self):
    method tlbr_to_tlwh (line 204) | def tlbr_to_tlwh(tlbr):
    method tlwh_to_tlbr (line 210) | def tlwh_to_tlbr(tlwh):
    method __repr__ (line 215) | def __repr__(self):
  function joint_stracks (line 219) | def joint_stracks(tlista, tlistb):
  function sub_stracks (line 233) | def sub_stracks(tlista, tlistb):
  function remove_duplicate_stracks (line 244) | def remove_duplicate_stracks(stracksa, stracksb):

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/tracker/base_sde_tracker.py
  class TrackState (line 23) | class TrackState(object):
  class Track (line 36) | class Track(object):
    method __init__ (line 64) | def __init__(self, mean, covariance, track_id, n_init, max_age, featur...
    method to_tlwh (line 80) | def to_tlwh(self):
    method to_tlbr (line 87) | def to_tlbr(self):
    method predict (line 93) | def predict(self, kalman_filter):
    method update (line 102) | def update(self, kalman_filter, detection):
    method mark_missed (line 115) | def mark_missed(self):
    method is_tentative (line 123) | def is_tentative(self):
    method is_confirmed (line 127) | def is_confirmed(self):
    method is_deleted (line 131) | def is_deleted(self):

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/tracker/jde_tracker.py
  class FrozenJDETracker (line 33) | class FrozenJDETracker(object):
    method __init__ (line 57) | def __init__(self,
    method update (line 88) | def update(self, pred_dets, pred_embs):

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/utils.py
  class Timer (line 32) | class Timer(object):
    method __init__ (line 37) | def __init__(self):
    method tic (line 45) | def tic(self):
    method toc (line 50) | def toc(self, average=True):
    method clear (line 61) | def clear(self):
  class Detection (line 70) | class Detection(object):
    method __init__ (line 82) | def __init__(self, tlwh, confidence, feature):
    method to_tlbr (line 87) | def to_tlbr(self):
    method to_xyah (line 96) | def to_xyah(self):
  function load_det_results (line 107) | def load_det_results(det_file, num_frames):
  function scale_coords (line 122) | def scale_coords(coords, input_shape, im_shape, scale_factor):
  function clip_box (line 135) | def clip_box(xyxy, input_shape, im_shape, scale_factor):
  function get_crops (line 145) | def get_crops(xyxy, ori_img, pred_scores, w, h):
  function preprocess_reid (line 164) | def preprocess_reid(imgs, w=64, h=192, mean=[0.485, 0.456, 0.406], std=[...

FILE: modules/video/multiple_object_tracking/jde_darknet53/modeling/mot/visualization.py
  function tlwhs_to_tlbrs (line 19) | def tlwhs_to_tlbrs(tlwhs):
  function get_color (line 28) | def get_color(idx):
  function resize_image (line 34) | def resize_image(image, max_size=800):
  function plot_tracking (line 41) | def plot_tracking(image, tlwhs, obj_ids, scores=None, frame_id=0, fps=0....
  function plot_trajectory (line 87) | def plot_trajectory(image, tlwhs, track_ids):
  function plot_detections (line 97) | def plot_detections(image, tlbrs, scores=None, color=(255, 0, 0), ids=No...

FILE: modules/video/multiple_object_tracking/jde_darknet53/module.py
  class JDETracker_1088x608 (line 45) | class JDETracker_1088x608:
    method __init__ (line 47) | def __init__(self):
    method tracking (line 50) | def tracking(self, video_stream, output_dir='mot_result', visualizatio...
    method stream_mode (line 86) | def stream_mode(self, output_dir='mot_result', visualization=True, dra...
    method __enter__ (line 114) | def __enter__(self):
    method __exit__ (line 122) | def __exit__(self, exc_type, exc_value, traceback):
    method predict (line 150) | def predict(self, images: list = []):
    method run_cmd (line 175) | def run_cmd(self, argvs: list):
    method signalhandler (line 198) | def signalhandler(self, signum, frame):
    method add_module_config_arg (line 228) | def add_module_config_arg(self):
    method add_module_input_arg (line 246) | def add_module_input_arg(self):

FILE: modules/video/multiple_object_tracking/jde_darknet53/tracker.py
  class StreamTracker (line 36) | class StreamTracker(object):
    method __init__ (line 37) | def __init__(self, cfg, mode='eval'):
    method load_weights_jde (line 50) | def load_weights_jde(self, weights):
    method _eval_seq_jde (line 53) | def _eval_seq_jde(self, dataloader, save_dir=None, show_image=False, f...
    method _eval_seq_jde_single_image (line 96) | def _eval_seq_jde_single_image(self, iterator, save_dir=None, show_ima...
    method imagestream_predict (line 136) | def imagestream_predict(self, output_dir, data_type='mot', model_type=...
    method videostream_predict (line 169) | def videostream_predict(self,
    method write_mot_results (line 228) | def write_mot_results(self, filename, results, data_type='mot'):
    method save_results (line 250) | def save_results(self, data, frame_id, online_ids, online_tlwhs, onlin...

FILE: modules/video/multiple_object_tracking/jde_darknet53/utils.py
  class Timer (line 4) | class Timer(object):
    method __init__ (line 9) | def __init__(self):
    method tic (line 17) | def tic(self):
    method toc (line 22) | def toc(self, average=True):
    method clear (line 33) | def clear(self):

FILE: paddlehub/__init__.py
  function load (line 74) | def load(*args, **kwargs):
  function list (line 86) | def list(*args, **kwargs):
  function help (line 98) | def help(*args, **kwargs):

FILE: paddlehub/commands/clear.py
  function file_size_in_human_format (line 24) | def file_size_in_human_format(size: int) -> str:
  class ClearCommand (line 37) | class ClearCommand:
    method execute (line 38) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/config.py
  class ConfigCommand (line 25) | class ConfigCommand:
    method show_config (line 27) | def show_config():
    method show_help (line 32) | def show_help():
    method execute (line 46) | def execute(self, argv):

FILE: paddlehub/commands/convert.py
  class ConvertCommand (line 34) | class ConvertCommand:
    method __init__ (line 35) | def __init__(self):
    method create_module_tar (line 44) | def create_module_tar(self):
    method create_module_py (line 60) | def create_module_py(self):
    method create_init_py (line 78) | def create_init_py(self):
    method create_serving_demo_py (line 84) | def create_serving_demo_py(self):
    method show_help (line 95) | def show_help():
    method execute (line 109) | def execute(self, argv):

FILE: paddlehub/commands/download.py
  class DownloadCommand (line 26) | class DownloadCommand:
    method execute (line 27) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/help.py
  class HelpCommand (line 23) | class HelpCommand:
    method execute (line 24) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/hub.py
  class HubCommand (line 23) | class HubCommand:
    method execute (line 24) | def execute(self, argv):

FILE: paddlehub/commands/install.py
  class InstallCommand (line 27) | class InstallCommand:
    method __init__ (line 28) | def __init__(self):
    method execute (line 35) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/list.py
  class ListCommand (line 25) | class ListCommand:
    method execute (line 26) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/run.py
  class RunCommand (line 29) | class RunCommand:
    method execute (line 30) | def execute(self, argv: List) -> bool:
    method run_module_v1 (line 61) | def run_module_v1(self, module, argv: List) -> Any:

FILE: paddlehub/commands/search.py
  class SearchCommand (line 28) | class SearchCommand:
    method execute (line 29) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/serving.py
  function number_of_workers (line 34) | def number_of_workers():
  function pid_is_exist (line 41) | def pid_is_exist(pid: int):
  class ServingCommand (line 65) | class ServingCommand:
    method dump_pid_file (line 69) | def dump_pid_file(self):
    method load_pid_file (line 82) | def load_pid_file(filepath: str, port: int = None):
    method stop_serving (line 97) | def stop_serving(self, port: int):
    method start_bert_serving (line 125) | def start_bert_serving(args):
    method preinstall_modules (line 143) | def preinstall_modules(self):
    method start_app_with_args (line 168) | def start_app_with_args(self):
    method start_zmq_serving_with_args (line 185) | def start_zmq_serving_with_args(self):
    method start_single_app_with_args (line 211) | def start_single_app_with_args(self):
    method start_serving (line 227) | def start_serving(self):
    method show_help (line 248) | def show_help():
    method parse_args (line 287) | def parse_args(self):
    method execute (line 324) | def execute(self, argv):

FILE: paddlehub/commands/show.py
  class ShowCommand (line 26) | class ShowCommand:
    method execute (line 27) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/uninstall.py
  class UninstallCommand (line 24) | class UninstallCommand:
    method execute (line 25) | def execute(self, argv: List) -> bool:

FILE: paddlehub/commands/utils.py
  function _CommandDict (line 19) | def _CommandDict():
  function register (line 26) | def register(name: str, description: str = '') -> Any:
  function get_command (line 49) | def get_command(name: str) -> Any:
  function execute (line 58) | def execute():

FILE: paddlehub/commands/version.py
  class VersionCommand (line 23) | class VersionCommand:
    method execute (line 24) | def execute(self, argv: List) -> bool:

FILE: paddlehub/compat/datasets/base_dataset.py
  class InputExample (line 21) | class InputExample(object):
    method __init__ (line 37) | def __init__(self, guid, text_a, text_b=None, label=None):
    method __str__ (line 43) | def __str__(self):
  class BaseDataset (line 50) | class BaseDataset(object):
    method __init__ (line 51) | def __init__(self,
    method get_train_examples (line 102) | def get_train_examples(self):
    method get_dev_examples (line 105) | def get_dev_examples(self):
    method get_test_examples (line 108) | def get_test_examples(self):
    method get_val_examples (line 111) | def get_val_examples(self):
    method get_predict_examples (line 114) | def get_predict_examples(self):
    method get_examples (line 117) | def get_examples(self, phase):
    method get_labels (line 131) | def get_labels(self):
    method num_labels (line 135) | def num_labels(self):
    method label_dict (line 139) | def label_dict(self):
    method _load_train_examples (line 142) | def _load_train_examples(self):
    method _load_dev_examples (line 146) | def _load_dev_examples(self):
    method _load_test_examples (line 150) | def _load_test_examples(self):
    method _load_predict_examples (line 154) | def _load_predict_examples(self):
    method _read_file (line 158) | def _read_file(self, path, phase=None):
    method _load_label_data (line 161) | def _load_label_data(self):
    method __str__ (line 165) | def __str__(self):

