SYMBOL INDEX (248 symbols across 26 files)

FILE: build_soft_labels/gen_soft_label.py
  function parse_args (line 9) | def parse_args():
  function calculate_srcc_plcc (line 30) | def calculate_srcc_plcc(pred, mos):
  function get_level (line 36) | def get_level(mos, min_mos, max_mos):
  function adjust_gaussian_bar (line 49) | def adjust_gaussian_bar(probs, score):
  function get_binary_probs (line 64) | def get_binary_probs(mos, min_mos=1.0, max_mos=5.0):
  function main (line 80) | def main(cfg):

FILE: src/conversation.py
  class SeparatorStyle (line 6) | class SeparatorStyle(Enum):
  class Conversation (line 17) | class Conversation:
    method get_prompt (line 30) | def get_prompt(self):
    method append_message (line 119) | def append_message(self, role, message):
    method get_images (line 122) | def get_images(self, return_pil=False):
    method to_gradio_chatbot (line 172) | def to_gradio_chatbot(self):
    method copy (line 203) | def copy(self):
    method dict (line 214) | def dict(self):

FILE: src/datasets/__init__.py
  function make_data_module (line 5) | def make_data_module(tokenizer, data_args):

FILE: src/datasets/pair_dataset.py
  class PairDataset (line 19) | class PairDataset(Dataset):
    method __init__ (line 22) | def __init__(
    method __len__ (line 49) | def __len__(self):
    method lengths (line 53) | def lengths(self):
    method modality_lengths (line 65) | def modality_lengths(self):
    method next_rand (line 76) | def next_rand(self):
    method __getitem__ (line 79) | def __getitem__(self, i):
    method get_one_item (line 112) | def get_one_item(self, idx_dataset, idx_sample) -> Dict[str, torch.Ten...
  class DataCollatorForPairDataset (line 214) | class DataCollatorForPairDataset(object):
    method __call__ (line 219) | def __call__(self, instances: Sequence[Dict]) -> Dict[str, torch.Tensor]:
    method collate_one (line 229) | def collate_one(self, instances: Sequence[Dict]) -> Dict[str, torch.Te...
  function make_pair_data_module (line 263) | def make_pair_data_module(

FILE: src/datasets/single_dataset.py
  class SingleDataset (line 18) | class SingleDataset(Dataset):
    method __init__ (line 21) | def __init__(
    method __len__ (line 39) | def __len__(self):
    method lengths (line 43) | def lengths(self):
    method modality_lengths (line 54) | def modality_lengths(self):
    method next_rand (line 64) | def next_rand(self):
    method __getitem__ (line 69) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  class DataCollatorForSupervisedDataset (line 194) | class DataCollatorForSupervisedDataset(object):
    method __call__ (line 199) | def __call__(self, instances: Sequence[Dict]) -> Dict[str, torch.Tensor]:
  function make_single_data_module (line 231) | def make_single_data_module(

FILE: src/datasets/utils.py
  function rank0_print (line 22) | def rank0_print(*args):
  class DataArguments (line 31) | class DataArguments:
  function _tokenize_fn (line 40) | def _tokenize_fn(
  function _mask_targets (line 67) | def _mask_targets(target, tokenized_lens, speakers):
  function _add_speaker_and_signal (line 78) | def _add_speaker_and_signal(header, source, get_conversation=True):
  function preprocess_multimodal (line 100) | def preprocess_multimodal(sources: Sequence[str], data_args: DataArgumen...
  function preprocess_v1 (line 122) | def preprocess_v1(
  function preprocess_plain (line 210) | def preprocess_plain(
  function preprocess (line 239) | def preprocess(
  function load_video (line 292) | def load_video(video_file):
  function expand2square (line 306) | def expand2square(pil_img, background_color):

