SYMBOL INDEX (380 symbols across 56 files)

FILE: HTTP_API_TtsDemo/apidemo/TtsDemo.py
  function createRequest (line 14) | def createRequest():
  function doCall (line 31) | def doCall(url, header, params, method):
  function saveFile (line 38) | def saveFile(res):

FILE: HTTP_API_TtsDemo/apidemo/utils/AuthV3Util.py
  function addAuthParams (line 17) | def addAuthParams(appKey, appSecret, params):
  function calculateSign (line 40) | def calculateSign(appKey, appSecret, q, salt, curtime):
  function encrypt (line 45) | def encrypt(strSrc):
  function getInput (line 51) | def getInput(input):

FILE: cn2an/an2cn.py
  class An2Cn (line 13) | class An2Cn(object):
    method __init__ (line 14) | def __init__(self) -> None:
    method an2cn (line 20) | def an2cn(self, inputs: Union[str, int, float] = None, mode: str = "lo...
    method __direct_convert (line 116) | def __direct_convert(self, inputs: str) -> str:
    method __number_to_string (line 126) | def __number_to_string(number_data: Union[int, float]) -> str:
    method __check_inputs_is_valid (line 139) | def __check_inputs_is_valid(self, check_data: str) -> None:
    method __integer_convert (line 146) | def __integer_convert(self, integer_data: str, mode: str) -> str:
    method __decimal_convert (line 187) | def __decimal_convert(self, decimal_data: str, o_mode: str) -> str:

FILE: config/joint/config.py
  function get_labels_length (line 18) | def get_labels_length(file_path):
  class Config (line 32) | class Config:

FILE: config/template.py
  function get_labels_length (line 18) | def get_labels_length(file_path):
  class Config (line 32) | class Config:

FILE: data/DataBaker/src/step1_clean_raw_data.py
  function main (line 13) | def main(args):

FILE: data/DataBaker/src/step2_get_phoneme.py
  function g2p_cn_en (line 35) | def g2p_cn_en(text, g2p, lexicon):
  function get_eng_phoneme (line 73) | def get_eng_phoneme(text, g2p, lexicon):
  function onetime (line 114) | def onetime(resource, sample):
  function onetime2 (line 127) | def onetime2(resource, sample):
  function get_phoneme (line 148) | def get_phoneme(text, g2p):
  function main (line 163) | def main(args):

FILE: data/LJspeech/src/step1_clean_raw_data.py
  function main (line 22) | def main(args):

FILE: data/LJspeech/src/step2_get_phoneme.py
  function onetime (line 30) | def onetime(resource, sample):
  function get_phoneme (line 43) | def get_phoneme(text, g2p, lexicon):
  function main (line 83) | def main(args):

FILE: demo_page.py
  function create_download_link (line 36) | def create_download_link():
  function scan_checkpoint (line 61) | def scan_checkpoint(cp_dir, prefix, c=8):
  function get_models (line 69) | def get_models():
  function get_style_embedding (line 105) | def get_style_embedding(prompt, tokenizer, style_encoder):
  function tts (line 119) | def tts(name, text, prompt, content, speaker, models):
  function new_line (line 157) | def new_line(i):

FILE: demo_page_databaker.py
  function create_download_link (line 36) | def create_download_link():
  function scan_checkpoint (line 61) | def scan_checkpoint(cp_dir, prefix, c=8):
  function get_models (line 69) | def get_models():
  function get_style_embedding (line 105) | def get_style_embedding(prompt, tokenizer, style_encoder):
  function tts (line 119) | def tts(name, text, prompt, content, speaker, models):
  function new_line (line 157) | def new_line(i):

FILE: frontend.py
  function g2p_cn_en (line 23) | def g2p_cn_en(text, g2p, lexicon):
  function contains_chinese (line 61) | def contains_chinese(text):

FILE: frontend_cn.py
  function split_py (line 23) | def split_py(py):
  function has_chinese_punctuation (line 77) | def has_chinese_punctuation(text):
  function has_english_punctuation (line 80) | def has_english_punctuation(text):
  function number_to_chinese (line 86) | def number_to_chinese(number):
  function tn_chinese (line 92) | def tn_chinese(text):
  function g2p_cn (line 102) | def g2p_cn(text):

FILE: frontend_en.py
  function read_lexicon (line 27) | def read_lexicon(lex_path):
  function get_eng_phoneme (line 38) | def get_eng_phoneme(text, g2p, lexicon, pad_sos_eos=True):