FILE: paddlehub/compat/datasets/couplet.py
  class Couplet (line 27) | class Couplet(GenerationDataset):
    method __init__ (line 30) | def __init__(self, tokenizer=None, max_seq_len=None):
    method _read_file (line 43) | def _read_file(self, input_file, phase=None):

FILE: paddlehub/compat/datasets/nlp_dataset.py
  class BaseNLPDataset (line 29) | class BaseNLPDataset(BaseDataset):
    method __init__ (line 30) | def __init__(self,
    method train_records (line 64) | def train_records(self):
    method dev_records (line 74) | def dev_records(self):
    method test_records (line 84) | def test_records(self):
    method predict_records (line 94) | def predict_records(self):
    method _read_file (line 103) | def _read_file(self, input_file, phase=None):
    method _convert_examples_to_records (line 139) | def _convert_examples_to_records(self, examples, phase):
    method get_train_records (line 166) | def get_train_records(self, shuffle=False):
    method get_dev_records (line 169) | def get_dev_records(self, shuffle=False):
    method get_test_records (line 172) | def get_test_records(self, shuffle=False):
    method get_val_records (line 175) | def get_val_records(self, shuffle=False):
    method get_predict_records (line 178) | def get_predict_records(self, shuffle=False):
    method get_records (line 181) | def get_records(self, phase, shuffle=False):
    method get_feed_list (line 199) | def get_feed_list(self, phase):
    method batch_records_generator (line 207) | def batch_records_generator(self, phase, batch_size, shuffle=True, pad...
  class GenerationDataset (line 255) | class GenerationDataset(BaseNLPDataset):
    method __init__ (line 256) | def __init__(self,
    method _convert_examples_to_records (line 293) | def _convert_examples_to_records(self, examples, phase):

FILE: paddlehub/compat/module/module_v1.py
  class ModuleV1 (line 30) | class ModuleV1(object):
    method __init__ (line 39) | def __init__(self, name: str = None, directory: str = None, version: s...
    method _load_processor (line 57) | def _load_processor(self):
    method _load_assets (line 67) | def _load_assets(self):
    method _load_parameters (line 73) | def _load_parameters(self):
    method _load_extra_info (line 101) | def _load_extra_info(self):
    method _generate_func (line 108) | def _generate_func(self):
    method _load_model (line 112) | def _load_model(self):
    method context (line 125) | def context(self,
    method _update_bert_max_seq_len (line 158) | def _update_bert_max_seq_len(self, program: paddle.static.Program, fee...
    method __call__ (line 173) | def __call__(self, sign_name: str, data: dict, use_gpu: bool = False, ...
    method get_py_requirements (line 215) | def get_py_requirements(cls) -> List[str]:
    method load (line 220) | def load(cls, directory: str) -> EasyDict:
    method load_module_info (line 241) | def load_module_info(cls, directory: str) -> EasyDict:
    method assets_path (line 252) | def assets_path(self):
    method get_name_prefix (line 255) | def get_name_prefix(self):
    method is_runnable (line 259) | def is_runnable(self):
    method save_inference_model (line 267) | def save_inference_model(self,
    method export_onnx_model (line 306) | def export_onnx_model(self, dirname: str, **kwargs):
    method sub_modules (line 332) | def sub_modules(self, recursive: bool = True):

FILE: paddlehub/compat/module/module_v1_utils.py
  function convert_module_desc (line 21) | def convert_module_desc(desc_file):
  function convert_signatures (line 31) | def convert_signatures(signmaps):
  function convert_attr (line 44) | def convert_attr(module_attr):

FILE: paddlehub/compat/module/nlp_module.py
  class DataFormatError (line 39) | class DataFormatError(Exception):
    method __init__ (line 41) | def __init__(self, *args):
  class NLPBaseModule (line 45) | class NLPBaseModule(RunModule):
    method get_vocab_path (line 47) | def get_vocab_path(self):
  class NLPPredictionModule (line 56) | class NLPPredictionModule(NLPBaseModule):
    method _set_config (line 58) | def _set_config(self):
    method texts2tensor (line 77) | def texts2tensor(self, texts: List[dict]) -> paddle.Tensor:
    method to_unicode (line 97) | def to_unicode(self, texts: str) -> Text:
    method run_cmd (line 116) | def run_cmd(self, argvs: List[Any]):
    method add_module_config_arg (line 142) | def add_module_config_arg(self):
    method add_module_input_arg (line 151) | def add_module_input_arg(self):
    method check_input_data (line 156) | def check_input_data(self, args):
  class TransformerModule (line 169) | class TransformerModule(NLPBaseModule):
    method __init__ (line 174) | def __init__(self,
    method init_pretraining_params (line 191) | def init_pretraining_params(self, exe: paddle.static.Executor, pretrai...
    method param_prefix (line 205) | def param_prefix(self) -> str:
    method context (line 209) | def context(
    method get_embedding (line 350) | def get_embedding(self, texts: List[str], max_seq_len: int = 512, use_...
    method get_spm_path (line 399) | def get_spm_path(self) -> str:
    method get_word_dict_path (line 404) | def get_word_dict_path(self) -> str:
    method get_params_layer (line 409) | def get_params_layer(self) -> dict:

FILE: paddlehub/compat/module/processor.py
  class BaseProcessor (line 19) | class BaseProcessor(object):
    method __init__ (line 23) | def __init__(self, module):
    method configs (line 26) | def configs(self) -> List:
    method preprocess (line 29) | def preprocess(self, signature: str, data: dict):
    method postprocess (line 34) | def postprocess(self, signature: str, data_out: dict, data_info: dict,...
    method data_format (line 39) | def data_format(self, signature: str):

FILE: paddlehub/compat/paddle_utils.py
  function convert_dtype_to_string (line 39) | def convert_dtype_to_string(dtype: str) -> core.VarDesc.VarType:
  function get_variable_info (line 45) | def get_variable_info(var: paddle.static.Variable) -> dict:
  function remove_feed_fetch_op (line 77) | def remove_feed_fetch_op(program: paddle.static.Program):
  function rename_var (line 102) | def rename_var(block: paddle.device.framework.Block, old_name: str, new_...
  function add_vars_prefix (line 117) | def add_vars_prefix(program: paddle.static.Program,
  function remove_vars_prefix (line 130) | def remove_vars_prefix(program: paddle.static.Program,
  function clone_program (line 144) | def clone_program(origin_program: paddle.static.Program, for_test: bool ...
  function _copy_vars_and_ops_in_blocks (line 157) | def _copy_vars_and_ops_in_blocks(from_block: paddle.device.framework.Blo...
  function set_op_attr (line 193) | def set_op_attr(program: paddle.static.Program, is_test: bool = False):
  function static_mode_guard (line 203) | def static_mode_guard():
  function run_in_static_mode (line 216) | def run_in_static_mode(func):

FILE: paddlehub/compat/task/base_task.py
  class BaseTask (line 42) | class BaseTask(object):
    method __init__ (line 52) | def __init__(self,
    method phase_guard (line 130) | def phase_guard(self, phase: str):
    method enter_phase (line 135) | def enter_phase(self, phase: str):
    method exit_phase (line 144) | def exit_phase(self):
    method init_if_necessary (line 147) | def init_if_necessary(self):
    method init_if_load_best_model (line 154) | def init_if_load_best_model(self):
    method _build_env (line 167) | def _build_env(self):
    method places (line 232) | def places(self) -> List[Union[paddle.CPUPlace, paddle.CUDAPlace]]:
    method return_numpy (line 243) | def return_numpy(self) -> bool:
    method is_train_phase (line 247) | def is_train_phase(self) -> bool:
    method is_test_phase (line 251) | def is_test_phase(self) -> bool:
    method is_predict_phase (line 255) | def is_predict_phase(self) -> bool:
    method phase (line 259) | def phase(self) -> str:
    method env (line 263) | def env(self) -> RunEnv:
    method current_step (line 272) | def current_step(self) -> int:
    method current_epoch (line 278) | def current_epoch(self) -> int:
    method main_program (line 284) | def main_program(self) -> paddle.static.Program:
    method startup_program (line 290) | def startup_program(self) -> paddle.static.Program:
    method main_program_compiled (line 296) | def main_program_compiled(self) -> paddle.static.CompiledProgram:
    method main_program_to_be_run (line 302) | def main_program_to_be_run(self) -> Union[paddle.static.Program, paddl...
    method generator (line 310) | def generator(self) -> Generator:
    method loss (line 342) | def loss(self) -> paddle.static.Variable:
    method labels (line 351) | def labels(self) -> List[paddle.static.Variable]:
    method outputs (line 360) | def outputs(self) -> List[paddle.static.Variable]:
    method metrics (line 366) | def metrics(self) -> List[str]:
    method unique_name_generator (line 375) | def unique_name_generator(self):
    method feed_list (line 379) | def feed_list(self) -> List[str]:
    method feed_var_list (line 392) | def feed_var_list(self) -> List[paddle.static.Variable]:
    method fetch_list (line 400) | def fetch_list(self) -> List[str]:
    method fetch_var_list (line 406) | def fetch_var_list(self) -> List[paddle.static.Variable]:
    method vdl_writer (line 411) | def vdl_writer(self) -> LogWriter:
    method create_event_function (line 422) | def create_event_function(self, hook_type: str) -> Callable:
    method hooks (line 442) | def hooks(self) -> List[dict]:
    method hooks_info (line 445) | def hooks_info(self, show_default: bool = False) -> str:
    method add_hook (line 455) | def add_hook(self, hook_type: str, name: str = None, func: Callable = ...
    method delete_hook (line 468) | def delete_hook(self, hook_type: str, name: str):
    method modify_hook (line 478) | def modify_hook(self, hook_type: str, name: str, func: Callable):
    method _default_build_env_start_event (line 489) | def _default_build_env_start_event(self):
    method _default_build_env_end_event (line 492) | def _default_build_env_end_event(self):
    method _default_finetune_start_event (line 496) | def _default_finetune_start_event(self):
    method _default_finetune_end_event (line 499) | def _default_finetune_end_event(self, run_states: List[RunState]):
    method _default_predict_start_event (line 502) | def _default_predict_start_event(self):
    method _default_predict_end_event (line 505) | def _default_predict_end_event(self, run_states: List[RunState]):
    method _default_eval_start_event (line 508) | def _default_eval_start_event(self):
    method _default_eval_end_event (line 511) | def _default_eval_end_event(self, run_states: List[RunState]):
    method _default_log_interval_event (line 548) | def _default_log_interval_event(self, run_states: List[RunState]):
    method _default_save_ckpt_interval_event (line 567) | def _default_save_ckpt_interval_event(self):
    method _default_eval_interval_event (line 570) | def _default_eval_interval_event(self):
    method _default_run_step_event (line 573) | def _default_run_step_event(self, run_state: List[RunState]):
    method _build_net (line 576) | def _build_net(self):
    method _add_loss (line 579) | def _add_loss(self):
    method _add_label (line 582) | def _add_label(self):
    method _add_metrics (line 585) | def _add_metrics(self):
    method _calculate_metrics (line 590) | def _calculate_metrics(self, run_states: List[RunState]):
    method load_checkpoint (line 596) | def load_checkpoint(self):
    method load_parameters (line 606) | def load_parameters(self, dirname):
    method save_inference_model (line 614) | def save_inference_model(self, dirname: str, model_filename: str = Non...
    method finetune_and_eval (line 624) | def finetune_and_eval(self) -> List[RunState]:
    method finetune (line 627) | def finetune(self, do_eval: bool = False) -> List[RunState]:
    method eval (line 668) | def eval(self, phase: str = 'dev', load_best_model: bool = False) -> L...
    method _create_predictor (line 690) | def _create_predictor(self) -> core.PaddlePredictor:
    method _run_with_predictor (line 709) | def _run_with_predictor(self) -> List[RunState]:
    method predict (line 753) | def predict(
    method _postprocessing (line 796) | def _postprocessing(self, run_states: List[RunState]) -> List:
    method _run (line 810) | def _run(self, do_eval: bool = False) -> List[RunState]:
    method __repr__ (line 875) | def __repr__(self) -> str:

FILE: paddlehub/compat/task/batch.py
  function pad_batch_data (line 22) | def pad_batch_data(insts: List,

FILE: paddlehub/compat/task/checkpoint.py
  function load_checkpoint (line 27) | def load_checkpoint(checkpoint_dir: str, exe: paddle.static.Executor,

FILE: paddlehub/compat/task/config.py
  class RunConfig (line 20) | class RunConfig(object):
    method __init__ (line 23) | def __init__(self,
    method __repr__ (line 49) | def __repr__(self):

FILE: paddlehub/compat/task/hook.py
  class TaskHooks (line 21) | class TaskHooks(object):
    method __init__ (line 24) | def __init__(self):
    method add (line 54) | def add(self, hook_type: str, name: str = None, func: Callable = None):
    method delete (line 81) | def delete(self, hook_type: str, name: str):
    method modify (line 94) | def modify(self, hook_type: str, name: str, func: Callable):
    method exist (line 110) | def exist(self, hook_type: str, name: str) -> bool:
    method info (line 125) | def info(self, show_default: bool = False) -> str:
    method __getitem__ (line 154) | def __getitem__(self, hook_type: str) -> OrderedDict:
    method __repr__ (line 157) | def __repr__(self) -> str:

FILE: paddlehub/compat/task/metrics.py
  function _get_ngrams (line 21) | def _get_ngrams(segment: str, max_order: int):
  function compute_bleu (line 42) | def compute_bleu(reference_corpus: List, translation_corpus: List, max_o...

FILE: paddlehub/compat/task/reader.py
  class InputExample (line 26) | class InputExample(object):
    method __init__ (line 33) | def __init__(self, guid: int, text_a: str, text_b: str = None, label: ...
    method __str__ (line 49) | def __str__(self):
  class BaseReader (line 56) | class BaseReader(object):
    method __init__ (line 57) | def __init__(self, dataset: Generic, random_seed: int = None):
    method get_train_examples (line 72) | def get_train_examples(self) -> List:
    method get_dev_examples (line 75) | def get_dev_examples(self) -> List:
    method get_test_examples (line 78) | def get_test_examples(self) -> List:
    method data_generator (line 81) | def data_generator(self) -> Generic:
  class BaseNLPReader (line 85) | class BaseNLPReader(BaseReader):
    method __init__ (line 86) | def __init__(self,
    method _truncate_seq_pair (line 111) | def _truncate_seq_pair(self, tokens_a: List, tokens_b: List, max_lengt...
    method _convert_example_to_record (line 127) | def _convert_example_to_record(self,
    method _pad_batch_records (line 206) | def _pad_batch_records(self, batch_records: List, phase: str):
    method _prepare_batch_data (line 209) | def _prepare_batch_data(self, examples: List, batch_size: int, phase: ...
    method data_generator (line 230) | def data_generator(self,
  class ClassifyReader (line 287) | class ClassifyReader(BaseNLPReader):
    method _pad_batch_records (line 288) | def _pad_batch_records(self, batch_records: List, phase: str = None) -...

FILE: paddlehub/compat/task/task_utils.py
  class RunState (line 22) | class RunState(object):
    method __init__ (line 29) | def __init__(self, length: int):
    method __add__ (line 37) | def __add__(self, other):
    method update (line 44) | def update(self):
  class RunEnv (line 50) | class RunEnv(object):
    method __init__ (line 53) | def __init__(self):
    method __setattr__ (line 67) | def __setattr__(self, key: str, value: Any):
    method __getattr__ (line 70) | def __getattr__(self, key: str) -> Any:

FILE: paddlehub/compat/task/text_generation_task.py
  class AttentionDecoderCell (line 32) | class AttentionDecoderCell(RNNCellBase):
    method __init__ (line 34) | def __init__(self, num_layers, input_size, hidden_size, dropout_prob=0...
    method attention (line 45) | def attention(self, query, enc_output, mask=None):
    method forward (line 64) | def forward(self, step_input, states, enc_output, enc_padding_mask=None):
  class TextGenerationTask (line 84) | class TextGenerationTask(BaseTask):
    method __init__ (line 106) | def __init__(
    method _add_label (line 145) | def _add_label(self):
    method _build_net (line 149) | def _build_net(self):
    method _postprocessing (line 215) | def _postprocessing(self, run_states):
    method _add_metrics (line 229) | def _add_metrics(self):
    method _add_loss (line 233) | def _add_loss(self):
    method fetch_list (line 245) | def fetch_list(self):
    method _calculate_metrics (line 252) | def _calculate_metrics(self, run_states):

FILE: paddlehub/compat/task/tokenization.py
  function convert_to_unicode (line 24) | def convert_to_unicode(text: Union[str, bytes]) -> str:
  function load_vocab (line 34) | def load_vocab(vocab_file: str) -> List:
  function convert_by_vocab (line 51) | def convert_by_vocab(vocab: collections.OrderedDict, items: List[str]) -...
  function convert_tokens_to_ids (line 60) | def convert_tokens_to_ids(vocab: collections.OrderedDict, tokens: List[s...
  function convert_ids_to_tokens (line 64) | def convert_ids_to_tokens(inv_vocab, ids):
  function whitespace_tokenize (line 68) | def whitespace_tokenize(text: str) -> List:
  class FullTokenizer (line 78) | class FullTokenizer(object):
    method __init__ (line 81) | def __init__(self, vocab_file: str, do_lower_case: bool = True, use_se...
    method tokenize (line 89) | def tokenize(self, text: str) -> List:
    method convert_tokens_to_ids (line 97) | def convert_tokens_to_ids(self, tokens: List) -> List:
    method convert_ids_to_tokens (line 100) | def convert_ids_to_tokens(self, ids: List) -> List:
  class WSSPTokenizer (line 104) | class WSSPTokenizer(object):
    method __init__ (line 105) | def __init__(self, vocab_file: str, sp_model_dir: str, word_dict: str,...
    method cut (line 117) | def cut(self, chars: List) -> List:
    method tokenize (line 134) | def tokenize(self, text: Union[str, bytes], unk_token: str = '[UNK]') ...
    method convert_tokens_to_ids (line 152) | def convert_tokens_to_ids(self, tokens: List) -> List:
    method convert_ids_to_tokens (line 155) | def convert_ids_to_tokens(self, ids: List) -> List:
  class BasicTokenizer (line 159) | class BasicTokenizer(object):
    method __init__ (line 162) | def __init__(self, do_lower_case: bool = True):
    method tokenize (line 169) | def tokenize(self, text: Union[str, bytes]) -> List:
    method _run_strip_accents (line 193) | def _run_strip_accents(self, text: str) -> str:
    method _run_split_on_punc (line 204) | def _run_split_on_punc(self, text: str) -> List:
    method _tokenize_chinese_chars (line 224) | def _tokenize_chinese_chars(self, text: str) -> str:
    method _is_chinese_char (line 237) | def _is_chinese_char(self, cp: int) -> bool:
    method _clean_text (line 258) | def _clean_text(self, text: str) -> str:
  class WordpieceTokenizer (line 272) | class WordpieceTokenizer(object):
    method __init__ (line 275) | def __init__(self,
    method tokenize (line 285) | def tokenize(self, text: Union[str, bytes]) -> List:
  function _is_whitespace (line 337) | def _is_whitespace(char: str) -> bool:
  function _is_control (line 349) | def _is_control(char: str) -> bool:
  function _is_punctuation (line 361) | def _is_punctuation(char: str) -> bool:

FILE: paddlehub/compat/task/transformer_emb_task.py
  class TransformerEmbeddingTask (line 26) | class TransformerEmbeddingTask(BaseTask):
    method __init__ (line 27) | def __init__(self,
    method _build_net (line 39) | def _build_net(self) -> List[paddle.static.Variable]:
    method _postprocessing (line 44) | def _postprocessing(self, run_states: List[RunState]) -> List[List[np....
    method feed_list (line 55) | def feed_list(self) -> List[str]:
    method fetch_list (line 60) | def fetch_list(self) -> List[str]:

FILE: paddlehub/compat/type.py
  class DataType (line 17) | class DataType(object):