FILE: src/evaluate/cal_distribution_gap.py
  function parse_args (line 7) | def parse_args():
  function kl_divergence (line 17) | def kl_divergence(mu_1, mu_2, sigma_1, sigma_2):
  function js_divergence (line 34) | def js_divergence(mu_1, mu_2, sigma_1, sigma_2):
  function wasserstein_distance (line 55) | def wasserstein_distance(mu_1, mu_2, sigma_1, sigma_2):
  function cal_score (line 71) | def cal_score(level_names, logits=None, probs=None, use_openset_probs=Fa...
  function cal_std (line 83) | def cal_std(score, probs):

FILE: src/evaluate/cal_plcc_srcc.py
  function parse_args (line 9) | def parse_args():
  function calculate_srcc (line 19) | def calculate_srcc(pred, mos):
  function calculate_plcc (line 24) | def calculate_plcc(pred, mos):
  function fit_curve (line 29) | def fit_curve(x, y, curve_type="logistic_4params"):
  function cal_score (line 65) | def cal_score(level_names, logits=None, probs=None, use_openset_probs=Fa...

FILE: src/evaluate/eval_qbench_mcq.py
  function disable_torch_init (line 21) | def disable_torch_init():
  function load_image (line 30) | def load_image(image_file):
  function main (line 39) | def main(args):

FILE: src/evaluate/iqa_eval.py
  function disable_torch_init (line 18) | def disable_torch_init():
  function load_image (line 28) | def load_image(image_file):
  function main (line 37) | def main(args):

FILE: src/evaluate/scorer.py
  class Scorer (line 14) | class Scorer(nn.Module):
    method __init__ (line 15) | def __init__(self, pretrained="zhiyuanyou/DeQA-Score-Mix3", device="cu...
    method expand2square (line 28) | def expand2square(self, pil_img, background_color):
    method forward (line 41) | def forward(self, image: List[Image.Image]):

FILE: src/mm_utils.py
  function load_image_from_base64 (line 11) | def load_image_from_base64(image):
  function expand2square (line 15) | def expand2square(pil_img, background_color):
  function process_images (line 29) | def process_images(images, image_processor, model_cfg=None):
  function tokenizer_image_token (line 53) | def tokenizer_image_token(prompt, tokenizer, image_token_index=IMAGE_TOK...
  function get_model_name_from_path (line 75) | def get_model_name_from_path(model_path):
  class KeywordsStoppingCriteria (line 86) | class KeywordsStoppingCriteria(StoppingCriteria):
    method __init__ (line 87) | def __init__(self, keywords, tokenizer, input_ids):
    method __call__ (line 101) | def __call__(self, output_ids: torch.LongTensor, scores: torch.FloatTe...

FILE: src/model/builder.py
  function load_pretrained_model (line 31) | def load_pretrained_model(

FILE: src/model/configuration_mplug_owl2.py
  class LlamaConfig (line 15) | class LlamaConfig(PretrainedConfig):
    method __init__ (line 99) | def __init__(
    method _rope_scaling_validation (line 154) | def _rope_scaling_validation(self):
  class MplugOwlVisionConfig (line 176) | class MplugOwlVisionConfig(PretrainedConfig):
    method __init__ (line 218) | def __init__(
    method from_pretrained (line 253) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....
  class MplugOwlVisualAbstractorConfig (line 269) | class MplugOwlVisualAbstractorConfig(PretrainedConfig):
    method __init__ (line 272) | def __init__(
    method from_pretrained (line 299) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....
  class MPLUGOwl2Config (line 321) | class MPLUGOwl2Config(LlamaConfig):
    method __init__ (line 323) | def __init__(self, visual_config=None, **kwargs):

FILE: src/model/convert_mplug_owl2_weight_to_hf.py
  function compute_intermediate_size (line 65) | def compute_intermediate_size(n):
  function read_json (line 69) | def read_json(path):
  function write_json (line 74) | def write_json(text, path):
  function write_model (line 79) | def write_model(model_path,
  function write_tokenizer (line 346) | def write_tokenizer(tokenizer_path, input_tokenizer_path):
  function main (line 354) | def main():