FILE: inference_am_vocoder_exp.py
  function get_style_embedding (line 25) | def get_style_embedding(prompt, tokenizer, style_encoder):
  function main (line 40) | def main(args, config):

FILE: inference_am_vocoder_joint.py
  function get_style_embedding (line 25) | def get_style_embedding(prompt, tokenizer, style_encoder):
  function main (line 40) | def main(args, config):

FILE: inference_tts.py
  function get_style_embedding (line 31) | def get_style_embedding(prompt, tokenizer, style_encoder):
  function main (line 46) | def main(args, config, gpu_id, start_idx, chunk_num):

FILE: mel_process.py
  function dynamic_range_compression_torch (line 19) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression_torch (line 24) | def dynamic_range_decompression_torch(x, C=1):
  function spectral_normalize_torch (line 29) | def spectral_normalize_torch(magnitudes):
  function spectral_de_normalize_torch (line 34) | def spectral_de_normalize_torch(magnitudes):
  function spectrogram_torch (line 43) | def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, cente...
  function spec_to_mel_torch (line 65) | def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
  function mel_spectrogram_torch (line 77) | def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, w...

FILE: mfa/step1_create_dataset.py
  function main (line 8) | def main(args):

FILE: mfa/step2_prepare_data.py
  function get_args (line 9) | def get_args():
  function save_scp_files (line 20) | def save_scp_files(wav_scp_path: os.PathLike, speaker_scp_path: os.PathL...
  function main (line 38) | def main(args):

FILE: mfa/step3_prepare_special_tokens.py
  function get_args (line 4) | def get_args():
  function main (line 11) | def main(args):

FILE: mfa/step4_convert_text_to_phn.py
  function get_args (line 21) | def get_args():
  function main (line 31) | def main(args):

FILE: mfa/step5_prepare_alignment.py
  function get_args (line 10) | def get_args():
  function main (line 32) | def main(args):

FILE: mfa/step7_gen_alignment_from_textgrid.py
  function readtg (line 32) | def readtg(tg_path):
  function insert_special_tokens (line 63) | def insert_special_tokens(seq1: List[str], seq2: List[str],
  function get_args (line 129) | def get_args():
  function main (line 165) | def main(args):

FILE: mfa/step8_make_data_list.py
  function read_lists (line 19) | def read_lists(list_file):
  function get_args (line 26) | def get_args():
  function main (line 39) | def main(args):

FILE: mfa/step9_datalist_from_mfa.py
  function main (line 8) | def main(args):

FILE: models/hifigan/dataset.py
  function get_mel (line 26) | def get_mel(filename, stft, sampling_rate, trim=False):
  function pad_mel (line 48) | def pad_mel(data, downsample_ratio, max_len ):
  class DatasetTTS (line 60) | class DatasetTTS(torch.utils.data.Dataset):
    method __init__ (line 61) | def __init__(self, data_path, config):
    method load_files (line 77) | def load_files(self, data_path):
    method __len__ (line 83) | def __len__(self):
    method __getitem__ (line 86) | def __getitem__(self, index):
    method TextMelCollate (line 100) | def TextMelCollate(self, data):

FILE: models/hifigan/env.py
  class AttrDict (line 9) | class AttrDict(dict):
    method __init__ (line 10) | def __init__(self, *args, **kwargs):
  function build_env (line 15) | def build_env(config, config_name, path):

FILE: models/hifigan/get_random_segments.py
  function get_random_segments (line 8) | def get_random_segments( x: torch.Tensor, x_lengths: torch.Tensor, segme...
  function get_segments (line 19) | def get_segments( x: torch.Tensor, start_idxs: torch.Tensor, segment_siz...

FILE: models/hifigan/get_vocoder.py
  function vocoder (line 21) | def vocoder(hifi_gan_path, hifi_gan_name):
  function vocoder2 (line 39) | def vocoder2(config,hifi_gan_ckpt_path):
  function vocoder_inference (line 52) | def vocoder_inference(vocoder, melspec, max_db, min_db):