FILE: paddlehub/config.py
  function md5 (line 27) | def md5(text: str):
  class HubConfig (line 33) | class HubConfig:
    method __init__ (line 40) | def __init__(self):
    method _initialize (line 55) | def _initialize(self):
    method reset (line 63) | def reset(self):
    method log_level (line 69) | def log_level(self):
    method log_level (line 77) | def log_level(self, level: str):
    method log_enable (line 86) | def log_enable(self):
    method log_enable (line 91) | def log_enable(self, enable: bool):
    method server (line 96) | def server(self):
    method server (line 101) | def server(self, url: str):
    method flush (line 105) | def flush(self):
    method __str__ (line 112) | def __str__(self):
  class CacheConfig (line 117) | class CacheConfig(object):
    method __init__ (line 118) | def __init__(self):
    method _initialize (line 132) | def _initialize(self):
    method hub_name (line 139) | def hub_name(self):
    method hub_name (line 143) | def hub_name(self, url: str):
    method flush (line 147) | def flush(self):
    method __str__ (line 154) | def __str__(self):
  function _load_old_config (line 159) | def _load_old_config(config: HubConfig):

FILE: paddlehub/datasets/base_audio_dataset.py
  class InputExample (line 26) | class InputExample(object):
    method __init__ (line 31) | def __init__(self, guid: int, source: Union[list, str], label: Optiona...
  class BaseAudioDataset (line 37) | class BaseAudioDataset(object):
    method __init__ (line 42) | def __init__(self, base_path: str, data_file: str, mode: Optional[str]...
    method _read_file (line 46) | def _read_file(self, input_file: str):
  class AudioClassificationDataset (line 50) | class AudioClassificationDataset(BaseAudioDataset, paddle.io.Dataset):
    method __init__ (line 56) | def __init__(self,
    method _read_file (line 72) | def _read_file(self, input_file: str) -> List[InputExample]:
    method _convert_examples_to_records (line 89) | def _convert_examples_to_records(self, examples: List[InputExample]) -...
    method __getitem__ (line 120) | def __getitem__(self, idx):
    method __len__ (line 127) | def __len__(self):

FILE: paddlehub/datasets/base_nlp_dataset.py
  class InputExample (line 32) | class InputExample(object):
    method __init__ (line 37) | def __init__(self, guid: int, text_a: str, text_b: Optional[str] = Non...
    method __str__ (line 62) | def __str__(self):
  class BaseNLPDataset (line 69) | class BaseNLPDataset(object):
    method __init__ (line 75) | def __init__(self,
    method _load_label_data (line 116) | def _load_label_data(self):
    method _download_and_uncompress_dataset (line 126) | def _download_and_uncompress_dataset(self, destination: str, url: str):
    method _read_file (line 140) | def _read_file(self, input_file: str, is_file_with_header: bool = False):
    method get_labels (line 150) | def get_labels(self):
  class TextClassificationDataset (line 157) | class TextClassificationDataset(BaseNLPDataset, paddle.io.Dataset):
    method __init__ (line 162) | def __init__(self,
    method _read_file (line 202) | def _read_file(self, input_file, is_file_with_header: bool = False) ->...
    method _convert_examples_to_records (line 226) | def _convert_examples_to_records(self, examples: List[InputExample]) -...
    method __getitem__ (line 272) | def __getitem__(self, idx):
    method __len__ (line 296) | def __len__(self):
  class SeqLabelingDataset (line 300) | class SeqLabelingDataset(BaseNLPDataset, paddle.io.Dataset):
    method __init__ (line 328) | def __init__(self,
    method _read_file (line 356) | def _read_file(self, input_file, is_file_with_header: bool = False) ->...
    method _convert_examples_to_records (line 372) | def _convert_examples_to_records(self, examples: List[InputExample]) -...
    method __getitem__ (line 445) | def __getitem__(self, idx):
    method __len__ (line 470) | def __len__(self):
  class TextMatchingDataset (line 474) | class TextMatchingDataset(BaseNLPDataset, paddle.io.Dataset):
    method __init__ (line 479) | def __init__(self,
    method _read_file (line 519) | def _read_file(self, input_file, is_file_with_header: bool = False) ->...
    method _convert_examples_to_records (line 543) | def _convert_examples_to_records(self, examples: List[InputExample]) -...
    method __getitem__ (line 573) | def __getitem__(self, idx):
    method __len__ (line 591) | def __len__(self):

FILE: paddlehub/datasets/base_seg_dataset.py
  class SegDataset (line 23) | class SegDataset(paddle.io.Dataset):
    method __init__ (line 45) | def __init__(self,
    method __getitem__ (line 111) | def __getitem__(self, idx: int) -> Tuple[np.ndarray]:
    method __len__ (line 126) | def __len__(self) -> int:

FILE: paddlehub/datasets/canvas.py
  class Canvas (line 28) | class Canvas(paddle.io.Dataset):
    method __init__ (line 41) | def __init__(self, transform: Callable, mode: str = 'train'):
    method __getitem__ (line 53) | def __getitem__(self, idx: int) -> np.ndarray:
    method __len__ (line 58) | def __len__(self):

FILE: paddlehub/datasets/chnsenticorp.py
  class ChnSentiCorp (line 25) | class ChnSentiCorp(TextClassificationDataset):
    method __init__ (line 33) | def __init__(self, tokenizer: Union[BertTokenizer, CustomTokenizer], m...

FILE: paddlehub/datasets/esc50.py
  class ESC50 (line 23) | class ESC50(AudioClassificationDataset):
    method __init__ (line 85) | def __init__(self, mode: str = 'train', feat_type: str = 'mel'):

FILE: paddlehub/datasets/flowers.py
  class Flowers (line 26) | class Flowers(paddle.io.Dataset):
    method __init__ (line 27) | def __init__(self, transforms: Callable, mode: str = 'train'):
    method __getitem__ (line 43) | def __getitem__(self, idx) -> Tuple[np.ndarray, int]:
    method __len__ (line 49) | def __len__(self):

FILE: paddlehub/datasets/lcqmc.py
  class LCQMC (line 26) | class LCQMC(TextMatchingDataset):
    method __init__ (line 29) | def __init__(

FILE: paddlehub/datasets/minicoco.py
  class MiniCOCO (line 28) | class MiniCOCO(paddle.io.Dataset):
    method __init__ (line 41) | def __init__(self, transform: Callable, mode: str = 'train'):
    method __getitem__ (line 54) | def __getitem__(self, idx: int) -> np.ndarray:
    method __len__ (line 65) | def __len__(self):

FILE: paddlehub/datasets/msra_ner.py
  class MSRA_NER (line 27) | class MSRA_NER(SeqLabelingDataset):
    method __init__ (line 36) | def __init__(

FILE: paddlehub/datasets/opticdiscseg.py
  class OpticDiscSeg (line 29) | class OpticDiscSeg(SegDataset):
    method __init__ (line 40) | def __init__(self, transforms: Callable = None, mode: str = 'train'):

FILE: paddlehub/datasets/pascalvoc.py
  class DetectCatagory (line 26) | class DetectCatagory:
    method __init__ (line 39) | def __init__(self, attrbox: Callable, data_dir: str):
    method __call__ (line 43) | def __call__(self):
  class ParseImages (line 55) | class ParseImages:
    method __init__ (line 67) | def __init__(self, attrbox: Callable, data_dir: str, category_to_id_ma...
    method __call__ (line 73) | def __call__(self):
  class GTAnotations (line 88) | class GTAnotations:
    method __init__ (line 100) | def __init__(self, attrbox: Callable, category_to_id_map: dict):
    method box_to_center_relative (line 104) | def box_to_center_relative(self, box: list, img_height: int, img_width...
    method __call__ (line 125) | def __call__(self, img: dict):
  class DetectionData (line 149) | class DetectionData(paddle.io.Dataset):
    method __init__ (line 161) | def __init__(self, transform: Callable, size: int = 416, mode: str = '...
    method __getitem__ (line 187) | def __getitem__(self, idx: int):
    method __len__ (line 193) | def __len__(self):

FILE: paddlehub/env.py
  function _get_user_home (line 36) | def _get_user_home():
  function _get_hub_home (line 40) | def _get_hub_home():
  function _get_sub_home (line 53) | def _get_sub_home(directory):

FILE: paddlehub/finetune/trainer.py
  class Trainer (line 31) | class Trainer(object):
    method __init__ (line 55) | def __init__(self,
    method _load_checkpoint (line 91) | def _load_checkpoint(self):
    method load_model (line 123) | def load_model(self, load_dir: str):
    method _save_checkpoint (line 135) | def _save_checkpoint(self):
    method save_model (line 141) | def save_model(self, save_dir: str):
    method _save_metrics (line 148) | def _save_metrics(self):
    method _load_metrics (line 152) | def _load_metrics(self):
    method train (line 160) | def train(self,
    method evaluate (line 283) | def evaluate(self,
    method training_step (line 345) | def training_step(self, batch: List[paddle.Tensor], batch_idx: int):
    method validation_step (line 374) | def validation_step(self, batch: Any, batch_idx: int):
    method optimizer_step (line 388) | def optimizer_step(self, epoch_idx: int, batch_idx: int, optimizer: pa...
    method learning_rate_step (line 402) | def learning_rate_step(self, epoch_idx: int, batch_idx: int, learning_...
    method optimizer_zero_grad (line 406) | def optimizer_zero_grad(self, epoch_idx: int, batch_idx: int, optimize...
    method _compare_metrics (line 418) | def _compare_metrics(self, old_metric: dict, new_metric: dict):

FILE: paddlehub/module/audio_module.py
  class AudioClassifierModule (line 25) | class AudioClassifierModule(RunModule):
    method _batchify (line 33) | def _batchify(self, data: List[List[float]], sample_rate: int, feat_ty...
    method training_step (line 53) | def training_step(self, batch: List[paddle.Tensor], batch_idx: int):
    method validation_step (line 62) | def validation_step(self, batch: List[paddle.Tensor], batch_idx: int):
    method predict (line 70) | def predict(self,