FILE: src/model/modeling_attn_mask_utils.py
  class AttentionMaskConverter (line 19) | class AttentionMaskConverter:
    method __init__ (line 35) | def __init__(self, is_causal: bool, sliding_window: Optional[int] = No...
    method to_causal_4d (line 44) | def to_causal_4d(
    method to_4d (line 77) | def to_4d(
    method _make_causal_mask (line 120) | def _make_causal_mask(
    method _expand_mask (line 150) | def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Opti...
  function _prepare_4d_causal_attention_mask (line 164) | def _prepare_4d_causal_attention_mask(
  function _prepare_4d_attention_mask (line 204) | def _prepare_4d_attention_mask(mask: torch.Tensor, dtype: torch.dtype, t...
  function _create_4d_causal_attention_mask (line 220) | def _create_4d_causal_attention_mask(

FILE: src/model/modeling_llama2.py
  function _get_unpad_data (line 22) | def _get_unpad_data(attention_mask):
  class MultiwayNetwork (line 40) | class MultiwayNetwork(nn.Module):
    method __init__ (line 42) | def __init__(self, module_provider, num_multiway=2):
    method forward (line 47) | def forward(self, hidden_states, multiway_indices):
  class LlamaAttention (line 67) | class LlamaAttention(nn.Module):
    method __init__ (line 70) | def __init__(self, config: LlamaConfig, layer_idx: Optional[int] = None):
    method _init_rope (line 106) | def _init_rope(self):
    method _shape (line 133) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 136) | def forward(
  class LlamaFlashAttention2 (line 210) | class LlamaFlashAttention2(LlamaAttention):
    method __init__ (line 217) | def __init__(self, *args, **kwargs):
    method forward (line 225) | def forward(
    method _flash_attention_forward (line 316) | def _flash_attention_forward(
    method _upad_input (line 375) | def _upad_input(self, query_layer, key_layer, value_layer, attention_m...
  class LlamaSdpaAttention (line 414) | class LlamaSdpaAttention(LlamaAttention):
    method forward (line 422) | def forward(
  class LlamaDecoderLayer (line 510) | class LlamaDecoderLayer(nn.Module):
    method __init__ (line 511) | def __init__(self, config: LlamaConfig, layer_idx):
    method forward (line 524) | def forward(
  function model_forward (line 581) | def model_forward(
  function causal_model_forward (line 726) | def causal_model_forward(
  function replace_llama_modality_adaptive (line 820) | def replace_llama_modality_adaptive():

FILE: src/model/modeling_mplug_owl2.py
  class MPLUGOwl2MetaModel (line 45) | class MPLUGOwl2MetaModel:
    method __init__ (line 46) | def __init__(self, config):
    method get_vision_tower (line 56) | def get_vision_tower(self):
    method get_visual_abstractor (line 62) | def get_visual_abstractor(self):
  class MPLUGOwl2MetaForCausalLM (line 69) | class MPLUGOwl2MetaForCausalLM(ABC):
    method get_model (line 71) | def get_model(self):
    method encode_images (line 74) | def encode_images(self, images):
    method prepare_inputs_labels_for_multimodal (line 83) | def prepare_inputs_labels_for_multimodal(
  class MPLUGOwl2LlamaModel (line 324) | class MPLUGOwl2LlamaModel(MPLUGOwl2MetaModel, LlamaModel):
    method __init__ (line 327) | def __init__(self, config: MPLUGOwl2Config):
  class MPLUGOwl2LlamaForCausalLM (line 331) | class MPLUGOwl2LlamaForCausalLM(LlamaForCausalLM, MPLUGOwl2MetaForCausal...
    method __init__ (line 334) | def __init__(self, config):
    method get_model (line 343) | def get_model(self):
    method forward (line 346) | def forward(self, input_type=None, **kwargs):
    method softkl_loss (line 380) | def softkl_loss(self, logits, labels, level_probs):
    method forward_single (line 406) | def forward_single(
    method get_score (line 514) | def get_score(self, item):
    method get_subitem (line 558) | def get_subitem(self, item, task_type):
    method forward_pair (line 585) | def forward_pair(self, item_A, item_B, **kwargs):
    method rating_loss (line 669) | def rating_loss(
    method binary_rating_loss (line 695) | def binary_rating_loss(self, pred_scores_A, gt_scores_A, pred_scores_B...
    method prepare_inputs_for_generation (line 709) | def prepare_inputs_for_generation(