FILE: models/hifigan/models.py
  function init_weights (line 18) | def init_weights(m, mean=0.0, std=0.01):
  function get_padding (line 23) | def get_padding(kernel_size, dilation=1):
  class ResBlock1 (line 26) | class ResBlock1(torch.nn.Module):
    method __init__ (line 27) | def __init__(self, h, channels, kernel_size=3, dilation=(1, 3, 5)):
    method forward (line 50) | def forward(self, x):
    method remove_weight_norm (line 59) | def remove_weight_norm(self):
  class ResBlock2 (line 66) | class ResBlock2(torch.nn.Module):
    method __init__ (line 67) | def __init__(self, h, channels, kernel_size=3, dilation=(1, 3)):
    method forward (line 78) | def forward(self, x):
    method remove_weight_norm (line 85) | def remove_weight_norm(self):
  class Generator (line 90) | class Generator(torch.nn.Module):
    method __init__ (line 91) | def __init__(self, h):
    method forward (line 115) | def forward(self, x):
    method remove_weight_norm (line 133) | def remove_weight_norm(self):
  class DiscriminatorP (line 143) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 144) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=...
    method forward (line 157) | def forward(self, x):
  class MultiPeriodDiscriminator (line 179) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 180) | def __init__(self):
    method forward (line 190) | def forward(self, y, y_hat):
  class DiscriminatorS (line 206) | class DiscriminatorS(torch.nn.Module):
    method __init__ (line 207) | def __init__(self, use_spectral_norm=False):
    method forward (line 221) | def forward(self, x):
  class MultiScaleDiscriminator (line 234) | class MultiScaleDiscriminator(torch.nn.Module):
    method __init__ (line 235) | def __init__(self):
    method forward (line 247) | def forward(self, y, y_hat):
  class Discriminator (line 266) | class Discriminator(nn.Module):
    method __init__ (line 267) | def __init__(self, config) -> None:
    method forward (line 273) | def forward(self, y, y_hat):
  function feature_loss (line 279) | def feature_loss(fmap_r, fmap_g):
  function discriminator_loss (line 288) | def discriminator_loss(disc_real_outputs, disc_generated_outputs):
  function generator_loss (line 302) | def generator_loss(disc_outputs):

FILE: models/hifigan/pretrained_discriminator.py
  class Discriminator (line 21) | class Discriminator(nn.Module):
    method __init__ (line 22) | def __init__(self, config) -> None:
    method forward (line 33) | def forward(self, y, y_hat):

FILE: models/prompt_tts_modified/audio_processing.py
  function window_sumsquare (line 11) | def window_sumsquare(window,
  function griffin_lim (line 36) | def griffin_lim(magnitudes, stft_fn, n_iters=30):
  function dynamic_range_compression (line 50) | def dynamic_range_compression(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression (line 54) | def dynamic_range_decompression(x, C=1):

FILE: models/prompt_tts_modified/feats.py
  class LogMelFBank (line 21) | class LogMelFBank():
    method __init__ (line 23) | def __init__(self,
    method _create_mel_filter (line 48) | def _create_mel_filter(self):
    method _stft (line 56) | def _stft(self, wav):
    method _spectrogram (line 66) | def _spectrogram(self, wav):
    method _mel_spectrogram (line 70) | def _mel_spectrogram(self, wav):
    method get_log_mel_fbank (line 75) | def get_log_mel_fbank(self, wav):
  class Pitch (line 83) | class Pitch():
    method __init__ (line 85) | def __init__(self, sr=24000, hop_length=300, pitch_min=80, pitch_max=7...
    method _convert_to_continuous_pitch (line 92) | def _convert_to_continuous_pitch(self, pitch: np.array) -> np.array:
    method _calculate_pitch (line 114) | def _calculate_pitch(self,
    method _average_by_duration (line 132) | def _average_by_duration(self, input: np.array, d: np.array) -> np.array:
    method get_pitch (line 147) | def get_pitch(self,
  class Energy (line 159) | class Energy():
    method __init__ (line 161) | def __init__(self,
    method _stft (line 178) | def _stft(self, wav):
    method _calculate_energy (line 188) | def _calculate_energy(self, input):
    method _average_by_duration (line 198) | def _average_by_duration(self, input: np.array, d: np.array) -> np.array:
    method get_energy (line 209) | def get_energy(self, wav, use_token_averaged_energy=True, duration=None):
  function window_sumsquare (line 216) | def window_sumsquare(window,
  function griffin_lim (line 241) | def griffin_lim(magnitudes, stft_fn, n_iters=30):
  function dynamic_range_compression (line 261) | def dynamic_range_compression(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression (line 270) | def dynamic_range_decompression(x, C=1):
  class STFT (line 281) | class STFT(torch.nn.Module):
    method __init__ (line 282) | def __init__(self, filter_length=800, hop_length=200, win_length=800,
    method transform (line 315) | def transform(self, input_data):
    method inverse (line 345) | def inverse(self, magnitude, phase):
    method forward (line 376) | def forward(self, input_data):
  class TacotronSTFT (line 381) | class TacotronSTFT(torch.nn.Module):
    method __init__ (line 382) | def __init__(self, filter_length=1024, hop_length=256, win_length=1024,
    method spectral_normalize (line 398) | def spectral_normalize(self, magnitudes):
    method spectral_de_normalize (line 402) | def spectral_de_normalize(self, magnitudes):
    method mel_spectrogram (line 406) | def mel_spectrogram(self, y):