FILE: paddlehub/module/cv_module.py
  class ImageServing (line 37) | class ImageServing(object):
    method serving_method (line 39) | def serving_method(self, images: List[str], **kwargs) -> List[dict]:
  class ImageClassifierModule (line 46) | class ImageClassifierModule(RunModule, ImageServing):
    method training_step (line 47) | def training_step(self, batch: int, batch_idx: int) -> dict:
    method validation_step (line 60) | def validation_step(self, batch: int, batch_idx: int) -> dict:
    method predict (line 82) | def predict(self, images: List[np.ndarray], batch_size: int = 1, top_k...
    method serving_method (line 125) | def serving_method(self, images: list, top_k: int, **kwargs):
    method run_cmd (line 140) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 159) | def add_module_config_arg(self):
    method add_module_input_arg (line 166) | def add_module_input_arg(self):
  class ImageColorizeModule (line 173) | class ImageColorizeModule(RunModule, ImageServing):
    method training_step (line 174) | def training_step(self, batch: int, batch_idx: int) -> dict:
    method validation_step (line 187) | def validation_step(self, batch: int, batch_idx: int) -> dict:
    method predict (line 213) | def predict(self, images: list, visualization: bool = True, batch_size...
    method serving_method (line 278) | def serving_method(self, images: list, **kwargs):
    method run_cmd (line 294) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 313) | def add_module_config_arg(self):
    method add_module_input_arg (line 323) | def add_module_input_arg(self):
  class Yolov3Module (line 330) | class Yolov3Module(RunModule, ImageServing):
    method training_step (line 331) | def training_step(self, batch: int, batch_idx: int) -> dict:
    method validation_step (line 345) | def validation_step(self, batch: int, batch_idx: int) -> dict:
    method predict (line 382) | def predict(self, imgpath: str, filelist: str, visualization: bool = T...
  class StyleTransferModule (line 455) | class StyleTransferModule(RunModule, ImageServing):
    method training_step (line 456) | def training_step(self, batch: int, batch_idx: int) -> dict:
    method validation_step (line 469) | def validation_step(self, batch: int, batch_idx: int) -> dict:
    method predict (line 507) | def predict(self,
    method serving_method (line 561) | def serving_method(self, images: list, **kwargs):
    method run_cmd (line 573) | def run_cmd(self, argvs: list):
    method add_module_config_arg (line 596) | def add_module_config_arg(self):
    method add_module_input_arg (line 607) | def add_module_input_arg(self):
  class ImageSegmentationModule (line 615) | class ImageSegmentationModule(ImageServing, RunModule):
    method training_step (line 616) | def training_step(self, batch: List[paddle.Tensor], batch_idx: int) ->...
    method predict (line 644) | def predict(self,
    method serving_method (line 706) | def serving_method(self, images: List[str], **kwargs):

FILE: paddlehub/module/manager.py
  class HubModuleNotFoundError (line 31) | class HubModuleNotFoundError(Exception):
    method __init__ (line 32) | def __init__(self, name: str, info: dict = None, version: str = None, ...
    method __str__ (line 38) | def __str__(self):
  class EnvironmentMismatchError (line 67) | class EnvironmentMismatchError(Exception):
    method __init__ (line 68) | def __init__(self, name: str, info: dict, version: str = None):
    method __str__ (line 73) | def __str__(self):
  class LocalModuleManager (line 113) | class LocalModuleManager(object):
    method __new__ (line 124) | def __new__(cls, home: str = MODULE_HOME):
    method __init__ (line 131) | def __init__(self, home: str = None):
    method _get_normalized_path (line 141) | def _get_normalized_path(self, name: str) -> str:
    method _get_normalized_name (line 144) | def _get_normalized_name(self, name: str) -> str:
    method install (line 149) | def install(self,
    method uninstall (line 200) | def uninstall(self, name: str) -> bool:
    method search (line 214) | def search(self, name: str, source: str = None, branch: str = None) ->...
    method list (line 239) | def list(self) -> List[HubModule]:
    method _install_from_url (line 251) | def _install_from_url(self, url: str) -> HubModule:
    method _install_from_name (line 260) | def _install_from_name(self, name: str, version: str = None, ignore_en...
    method _install_from_source (line 302) | def _install_from_source(self, name: str, version: str, source: str, u...
    method _install_from_directory (line 340) | def _install_from_directory(self, directory: str) -> HubModule:
    method _install_from_archive (line 370) | def _install_from_archive(self, archive: str) -> HubModule:
    method _install_module_requirements (line 382) | def _install_module_requirements(self, directory: str):

FILE: paddlehub/module/module.py
  class InvalidHubModule (line 39) | class InvalidHubModule(Exception):
    method __init__ (line 40) | def __init__(self, directory: str):
    method __str__ (line 43) | def __str__(self):
  function runnable (line 51) | def runnable(func: Callable) -> Callable:
  function serving (line 62) | def serving(func: Callable) -> Callable:
  class RunModule (line 73) | class RunModule(object):
    method __init__ (line 76) | def __init__(self, *args, **kwargs):
    method _get_func_name (line 79) | def _get_func_name(self, current_cls: Generic, module_func_dict: dict)...
    method __getattribute__ (line 94) | def __getattribute__(self, attr):
    method get_py_requirements (line 110) | def get_py_requirements(cls) -> List[str]:
    method _run_func_name (line 121) | def _run_func_name(self):
    method _run_func (line 125) | def _run_func(self):
    method is_runnable (line 129) | def is_runnable(self) -> bool:
    method serving_func_name (line 137) | def serving_func_name(self):
    method _pretrained_model_path (line 141) | def _pretrained_model_path(self):
    method sub_modules (line 155) | def sub_modules(self, recursive: bool = True):
    method save_inference_model (line 177) | def save_inference_model(self,
    method export_onnx_model (line 275) | def export_onnx_model(self,
  class Module (line 356) | class Module(object):
    method __new__ (line 379) | def __new__(cls,
    method load (line 411) | def load(cls, directory: str) -> Generic:
    method load_module_info (line 452) | def load_module_info(cls, directory: str) -> EasyDict:
    method init_with_name (line 479) | def init_with_name(cls,
    method init_with_directory (line 519) | def init_with_directory(cls, directory: str, **kwargs) -> Union[RunMod...
  function moduleinfo (line 540) | def moduleinfo(name: str,

FILE: paddlehub/module/nlp_module.py
  function fn_args_to_dict (line 45) | def fn_args_to_dict(func, *args, **kwargs):
  class InitTrackerMeta (line 63) | class InitTrackerMeta(type(nn.Layer)):
    method __init__ (line 75) | def __init__(cls, name, bases, attrs):
    method init_and_track_conf (line 85) | def init_and_track_conf(init_func, help_func=None):
  function register_base_model (line 113) | def register_base_model(cls):
  class PretrainedModel (line 128) | class PretrainedModel(nn.Layer):
    method _wrap_init (line 157) | def _wrap_init(self, original_init, *args, **kwargs):
    method base_model (line 166) | def base_model(self):
    method model_name_list (line 170) | def model_name_list(self):
    method get_input_embeddings (line 173) | def get_input_embeddings(self):
    method get_output_embeddings (line 180) | def get_output_embeddings(self):
    method from_pretrained (line 184) | def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs):
    method save_pretrained (line 325) | def save_pretrained(self, save_directory):
  class TextServing (line 352) | class TextServing(object):
    method predict_method (line 358) | def predict_method(self, data: List[List[str]], max_seq_len: int = 128...
  class TransformerModule (line 396) | class TransformerModule(RunModule, TextServing):
    method input_spec (line 407) | def input_spec(self):
    method _convert_text_to_input (line 413) | def _convert_text_to_input(self, tokenizer, texts: List[str], max_seq_...
    method _batchify (line 451) | def _batchify(self, data: List[List[str]], max_seq_len: int, batch_siz...
    method training_step (line 491) | def training_step(self, batch: List[paddle.Tensor], batch_idx: int):
    method validation_step (line 512) | def validation_step(self, batch: List[paddle.Tensor], batch_idx: int):
    method get_embedding (line 532) | def get_embedding(self, data: List[List[str]], use_gpu=False):
    method predict (line 546) | def predict(self,
  class EmbeddingServing (line 629) | class EmbeddingServing(object):
    method calc_similarity (line 635) | def calc_similarity(self, data: List[List[str]]):
  class EmbeddingModule (line 657) | class EmbeddingModule(RunModule, EmbeddingServing):
    method _download_vocab (line 663) | def _download_vocab(self):
    method get_vocab_path (line 670) | def get_vocab_path(self):
    method get_tokenizer (line 679) | def get_tokenizer(self, *args, **kwargs):

FILE: paddlehub/server/__init__.py
  function server_check (line 22) | def server_check() -> bool:

FILE: paddlehub/server/git_source.py
  class GitSource (line 29) | class GitSource(object):
    method __init__ (line 38) | def __init__(self, url: str, path: str = None):
    method checkout (line 60) | def checkout(self, branch: str):
    method update (line 69) | def update(self):
    method load_hub_modules (line 79) | def load_hub_modules(self):
    method search_module (line 110) | def search_module(self, name: str, version: str = None) -> List[dict]:
    method search_resource (line 120) | def search_resource(self, type: str, name: str, version: str = None) -...
    method get_module_compat_info (line 142) | def get_module_compat_info(self, name: str) -> dict:
    method check (line 147) | def check(cls, url: str) -> bool:

FILE: paddlehub/server/server.py
  class HubServer (line 34) | class HubServer(object):
    method __init__ (line 37) | def __init__(self):
    method _generate_source (line 41) | def _generate_source(self, url: str, source_type: str = 'git'):
    method _get_source_key (line 50) | def _get_source_key(self, url: str):
    method add_source (line 53) | def add_source(self, url: str, source_type: str = 'git', key: str = ''):
    method remove_source (line 59) | def remove_source(self, url: str = None, key: str = None):
    method get_source (line 63) | def get_source(self, url: str):
    method get_source_by_key (line 70) | def get_source_by_key(self, key: str):
    method search_module (line 74) | def search_module(self,
    method search_resource (line 90) | def search_resource(self,
    method get_module_compat_info (line 118) | def get_module_compat_info(self, name: str, source: str = None) -> dict:
  function uri_path (line 128) | def uri_path(server_url, api):
  function hub_request (line 140) | def hub_request(api, params, extra=None, timeout=8):
  class CacheUpdater (line 149) | class CacheUpdater(threading.Thread):
    method __init__ (line 150) | def __init__(self, command="update_cache", module=None, version=None, ...
    method update_resource_list_file (line 157) | def update_resource_list_file(self, command="update_cache", module=Non...
    method run (line 182) | def run(self):