FILE: src/model/utils.py
  function extend_list (line 5) | def extend_list(data_list, n, min_n):
  function find_prefix (line 13) | def find_prefix(input_ids, prefix):
  function auto_upgrade (line 35) | def auto_upgrade(config):

FILE: src/model/visual_encoder.py
  function get_abs_pos (line 14) | def get_abs_pos(abs_pos, tgt_size):
  function get_2d_sincos_pos_embed (line 33) | def get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False):
  function get_2d_sincos_pos_embed_from_grid (line 51) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
  function get_1d_sincos_pos_embed_from_grid (line 62) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
  class MplugOwlVisionEmbeddings (line 84) | class MplugOwlVisionEmbeddings(nn.Module):
    method __init__ (line 85) | def __init__(self, config):
    method forward (line 108) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class MplugOwlVisionAttention (line 121) | class MplugOwlVisionAttention(nn.Module):
    method __init__ (line 124) | def __init__(self, config):
    method _shape (line 141) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 144) | def forward(
  class QuickGELU (line 224) | class QuickGELU(nn.Module):
    method forward (line 225) | def forward(self, x: torch.Tensor):
  class MplugOwlMLP (line 229) | class MplugOwlMLP(nn.Module):
    method __init__ (line 230) | def __init__(self, config):
    method forward (line 237) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class MplugOwlVisionEncoderLayer (line 244) | class MplugOwlVisionEncoderLayer(nn.Module):
    method __init__ (line 245) | def __init__(self, config):
    method forward (line 253) | def forward(
  class MplugOwlVisionEncoder (line 292) | class MplugOwlVisionEncoder(nn.Module):
    method __init__ (line 302) | def __init__(self, config):
    method forward (line 308) | def forward(
  class MplugOwlVisionModel (line 384) | class MplugOwlVisionModel(PreTrainedModel):
    method __init__ (line 388) | def __init__(self, config):
    method forward (line 400) | def forward(
    method get_input_embeddings (line 445) | def get_input_embeddings(self):
  class MplugOwlVisualAbstractorMLP (line 449) | class MplugOwlVisualAbstractorMLP(nn.Module):
    method __init__ (line 450) | def __init__(self, config):
    method forward (line 461) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class MplugOwlVisualAbstractorMultiHeadAttention (line 468) | class MplugOwlVisualAbstractorMultiHeadAttention(nn.Module):
    method __init__ (line 469) | def __init__(self, config):
    method save_attn_gradients (line 507) | def save_attn_gradients(self, attn_gradients):
    method get_attn_gradients (line 510) | def get_attn_gradients(self):
    method save_attention_map (line 513) | def save_attention_map(self, attention_map):
    method get_attention_map (line 516) | def get_attention_map(self):
    method transpose_for_scores (line 519) | def transpose_for_scores(self, x):
    method forward (line 524) | def forward(
  class MplugOwlVisualAbstractorCrossOutput (line 586) | class MplugOwlVisualAbstractorCrossOutput(nn.Module):
    method __init__ (line 587) | def __init__(self, config):
    method forward (line 594) | def forward(self, hidden_states: torch.Tensor, input_tensor: torch.Ten...
  class MplugOwlVisualAbstractorAttention (line 600) | class MplugOwlVisualAbstractorAttention(nn.Module):
    method __init__ (line 601) | def __init__(self, config):
    method prune_heads (line 609) | def prune_heads(self, heads):
    method forward (line 627) | def forward(
  class MplugOwlVisualAbstractorLayer (line 657) | class MplugOwlVisualAbstractorLayer(nn.Module):
    method __init__ (line 658) | def __init__(self, config, layer_idx):
    method forward (line 668) | def forward(
  class MplugOwlVisualAbstractorEncoder (line 693) | class MplugOwlVisualAbstractorEncoder(nn.Module):
    method __init__ (line 694) | def __init__(self, config):
    method forward (line 702) | def forward(
  class MplugOwlVisualAbstractorModel (line 757) | class MplugOwlVisualAbstractorModel(PreTrainedModel):
    method __init__ (line 759) | def __init__(self, config, language_hidden_size):
    method _prune_heads (line 770) | def _prune_heads(self, heads_to_prune):
    method get_extended_attention_mask (line 778) | def get_extended_attention_mask(
    method forward (line 822) | def forward(