FILE: models/prompt_tts_modified/jets.py
  class JETSGenerator (line 26) | class JETSGenerator(nn.Module):
    method __init__ (line 27) | def __init__(self, config) -> None:
    method forward (line 50) | def forward(self, inputs_ling, input_lengths, inputs_speaker, inputs_s...

FILE: models/prompt_tts_modified/loss.py
  function get_mask_from_lengths (line 10) | def get_mask_from_lengths(lengths, max_len=None):
  class MelReconLoss (line 22) | class MelReconLoss(torch.nn.Module):
    method __init__ (line 23) | def __init__(self, loss_type="mae"):
    method forward (line 33) | def forward(self, output_lengths, mel_targets, dec_outputs, postnet_ou...
  class ForwardSumLoss (line 59) | class ForwardSumLoss(torch.nn.Module):
    method __init__ (line 61) | def __init__(self):
    method forward (line 64) | def forward(
  class ProsodyReconLoss (line 99) | class ProsodyReconLoss(torch.nn.Module):
    method __init__ (line 100) | def __init__(self, loss_type="mae"):
    method forward (line 110) | def forward(
  class TTSLoss (line 147) | class TTSLoss(torch.nn.Module):
    method __init__ (line 148) | def __init__(self, loss_type="mae") -> None:
    method forward (line 155) | def forward(self, outputs):

FILE: models/prompt_tts_modified/model_open_source.py
  class PromptTTS (line 14) | class PromptTTS(nn.Module):
    method __init__ (line 15) | def __init__(self, config) -> None:
    method forward (line 102) | def forward(self, inputs_ling, input_lengths, inputs_speaker, inputs_s...
    method get_mask_from_lengths (line 164) | def get_mask_from_lengths(self, lengths: torch.Tensor) -> torch.Tensor:
    method average_utterance_prosody (line 174) | def average_utterance_prosody(
    method load_my_state_dict (line 180) | def load_my_state_dict(self, state_dict):
    method make_pad_mask (line 194) | def make_pad_mask(self, lengths, max_len=None):
    method make_non_pad_mask (line 206) | def make_non_pad_mask(self, length, max_len=None):

FILE: models/prompt_tts_modified/modules/alignment.py
  class AlignmentModule (line 13) | class AlignmentModule(nn.Module):
    method __init__ (line 15) | def __init__(self, adim, odim, cache_prior=True):
    method forward (line 27) | def forward(self, text, feats, text_lengths, feats_lengths, x_masks=No...
    method _generate_prior (line 59) | def _generate_prior(self, text_lengths, feats_lengths, w=1) -> torch.T...
  function _monotonic_alignment_search (line 93) | def _monotonic_alignment_search(log_p_attn):
  function viterbi_decode (line 125) | def viterbi_decode(log_p_attn, text_lengths, feats_lengths):
  function _average_by_duration (line 146) | def _average_by_duration(ds, xs, text_lengths, feats_lengths):
  function average_by_duration (line 165) | def average_by_duration(ds, xs, text_lengths, feats_lengths):
  class GaussianUpsampling (line 175) | class GaussianUpsampling(torch.nn.Module):
    method __init__ (line 177) | def __init__(self, delta=0.1):
    method forward (line 180) | def forward(self, hs, ds, h_masks=None, d_masks=None, alpha=1.0):