FILE: paddlehub/server/server_source.py
  class ServerConnectionError (line 26) | class ServerConnectionError(Exception):
    method __init__ (line 28) | def __init__(self, url: str):
    method __str__ (line 31) | def __str__(self):
  class ServerSource (line 36) | class ServerSource(object):
    method __init__ (line 45) | def __init__(self, url: str, timeout: int = 10):
    method search_module (line 49) | def search_module(self, name: str, version: str = None) -> List[dict]:
    method search_resource (line 59) | def search_resource(self, type: str, name: str, version: str = None) -...
    method get_module_compat_info (line 110) | def get_module_compat_info(self, name: str) -> dict:
    method request (line 126) | def request(self, path: str, params: dict) -> dict:
    method is_connected (line 135) | def is_connected(self):
    method check (line 139) | def check(cls, url: str) -> bool:

FILE: paddlehub/serving/app_compat.py
  function package_result (line 40) | def package_result(status: str, msg: str, data: dict):
  function create_gradio_app (line 69) | def create_gradio_app(module_info: dict):
  function predict_v2 (line 117) | def predict_v2(module_info: dict, input: dict):
  function create_app (line 154) | def create_app(init_flag: bool = False, configs: dict = None):
  function config_with_file (line 265) | def config_with_file(configs: dict):
  function run (line 288) | def run(configs: dict = None, port: int = 8866):

FILE: paddlehub/serving/client.py
  class InferenceClient (line 19) | class InferenceClient(object):
    method __init__ (line 20) | def __init__(self, frontend_addr):
    method send_req (line 26) | def send_req(self, message):
  class InferenceClientProxy (line 33) | class InferenceClientProxy(object):
    method get_client (line 37) | def get_client(pid, frontend_addr):

FILE: paddlehub/serving/device.py
  class InferenceDevice (line 28) | class InferenceDevice(object):
    method __init__ (line 34) | def __init__(self):
    method listen (line 40) | def listen(self, frontend_addr: str, backend_addr: str):
  function start_workers (line 62) | def start_workers(modules_info: dict, gpus: list, backend_addr: str):
  class InferenceServer (line 85) | class InferenceServer(object):
    method __init__ (line 94) | def __init__(self, modules_info: dict, gpus: list):
    method listen (line 98) | def listen(self, port: int):

FILE: paddlehub/serving/http_server.py
  class StandaloneApplication (line 31) | class StandaloneApplication(object):
    method __init__ (line 32) | def __init__(self):
    method load_config (line 35) | def load_config(self):
    method load (line 38) | def load(self):
    method __init__ (line 49) | def __init__(self, app, options=None):
    method load_config (line 54) | def load_config(self):
    method load (line 62) | def load(self):
  class StandaloneApplication (line 43) | class StandaloneApplication(gunicorn.app.base.BaseApplication):
    method __init__ (line 32) | def __init__(self):
    method load_config (line 35) | def load_config(self):
    method load (line 38) | def load(self):
    method __init__ (line 49) | def __init__(self, app, options=None):
    method load_config (line 54) | def load_config(self):
    method load (line 62) | def load(self):
  function package_result (line 66) | def package_result(status: str, msg: str, data: dict):
  function create_app (line 95) | def create_app(client_port: int = 5559, modules_name: list = []):
  function run (line 164) | def run(port: int = 8866, client_port: int = 5559, names: list = [], wor...
  function run_http_server (line 189) | def run_http_server(port: int = 8866, client_port: int = 5559, names: li...
  function run_all (line 213) | def run_all(modules_info: dict, gpus: list, frontend_port: int, backend_...

FILE: paddlehub/serving/model_service/base_model_service.py
  class BaseModuleInfo (line 19) | class BaseModuleInfo(object):
    method __init__ (line 20) | def __init__(self):
    method set_modules_info (line 24) | def set_modules_info(self, modules_info):
    method get_module_info (line 30) | def get_module_info(self, module_name):
    method add_module (line 33) | def add_module(self, module_name, module_info):
    method get_module (line 37) | def get_module(self, module_name):
    method modules_info (line 41) | def modules_info(self):
  class CVModuleInfo (line 45) | class CVModuleInfo(BaseModuleInfo):
    method __init__ (line 46) | def __init__(self):
    method cv_modules (line 80) | def cv_modules(self):
    method add_module (line 83) | def add_module(self, module_name, module_info):
  class NLPModuleInfo (line 89) | class NLPModuleInfo(BaseModuleInfo):
    method __init__ (line 90) | def __init__(self):
    method nlp_modules (line 94) | def nlp_modules(self):
    method add_module (line 97) | def add_module(self, module_name, module_info):
  class V2ModuleInfo (line 103) | class V2ModuleInfo(BaseModuleInfo):
    method __init__ (line 104) | def __init__(self):
    method modules (line 108) | def modules(self):
    method add_module (line 111) | def add_module(self, module_name, module_info):
  class BaseModelService (line 116) | class BaseModelService(object):
    method _initialize (line 117) | def _initialize(self):
    method _pre_processing (line 121) | def _pre_processing(self, data):
    method _inference (line 125) | def _inference(self, data):
    method _post_processing (line 129) | def _post_processing(self, data):

FILE: paddlehub/serving/worker.py
  function run_worker (line 24) | def run_worker(modules_info: dict, gpu_index: int, addr: str):

FILE: paddlehub/text/bert_tokenizer.py
  class BasicTokenizer (line 28) | class BasicTokenizer(object):
    method __init__ (line 31) | def __init__(self, do_lower_case: bool = True, never_split: List[str] ...
    method tokenize (line 48) | def tokenize(self, text: str, never_split: List[str] = None):
    method _run_strip_accents (line 76) | def _run_strip_accents(self, text: str):
    method _run_split_on_punc (line 87) | def _run_split_on_punc(self, text: str, never_split: List[str] = None):
    method _tokenize_chinese_chars (line 109) | def _tokenize_chinese_chars(self, text: str):
    method _clean_text (line 121) | def _clean_text(self, text: str):
    method encode (line 134) | def encode(self):
    method decode (line 138) | def decode(self):
  class WordpieceTokenizer (line 143) | class WordpieceTokenizer(object):
    method __init__ (line 146) | def __init__(self, vocab: List[str], unk_token: str, max_input_chars_p...
    method tokenize (line 151) | def tokenize(self, text):
    method encode (line 198) | def encode(self):
    method decode (line 202) | def decode(self):
  class BertTokenizer (line 207) | class BertTokenizer(object):
    method __init__ (line 242) | def __init__(
    method vocab_size (line 282) | def vocab_size(self):
    method get_vocab (line 285) | def get_vocab(self):
    method _convert_token_to_id (line 288) | def _convert_token_to_id(self, token):
    method _convert_id_to_token (line 292) | def _convert_id_to_token(self, index):
    method convert_tokens_to_string (line 296) | def convert_tokens_to_string(self, tokens):
    method convert_tokens_to_ids (line 301) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 316) | def convert_ids_to_tokens(self, ids: Union[int, List[int]],
    method tokenize (line 333) | def tokenize(self, text: str):
    method build_inputs_with_special_tokens (line 350) | def build_inputs_with_special_tokens(self, token_ids_0: List[int],
    method num_special_tokens_to_add (line 372) | def num_special_tokens_to_add(self, pair=False):
    method get_special_tokens_mask (line 388) | def get_special_tokens_mask(self,
    method create_segment_ids_from_sequences (line 416) | def create_segment_ids_from_sequences(self, token_ids_0: List[int],
    method clean_up_tokenization (line 439) | def clean_up_tokenization(self, out_string: str) -> str:
    method truncate_sequences (line 447) | def truncate_sequences(
    method encode (line 506) | def encode(self,
    method decode (line 652) | def decode(self,
  class ErnieTinyTokenizer (line 693) | class ErnieTinyTokenizer(BertTokenizer):
    method __init__ (line 694) | def __init__(
    method cut (line 734) | def cut(self, chars: List[str]):
    method tokenize (line 751) | def tokenize(self, text: str):

FILE: paddlehub/text/tokenizer.py
  class CustomTokenizer (line 27) | class CustomTokenizer(object):
    method __init__ (line 33) | def __init__(self,
    method vocab_size (line 69) | def vocab_size(self):
    method get_vocab (line 72) | def get_vocab(self):
    method _convert_token_to_id (line 75) | def _convert_token_to_id(self, token: str):
    method _convert_id_to_token (line 79) | def _convert_id_to_token(self, index: int):
    method convert_tokens_to_string (line 83) | def convert_tokens_to_string(self, tokens: List[str]):
    method convert_ids_to_tokens (line 91) | def convert_ids_to_tokens(self, ids: Union[int, List[int]], skip_pad_t...
    method convert_tokens_to_ids (line 108) | def convert_tokens_to_ids(self, tokens: List[str]):
    method tokenize (line 125) | def tokenize(self, text: str):
    method encode (line 141) | def encode(self,
    method truncate_sequences (line 230) | def truncate_sequences(self,
    method decode (line 287) | def decode(self,
    method clean_up_tokenization (line 321) | def clean_up_tokenization(self, out_string: str) -> str:

FILE: paddlehub/text/utils.py
  function load_vocab (line 20) | def load_vocab(vocab_file: str):
  function whitespace_tokenize (line 31) | def whitespace_tokenize(text: str):
  function is_whitespace (line 40) | def is_whitespace(char: str):
  function is_control (line 52) | def is_control(char: str):
  function is_punctuation (line 64) | def is_punctuation(char: str):
  function is_chinese_char (line 79) | def is_chinese_char(char: str):

FILE: paddlehub/utils/download.py
  function download_data (line 25) | def download_data(url):
  class Downloader (line 45) | class Downloader:
    method download_file_and_uncompress (line 46) | def download_file_and_uncompress(self, url: str, save_path: str, print...