FILE: src/train/mplug_owl2_trainer.py
  function maybe_zero_3 (line 12) | def maybe_zero_3(param, ignore_status=False, name=None):
  function get_mm_adapter_state_maybe_zero_3 (line 26) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function split_to_even_chunks (line 32) | def split_to_even_chunks(indices, lengths, num_chunks):
  function get_modality_length_grouped_indices (line 54) | def get_modality_length_grouped_indices(lengths, batch_size, world_size,...
  function get_length_grouped_indices (line 82) | def get_length_grouped_indices(lengths, batch_size, world_size, generato...
  class LengthGroupedSampler (line 93) | class LengthGroupedSampler(Sampler):
    method __init__ (line 99) | def __init__(
    method __len__ (line 116) | def __len__(self):
    method __iter__ (line 119) | def __iter__(self):
  class MPLUGOwl2Trainer (line 127) | class MPLUGOwl2Trainer(Trainer):
    method _get_train_sampler (line 129) | def _get_train_sampler(self) -> Optional[torch.utils.data.Sampler]:
    method create_optimizer (line 144) | def create_optimizer(self):
    method _save_checkpoint (line 227) | def _save_checkpoint(self, model, trial, metrics=None):
    method _save (line 230) | def _save(self, output_dir: Optional[str] = None, state_dict=None):

FILE: src/train/train_mem.py
  function rank0_print (line 38) | def rank0_print(*args):
  class ModelArguments (line 44) | class ModelArguments:
  class DataArguments (line 51) | class DataArguments:
  class TrainingArguments (line 63) | class TrainingArguments(transformers.TrainingArguments):
  function maybe_zero_3 (line 149) | def maybe_zero_3(param, ignore_status=False, name=None):
  function get_peft_state_maybe_zero_3 (line 167) | def get_peft_state_maybe_zero_3(named_params, bias):
  function get_peft_state_non_lora_maybe_zero_3 (line 192) | def get_peft_state_non_lora_maybe_zero_3(named_params, require_grad_only...
  function get_mm_adapter_state_maybe_zero_3 (line 202) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function find_all_lora_names (line 214) | def find_all_lora_names(model):
  function safe_save_model_for_hf_trainer (line 228) | def safe_save_model_for_hf_trainer(
  function smart_tokenizer_and_embedding_resize (line 248) | def smart_tokenizer_and_embedding_resize(
  function train (line 275) | def train():

FILE: src/utils.py
  function build_logger (line 17) | def build_logger(logger_name, logger_filename):
  class StreamToLogger (line 60) | class StreamToLogger(object):
    method __init__ (line 64) | def __init__(self, logger, log_level=logging.INFO):
    method __getattr__ (line 70) | def __getattr__(self, attr):
    method write (line 73) | def write(self, buf):
    method flush (line 87) | def flush(self):
  function disable_torch_init (line 93) | def disable_torch_init():
  function violates_moderation (line 102) | def violates_moderation(text):
  function pretty_print_semaphore (line 123) | def pretty_print_semaphore(semaphore):

FILE: tests/datasets/test_pair_dataset.py
  class DataArguments (line 13) | class DataArguments:

FILE: tests/model/test_find_prefix.py
  function find_prefix (line 5) | def find_prefix(input_ids, prefix):

FILE: tests/model/test_grad.py
  class MyModel (line 5) | class MyModel(nn.Module):
    method __init__ (line 6) | def __init__(self, dim_in, closeset):
    method forward (line 12) | def forward(self, x_A, x_B, gt):
    method get_score (line 20) | def get_score(self, logits):
    method rating_loss (line 34) | def rating_loss(self, pred_scores_A, pred_scores_B, gt):