FILE: models/prompt_tts_modified/modules/encoder.py
  class MultiSequential (line 10) | class MultiSequential(torch.nn.Sequential):
    method __init__ (line 13) | def __init__(self, *args, layer_drop_rate=0.0):
    method forward (line 18) | def forward(self, *args):
  function repeat (line 27) | def repeat(N, fn, layer_drop_rate=0.0):
  class MultiLayeredConv1d (line 31) | class MultiLayeredConv1d(torch.nn.Module):
    method __init__ (line 32) | def __init__(self, in_chans, hidden_chans, kernel_size, dropout_rate):
    method forward (line 50) | def forward(self, x):
  class MultiHeadedAttention (line 55) | class MultiHeadedAttention(nn.Module):
    method __init__ (line 58) | def __init__(self, n_head, n_feat, dropout_rate):
    method forward_qkv (line 72) | def forward_qkv(self, query, key, value):
    method forward_attention (line 84) | def forward_attention(self, value, scores, mask):
    method forward (line 105) | def forward(self, query, key, value, mask):
  class LayerNorm (line 112) | class LayerNorm(torch.nn.LayerNorm):
    method __init__ (line 114) | def __init__(self, nout, dim=-1):
    method forward (line 119) | def forward(self, x):
  class EncoderLayer (line 129) | class EncoderLayer(nn.Module):
    method __init__ (line 130) | def __init__(
    method forward (line 154) | def forward(self, x, mask, cache=None):
  class PositionalEncoding (line 204) | class PositionalEncoding(torch.nn.Module):
    method __init__ (line 206) | def __init__(self, d_model, dropout_rate, max_len=5000, reverse=False):
    method extend_pe (line 216) | def extend_pe(self, x):
    method forward (line 239) | def forward(self, x: torch.Tensor):
  class ScaledPositionalEncoding (line 246) | class ScaledPositionalEncoding(PositionalEncoding):
    method __init__ (line 248) | def __init__(self, d_model, dropout_rate, max_len=5000):
    method reset_parameters (line 253) | def reset_parameters(self):
    method forward (line 257) | def forward(self, x):
  class Encoder (line 263) | class Encoder(torch.nn.Module):
    method __init__ (line 264) | def __init__(
    method forward (line 316) | def forward(self, xs, masks):

FILE: models/prompt_tts_modified/modules/initialize.py
  function initialize (line 11) | def initialize(model: torch.nn.Module, init: str):

FILE: models/prompt_tts_modified/modules/variance.py
  class DurationPredictor (line 9) | class DurationPredictor(torch.nn.Module):
    method __init__ (line 11) | def __init__(
    method _forward (line 36) | def _forward(self, xs, x_masks=None, is_inference=False):
    method forward (line 58) | def forward(self, xs, x_masks=None):
    method inference (line 62) | def inference(self, xs, x_masks=None):
  class VariancePredictor (line 68) | class VariancePredictor(torch.nn.Module):
    method __init__ (line 71) | def __init__(
    method forward (line 101) | def forward(self, xs: torch.Tensor, x_masks: torch.Tensor = None) -> t...

FILE: models/prompt_tts_modified/prompt_dataset.py
  function get_mel (line 29) | def get_mel(filename, stft, sampling_rate, trim=False):
  function pad_mel (line 51) | def pad_mel(data, downsample_ratio, max_len ):
  class Dataset_PromptTTS (line 63) | class Dataset_PromptTTS(torch.utils.data.Dataset):
    method __init__ (line 64) | def __init__(self, data_path, config, style_encoder):
    method get_style_embedding (line 106) | def get_style_embedding(self, uttid, prompt, dir):
    method load_files (line 125) | def load_files(self, data_path):
    method get_pitch (line 130) | def get_pitch(self, wav, pitch_stats):
    method get_energy (line 137) | def get_energy(self, wav, energy_stats):
    method __len__ (line 144) | def __len__(self):
    method __getitem__ (line 147) | def __getitem__(self, index):
    method TextMelCollate (line 179) | def TextMelCollate(self, data):
  class Dataset_Prompt_Pretrain (line 246) | class Dataset_Prompt_Pretrain(torch.utils.data.Dataset):
    method __init__ (line 247) | def __init__(self, data_path, config):
    method load_files (line 265) | def load_files(self, data_path):
    method __len__ (line 270) | def __len__(self):
    method __getitem__ (line 273) | def __getitem__(self, index):
    method TextMelCollate (line 292) | def TextMelCollate(self, data):

FILE: models/prompt_tts_modified/scheduler.py
  class FindLR (line 8) | class FindLR(_LRScheduler):
    method __init__ (line 11) | def __init__(self, optimizer, max_steps, max_lr=10):
    method get_lr (line 16) | def get_lr(self):
  class NoamLR (line 24) | class NoamLR(_LRScheduler):
    method __init__ (line 25) | def __init__(self, optimizer, warmup_steps):
    method get_lr (line 29) | def get_lr(self):