FILE: paddlehub/utils/io.py
  function redirect_istream (line 24) | def redirect_istream(stream: IO):
  function redirect_ostream (line 33) | def redirect_ostream(stream: IO):
  function redirect_estream (line 42) | def redirect_estream(stream: IO):
  function discard_oe (line 51) | def discard_oe():
  function typein (line 62) | def typein(chars: str = 'y'):

FILE: paddlehub/utils/log.py
  class Logger (line 66) | class Logger(object):
    method __init__ (line 74) | def __init__(self, name: str = None):
    method disable (line 97) | def disable(self):
    method enable (line 100) | def enable(self):
    method is_enable (line 104) | def is_enable(self) -> bool:
    method __call__ (line 107) | def __call__(self, log_level: str, msg: str):
    method use_terminator (line 114) | def use_terminator(self, terminator: str):
    method processing (line 121) | def processing(self, msg: str, interval: float = 0.1):
  class ProgressBar (line 148) | class ProgressBar(object):
    method __init__ (line 170) | def __init__(self, title: str, flush_interval: float = 0.1):
    method __enter__ (line 176) | def __enter__(self):
    method __exit__ (line 180) | def __exit__(self, exit_exception, exit_value, exit_traceback):
    method update (line 187) | def update(self, progress: float):
  class FormattedText (line 206) | class FormattedText(object):
    method __init__ (line 225) | def __init__(self, text: str, width: int = None, align: str = '<', col...
    method __repr__ (line 231) | def __repr__(self) -> str:
  class TableCell (line 239) | class TableCell(object):
    method __init__ (line 242) | def __init__(self, content: str = '', width: int = 0, align: str = '<'...
    method width (line 253) | def width(self) -> int:
    method width (line 257) | def width(self, value: int):
    method height (line 263) | def height(self) -> int:
    method height (line 267) | def height(self, value: int):
    method __len__ (line 273) | def __len__(self) -> int:
    method __getitem__ (line 276) | def __getitem__(self, idx: int) -> str:
    method __repr__ (line 279) | def __repr__(self) -> str:
  class TableRow (line 283) | class TableRow(object):
    method __init__ (line 286) | def __init__(self):
    method append (line 289) | def append(self, cell: TableCell):
    method width (line 293) | def width(self) -> int:
    method height (line 300) | def height(self) -> int:
    method __len__ (line 306) | def __len__(self) -> int:
    method __repr__ (line 309) | def __repr__(self) -> str:
    method __getitem__ (line 321) | def __getitem__(self, idx: int) -> TableCell:
  class TableColumn (line 325) | class TableColumn(object):
    method __init__ (line 328) | def __init__(self):
    method append (line 331) | def append(self, cell: TableCell):
    method width (line 335) | def width(self) -> int:
    method height (line 342) | def height(self) -> int:
    method __len__ (line 348) | def __len__(self) -> int:
    method __getitem__ (line 351) | def __getitem__(self, idx: int) -> TableCell:
  class Table (line 355) | class Table(object):
    method __init__ (line 392) | def __init__(self, colors: List[str] = [], aligns: List[str] = [], wid...
    method append (line 399) | def append(self, *contents, colors: List[str] = [], aligns: List[str] ...
    method _adjust (line 444) | def _adjust(self):
    method width (line 461) | def width(self) -> int:
    method height (line 468) | def height(self) -> int:
    method __repr__ (line 474) | def __repr__(self) -> str:
  function get_file_logger (line 483) | def get_file_logger(filename):

FILE: paddlehub/utils/paddlex.py
  class ResourceNotFoundError (line 23) | class ResourceNotFoundError(Exception):
    method __init__ (line 24) | def __init__(self, name: str, version: str = None):
    method __str__ (line 28) | def __str__(self):
  function download (line 36) | def download(name: str, save_path: str, version: str = None):

FILE: paddlehub/utils/parser.py
  class CSVFileParser (line 24) | class CSVFileParser(object):
    method parse (line 25) | def parse(self, csv_file: str) -> dict:
  class YAMLFileParser (line 45) | class YAMLFileParser(object):
    method parse (line 46) | def parse(self, yaml_file: str) -> dict:
  class TextFileParser (line 52) | class TextFileParser(object):
    method parse (line 53) | def parse(self, txt_file: str, use_strip: bool = True) -> List:

FILE: paddlehub/utils/platform.py
  function get_platform (line 20) | def get_platform() -> str:
  function is_windows (line 24) | def is_windows() -> bool:
  function get_platform_info (line 28) | def get_platform_info() -> dict:

FILE: paddlehub/utils/pypi.py
  function get_installed_packages (line 25) | def get_installed_packages() -> dict:
  function check (line 31) | def check(package: str, version: str = '') -> bool:
  function install (line 44) | def install(package: str, version: str = '', upgrade: bool = False, ostr...
  function install_from_file (line 64) | def install_from_file(file: str, ostream: IO = sys.stdout, estream: IO =...
  function uninstall (line 76) | def uninstall(package: str, ostream: IO = sys.stdout, estream: IO = sys....

FILE: paddlehub/utils/utils.py
  class Version (line 41) | class Version(packaging.version.Version):
    method match (line 44) | def match(self, condition: str) -> bool:
    method __lt__ (line 81) | def __lt__(self, other):
    method __le__ (line 86) | def __le__(self, other):
    method __gt__ (line 91) | def __gt__(self, other):
    method __ge__ (line 96) | def __ge__(self, other):
    method __eq__ (line 101) | def __eq__(self, other):
  class Timer (line 107) | class Timer(object):
    method __init__ (line 110) | def __init__(self, total_step: int):
    method start (line 116) | def start(self):
    method stop (line 120) | def stop(self):
    method count (line 124) | def count(self) -> int:
    method timing (line 130) | def timing(self) -> float:
    method is_running (line 138) | def is_running(self) -> bool:
    method eta (line 142) | def eta(self) -> str:
  function seconds_to_hms (line 150) | def seconds_to_hms(seconds: int) -> str:
  function cv2_to_base64 (line 159) | def cv2_to_base64(image: np.ndarray) -> str:
  function base64_to_cv2 (line 164) | def base64_to_cv2(b64str: str) -> np.ndarray:
  function generate_tempfile (line 173) | def generate_tempfile(directory: str = None, **kwargs):
  function generate_tempdir (line 181) | def generate_tempdir(directory: str = None, **kwargs):
  function download (line 188) | def download(url: str, path: str = None) -> str:
  function download_with_progress (line 204) | def download_with_progress(url: str, path: str = None) -> Generator[str,...
  function load_py_module (line 234) | def load_py_module(python_path: str, py_module_name: str) -> types.Modul...
  function get_platform_default_encoding (line 256) | def get_platform_default_encoding() -> str:
  function sys_stdin_encoding (line 263) | def sys_stdin_encoding() -> str:
  function sys_stdout_encoding (line 274) | def sys_stdout_encoding() -> str:
  function md5 (line 285) | def md5(text: str):
  function record (line 291) | def record(msg: str) -> str:
  function record_exception (line 303) | def record_exception(msg: str) -> str:
  function get_record_file (line 310) | def get_record_file() -> str:
  function is_port_occupied (line 314) | def is_port_occupied(ip: str, port: int) -> bool:
  function mkdir (line 327) | def mkdir(path: str):
  function reseg_token_label (line 333) | def reseg_token_label(tokenizer, tokens: List[str], labels: List[str] = ...
  function pad_sequence (line 371) | def pad_sequence(ids: List[int], max_seq_len: int, pad_token_id: int):
  function trunc_sequence (line 381) | def trunc_sequence(ids: List[int], max_seq_len: int):
  function extract_melspectrogram (line 391) | def extract_melspectrogram(y,
  function convert_version (line 429) | def convert_version(version: str) -> List:

FILE: paddlehub/utils/xarfile.py
  class XarInfo (line 24) | class XarInfo(object):
    method __init__ (line 27) | def __init__(self, _xarinfo, arctype='tar'):
    method name (line 32) | def name(self) -> str:
    method size (line 38) | def size(self) -> int:
  class XarFile (line 44) | class XarFile(object):
    method __init__ (line 63) | def __init__(self, name: str, mode: str, arctype: str = 'tar', **kwargs):
    method __del__ (line 100) | def __del__(self):
    method __enter__ (line 103) | def __enter__(self):
    method __exit__ (line 106) | def __exit__(self, exit_exception, exit_value, exit_traceback):
    method add (line 113) | def add(self, name: str, arcname: str = None, recursive: bool = True, ...
    method extract (line 136) | def extract(self, name: str, path: str):
    method extractall (line 140) | def extractall(self, path: str):
    method getnames (line 144) | def getnames(self) -> List[str]:
    method getxarinfo (line 150) | def getxarinfo(self, name: str) -> List[XarInfo]:
  function open (line 157) | def open(name: str, mode: str = 'w', **kwargs) -> XarFile:
  function archive (line 165) | def archive(filename: str, recursive: bool = True, exclude: Callable = N...
  function unarchive (line 192) | def unarchive(name: str, path: str):
  function unarchive_with_progress (line 210) | def unarchive_with_progress(name: str, path: str) -> Generator[str, int,...
  function is_xarfile (line 236) | def is_xarfile(file: str) -> bool:

FILE: paddlehub/vision/detect_transforms.py
  class RandomDistort (line 27) | class RandomDistort:
    method __init__ (line 41) | def __init__(self, lower: float = 0.5, upper: float = 1.5):
    method random_brightness (line 45) | def random_brightness(self, img: PIL.Image):
    method random_contrast (line 49) | def random_contrast(self, img: PIL.Image):
    method random_color (line 53) | def random_color(self, img: PIL.Image):
    method __call__ (line 57) | def __call__(self, img: np.ndarray, data: dict):
  class RandomExpand (line 69) | class RandomExpand:
    method __init__ (line 85) | def __init__(self, max_ratio: float = 4., fill: list = None, keep_rati...
    method __call__ (line 92) | def __call__(self, img: np.ndarray, data: dict):
  class RandomCrop (line 128) | class RandomCrop:
    method __init__ (line 145) | def __init__(self, scales: list = [0.3, 1.0], max_ratio: float = 2.0, ...
    method __call__ (line 152) | def __call__(self, img: np.ndarray, data: dict):
  class RandomFlip (line 201) | class RandomFlip:
    method __init__ (line 212) | def __init__(self, thresh: float = 0.5):
    method __call__ (line 215) | def __call__(self, img, data):
  class Compose (line 224) | class Compose:
    method __init__ (line 236) | def __init__(self, transforms: list):
    method __call__ (line 244) | def __call__(self, data: dict):
  class Resize (line 266) | class Resize:
    method __init__ (line 279) | def __init__(self, target_size: int = 512, interp: str = 'RANDOM'):
    method __call__ (line 300) | def __call__(self, img, data=None):
  class Normalize (line 313) | class Normalize:
    method __init__ (line 326) | def __init__(self, mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]):
    method __call__ (line 335) | def __call__(self, im, data=None):
  class ShuffleBox (line 347) | class ShuffleBox:
    method __call__ (line 350) | def __call__(self, img, data):