FILE: models/prompt_tts_modified/simbert.py
  class ClassificationHead (line 21) | class ClassificationHead(nn.Module):
    method __init__ (line 22) | def __init__(self, hidden_size, num_labels, dropout_rate=0.1) -> None:
    method forward (line 29) | def forward(self, pooled_output):
  class StyleEncoder (line 33) | class StyleEncoder(nn.Module):
    method __init__ (line 34) | def __init__(self, config) -> None:
    method forward (line 48) | def forward(self, input_ids, token_type_ids, attention_mask):
  class StylePretrainLoss (line 76) | class StylePretrainLoss(nn.Module):
    method __init__ (line 77) | def __init__(self) -> None:
    method forward (line 82) | def forward(self, inputs, outputs):
  class StylePretrainLoss2 (line 97) | class StylePretrainLoss2(StylePretrainLoss):
    method __init__ (line 98) | def __init__(self) -> None:
    method forward (line 103) | def forward(self, inputs, outputs):
  function flat_accuracy (line 109) | def flat_accuracy(preds, labels):

FILE: models/prompt_tts_modified/stft.py
  class STFT (line 14) | class STFT(torch.nn.Module):
    method __init__ (line 15) | def __init__(self, filter_length=800, hop_length=200, win_length=800,
    method transform (line 48) | def transform(self, input_data):
    method inverse (line 78) | def inverse(self, magnitude, phase):
    method forward (line 109) | def forward(self, input_data):

FILE: models/prompt_tts_modified/style_encoder.py
  class LearnedDownSample (line 11) | class LearnedDownSample(nn.Module):
    method __init__ (line 12) | def __init__(self, layer_type, dim_in):
    method forward (line 25) | def forward(self, x):
  class LearnedUpSample (line 28) | class LearnedUpSample(nn.Module):
    method __init__ (line 29) | def __init__(self, layer_type, dim_in):
    method forward (line 43) | def forward(self, x):
  class DownSample (line 46) | class DownSample(nn.Module):
    method __init__ (line 47) | def __init__(self, layer_type):
    method forward (line 51) | def forward(self, x):
  class UpSample (line 64) | class UpSample(nn.Module):
    method __init__ (line 65) | def __init__(self, layer_type):
    method forward (line 69) | def forward(self, x):
  class ResBlk (line 80) | class ResBlk(nn.Module):
    method __init__ (line 81) | def __init__(self, dim_in, dim_out, actv=nn.LeakyReLU(0.2),
    method _build_weights (line 91) | def _build_weights(self, dim_in, dim_out):
    method _shortcut (line 100) | def _shortcut(self, x):
    method _residual (line 107) | def _residual(self, x):
    method forward (line 119) | def forward(self, x):
  class StyleEncoder (line 123) | class StyleEncoder(nn.Module):
    method __init__ (line 124) | def __init__(self, dim_in=48, style_dim=48, max_conv_dim=384):
    method forward (line 143) | def forward(self, x):
  class CosineSimilarityLoss (line 151) | class CosineSimilarityLoss(nn.Module):
    method __init__ (line 152) | def __init__(self) -> None:
    method forward (line 157) | def forward(self, output1, output2):

FILE: models/prompt_tts_modified/tacotron_stft.py
  class LinearNorm (line 12) | class LinearNorm(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, in_dim, out_dim, bias=True, w_init_gain='linear'):
    method forward (line 21) | def forward(self, x):
  class ConvNorm (line 25) | class ConvNorm(torch.nn.Module):
    method __init__ (line 26) | def __init__(self, in_channels, out_channels, kernel_size=1, stride=1,
    method forward (line 41) | def forward(self, signal):
  class TacotronSTFT (line 46) | class TacotronSTFT(torch.nn.Module):
    method __init__ (line 47) | def __init__(self, filter_length=1024, hop_length=256, win_length=1024,
    method spectral_normalize (line 63) | def spectral_normalize(self, magnitudes):
    method spectral_de_normalize (line 67) | def spectral_de_normalize(self, magnitudes):
    method mel_spectrogram (line 71) | def mel_spectrogram(self, y):