FILE: paddlehub/vision/functional.py
  function normalize (line 23) | def normalize(im: np.ndarray, mean: float, std: float) -> np.ndarray:
  function permute (line 38) | def permute(im: np.ndarray) -> np.ndarray:
  function resize (line 49) | def resize(im: np.ndarray, target_size: Union[List[int], int], interpola...
  function resize_long (line 70) | def resize_long(im: np.ndarray, long_size: int, interpolation: int = cv2...
  function horizontal_flip (line 88) | def horizontal_flip(im: np.ndarray) -> np.ndarray:
  function vertical_flip (line 102) | def vertical_flip(im: np.ndarray) -> np.ndarray:
  function brightness (line 116) | def brightness(im: np.ndarray, brightness_lower: float, brightness_upper...
  function contrast (line 130) | def contrast(im: np.ndarray, contrast_lower: float, contrast_upper: floa...
  function saturation (line 144) | def saturation(im: np.ndarray, saturation_lower: float, saturation_upper...
  function hue (line 158) | def hue(im: np.ndarray, hue_lower: float, hue_upper: float) -> np.ndarray:
  function rotate (line 174) | def rotate(im: np.ndarray, rotate_lower: float, rotate_upper: float) -> ...

FILE: paddlehub/vision/segmentation_transforms.py
  class Compose (line 26) | class Compose:
    method __init__ (line 40) | def __init__(self, transforms: Callable, to_rgb: bool = True):
    method __call__ (line 49) | def __call__(self, im: Union[np.ndarray, str], label: Union[np.ndarray...
  class ColorMap (line 76) | class ColorMap:
    method __init__ (line 79) | def __init__(self, num_classes: int = 256):
    method __call__ (line 82) | def __call__(self) -> np.ndarray:
  class SegmentVisual (line 98) | class SegmentVisual:
    method __init__ (line 104) | def __init__(self, weight: float = 0.6):
    method __call__ (line 108) | def __call__(self, image: str, result: np.ndarray, save_dir: str) -> n...
  class Padding (line 129) | class Padding:
    method __init__ (line 142) | def __init__(self,
    method __call__ (line 156) | def __call__(self, im: np.ndarray, label: np.ndarray = None) -> Tuple:
  class Normalize (line 189) | class Normalize:
    method __init__ (line 199) | def __init__(self,
    method __call__ (line 210) | def __call__(self, im: np.ndarray, label: np.ndarray = None) -> Tuple:
  class Resize (line 229) | class Resize:
    method __init__ (line 254) | def __init__(self, target_size: Union[List[int], Tuple[int]] = (512, 5...
    method __call__ (line 267) | def __call__(self, im: np.ndarray, label: np.ndarray = None) -> Tuple:

FILE: paddlehub/vision/transforms.py
  class Compose (line 25) | class Compose:
    method __init__ (line 35) | def __init__(self, transforms: Callable, to_rgb: bool = False, channel...
    method __call__ (line 45) | def __call__(self, im: Union[np.ndarray, str]):
  class Permute (line 62) | class Permute:
    method __init__ (line 67) | def __init__(self):
    method __call__ (line 70) | def __call__(self, im):
  class RandomHorizontalFlip (line 75) | class RandomHorizontalFlip:
    method __init__ (line 83) | def __init__(self, prob: float = 0.5):
    method __call__ (line 86) | def __call__(self, im: np.ndarray):
  class RandomVerticalFlip (line 92) | class RandomVerticalFlip:
    method __init__ (line 100) | def __init__(self, prob: float = 0.5):
    method __call__ (line 103) | def __call__(self, im: np.ndarray):
  class Resize (line 109) | class Resize:
    method __init__ (line 126) | def __init__(self, target_size: Union[List[int], int], interpolation: ...
    method __call__ (line 140) | def __call__(self, im: np.ndarray):
  class ResizeByLong (line 149) | class ResizeByLong:
    method __init__ (line 157) | def __init__(self, long_size: Union[List[int], int]):
    method __call__ (line 160) | def __call__(self, im):
  class ResizeRangeScaling (line 165) | class ResizeRangeScaling:
    method __init__ (line 174) | def __init__(self, min_value: int = 400, max_value: int = 600):
    method __call__ (line 181) | def __call__(self, im: np.ndarray):
  class ResizeStepScaling (line 190) | class ResizeStepScaling:
    method __init__ (line 201) | def __init__(self, min_scale_factor: float = 0.75, max_scale_factor: f...
    method __call__ (line 209) | def __call__(self, im: np.ndarray):
  class Normalize (line 228) | class Normalize:
    method __init__ (line 238) | def __init__(self, mean: list = [0.5, 0.5, 0.5], std: list = [0.5, 0.5...
    method __call__ (line 248) | def __call__(self, im):
  class Padding (line 259) | class Padding:
    method __init__ (line 268) | def __init__(self, target_size: Union[List[int], Tuple[int], int], im_...
    method __call__ (line 279) | def __call__(self, im: np.ndarray):
  class RandomPaddingCrop (line 299) | class RandomPaddingCrop:
    method __init__ (line 308) | def __init__(self, crop_size, im_padding_value=[127.5, 127.5, 127.5]):
    method __call__ (line 319) | def __call__(self, im):
  class RandomBlur (line 348) | class RandomBlur:
    method __init__ (line 356) | def __init__(self, prob: float = 0.1):
    method __call__ (line 359) | def __call__(self, im: np.ndarray):
  class RandomRotation (line 378) | class RandomRotation:
    method __init__ (line 388) | def __init__(self, max_rotation: float = 15, im_padding_value: list = ...
    method __call__ (line 392) | def __call__(self, im):
  class RandomDistort (line 419) | class RandomDistort:
    method __init__ (line 435) | def __init__(self,
    method __call__ (line 453) | def __call__(self, im: np.ndarray):
  class RGB2LAB (line 501) | class RGB2LAB:
    method rgb2xyz (line 506) | def rgb2xyz(self, rgb: np.ndarray) -> np.ndarray:
    method xyz2lab (line 526) | def xyz2lab(self, xyz: np.ndarray) -> np.ndarray:
    method rgb2lab (line 546) | def rgb2lab(self, rgb: np.ndarray) -> np.ndarray:
    method __call__ (line 562) | def __call__(self, img: np.ndarray) -> np.ndarray:
  class LAB2RGB (line 569) | class LAB2RGB:
    method __init__ (line 574) | def __init__(self, mode: str = 'RGB2LAB'):
    method xyz2rgb (line 577) | def xyz2rgb(self, xyz: np.ndarray) -> np.ndarray:
    method lab2xyz (line 598) | def lab2xyz(self, lab: np.ndarray) -> np.ndarray:
    method lab2rgb (line 621) | def lab2rgb(self, lab_rs: np.ndarray) -> np.ndarray:
    method __call__ (line 637) | def __call__(self, img: np.ndarray) -> np.ndarray:
  class CenterCrop (line 641) | class CenterCrop:
    method __init__ (line 652) | def __init__(self, crop_size: int):
    method __call__ (line 655) | def __call__(self, img: np.ndarray):

FILE: paddlehub/vision/utils.py
  function is_image_file (line 26) | def is_image_file(filename: str) -> bool:
  function get_img_file (line 32) | def get_img_file(dir_name: str) -> List[str]:
  function box_crop (line 45) | def box_crop(boxes: np.ndarray, labels: np.ndarray, scores: np.ndarray, ...
  function box_iou_xywh (line 74) | def box_iou_xywh(box1: np.ndarray, box2: np.ndarray) -> float:
  function draw_boxes_on_image (line 101) | def draw_boxes_on_image(image_path: str,
  function get_label_infos (line 155) | def get_label_infos(file_list: str) -> str:
  function subtract_imagenet_mean_batch (line 166) | def subtract_imagenet_mean_batch(batch: paddle.Tensor) -> paddle.Tensor:
  function gram_matrix (line 176) | def gram_matrix(data: paddle.Tensor) -> paddle.Tensor:
  function npmax (line 185) | def npmax(array: np.ndarray) -> Tuple[int]:
  function visualize (line 194) | def visualize(image: Union[np.ndarray, str], result: np.ndarray, weight:...
  function get_pseudo_color_map (line 224) | def get_pseudo_color_map(pred: np.ndarray) -> PIL.Image.Image:
  function get_color_map_list (line 232) | def get_color_map_list(num_classes: int) -> List[int]:
  function get_reverse_list (line 259) | def get_reverse_list(ori_shape: List[int], transforms: List[Callable]) -...
  function reverse_transform (line 284) | def reverse_transform(pred: paddle.Tensor, ori_shape: List[int], transfo...
  class ConfusionMatrix (line 299) | class ConfusionMatrix(object):
    method __init__ (line 309) | def __init__(self, num_classes: int, streaming: bool = False):
    method calculate (line 314) | def calculate(self, pred, label, ignore=None):
    method zero_matrix (line 329) | def zero_matrix(self):
    method mean_iou (line 333) | def mean_iou(self) -> float:
    method accuracy (line 362) | def accuracy(self) -> float:
    method kappa (line 388) | def kappa(self) -> float:

FILE: tests/test_module.py
  class TestHubModule (line 7) | class TestHubModule(unittest.TestCase):
    method test_lac (line 8) | def test_lac(self):
    method test_senta (line 20) | def test_senta(self):
    method test_simnet (line 34) | def test_simnet(self):
    method test_ssd (line 48) | def test_ssd(self):