FILE: openaiapi.py
  function get_env (line 32) | def get_env(key):
  function get_int_env (line 36) | def get_int_env(key):
  function get_float_env (line 40) | def get_float_env(key):
  function get_bool_env (line 44) | def get_bool_env(key):
  function scan_checkpoint (line 48) | def scan_checkpoint(cp_dir, prefix, c=8):
  function get_models (line 56) | def get_models():
  function get_style_embedding (line 95) | def get_style_embedding(prompt, tokenizer, style_encoder):
  function emotivoice_tts (line 110) | def emotivoice_tts(text, prompt, content, speaker, models):
  class SpeechRequest (line 152) | class SpeechRequest(BaseModel):
  function text_to_speech (line 163) | def text_to_speech(speechRequest: SpeechRequest):

FILE: plot_image.py
  function plot_image_sambert (line 6) | def plot_image_sambert(target, melspec, mel_lengths=None, text_lengths=N...

FILE: predict.py
  function scan_checkpoint (line 57) | def scan_checkpoint(cp_dir, prefix, c=8):
  function g2p_en (line 64) | def g2p_en(text):
  function contains_chinese (line 67) | def contains_chinese(text):
  function download_json (line 72) | def download_json(url: str, dest: Path):
  function download_weights (line 80) | def download_weights(baseurl: str, basedest: str, files: List[str]):
  class Predictor (line 99) | class Predictor(BasePredictor):
    method setup_models (line 101) | def setup_models(self):
    method setup (line 138) | def setup(self) -> None:
    method get_style_embedding (line 148) | def get_style_embedding(self, text):
    method tts (line 164) | def tts(self, text, prompt, content, speaker):
    method predict (line 196) | def predict(

FILE: prepare_for_training.py
  function main (line 21) | def main(args):
  function prepare_info (line 38) | def prepare_info(data_dir, info_dir):
  function prepare_config (line 69) | def prepare_config(data_dir, info_dir, exp_dir, config_dir):
  function prepare_ckpt (line 80) | def prepare_ckpt(data_dir, info_dir, ckpt_dir):

FILE: text/__init__.py
  function text_to_sequence (line 18) | def text_to_sequence(text, cleaner_names):
  function sequence_to_text (line 49) | def sequence_to_text(sequence):
  function _clean_text (line 62) | def _clean_text(text, cleaner_names):
  function _symbols_to_sequence (line 71) | def _symbols_to_sequence(symbols):
  function _arpabet_to_sequence (line 75) | def _arpabet_to_sequence(text):
  function _should_keep_symbol (line 79) | def _should_keep_symbol(s):

FILE: text/cleaners.py
  function expand_abbreviations (line 47) | def expand_abbreviations(text):
  function expand_numbers (line 53) | def expand_numbers(text):
  function lowercase (line 57) | def lowercase(text):
  function collapse_whitespace (line 61) | def collapse_whitespace(text):
  function convert_to_ascii (line 65) | def convert_to_ascii(text):
  function basic_cleaners (line 69) | def basic_cleaners(text):
  function transliteration_cleaners (line 76) | def transliteration_cleaners(text):
  function english_cleaners (line 84) | def english_cleaners(text):

FILE: text/cmudict.py
  class CMUDict (line 98) | class CMUDict:
    method __init__ (line 101) | def __init__(self, file_or_path, keep_ambiguous=True):
    method __len__ (line 111) | def __len__(self):
    method lookup (line 114) | def lookup(self, word):
  function _parse_cmudict (line 122) | def _parse_cmudict(file):
  function _get_pronunciation (line 137) | def _get_pronunciation(s):

FILE: text/numbers.py
  function _remove_commas (line 18) | def _remove_commas(m):
  function _expand_decimal_point (line 22) | def _expand_decimal_point(m):
  function _expand_dollars (line 26) | def _expand_dollars(m):
  function _expand_ordinal (line 47) | def _expand_ordinal(m):
  function _expand_number (line 51) | def _expand_number(m):
  function normalize_numbers (line 68) | def normalize_numbers(text):

FILE: train_am_vocoder_joint.py
  function count_parameters (line 24) | def count_parameters(model):
  function get_writer (line 27) | def get_writer(output_directory):
  function save_checkpoint (line 34) | def save_checkpoint(filepath, obj):
  function scan_checkpoint (line 40) | def scan_checkpoint(cp_dir, prefix):
  function load_checkpoint (line 47) | def load_checkpoint(filepath, device):
  function validate (line 57) | def validate(args, generator, val_loader, iteration, writer, config, dev...
  function train (line 198) | def train(args, config):
  function main (line 461) | def main():