SYMBOL INDEX (656 symbols across 71 files)

FILE: __init__.py
  function nt_load_wav (line 14) | def nt_load_wav(speech, sample_rate, target_sr):
  class NTCosyVoiceZeroShotSampler (line 22) | class NTCosyVoiceZeroShotSampler:
    method __init__ (line 23) | def __init__(self):
    method cosyvoice (line 27) | def cosyvoice(self):
    method INPUT_TYPES (line 34) | def INPUT_TYPES(s):
    method main_func (line 49) | def main_func(self, audio, speed, text, prompt_text):
  class NTCosyVoiceCrossLingualSampler (line 65) | class NTCosyVoiceCrossLingualSampler:
    method __init__ (line 66) | def __init__(self):
    method cosyvoice (line 70) | def cosyvoice(self):
    method INPUT_TYPES (line 77) | def INPUT_TYPES(s):
    method main_func (line 91) | def main_func(self, audio, speed, text):
  class NTCosyVoiceInstruct2Sampler (line 108) | class NTCosyVoiceInstruct2Sampler:
    method __init__ (line 109) | def __init__(self):
    method cosyvoice (line 113) | def cosyvoice(self):
    method INPUT_TYPES (line 120) | def INPUT_TYPES(s):
    method main_func (line 135) | def main_func(self, audio, speed, text, instruct):

FILE: cosyvoice/bin/average_model.py
  function get_args (line 24) | def get_args():
  function main (line 43) | def main():

FILE: cosyvoice/bin/export_jit.py
  function get_args (line 29) | def get_args():
  function main (line 40) | def main():

FILE: cosyvoice/bin/export_onnx.py
  function get_dummy_input (line 33) | def get_dummy_input(batch_size, seq_len, out_channels, device):
  function get_args (line 43) | def get_args():
  function main (line 54) | def main():

FILE: cosyvoice/bin/inference.py
  function get_args (line 30) | def get_args():
  function main (line 53) | def main():

FILE: cosyvoice/bin/train.py
  function get_args (line 39) | def get_args():
  function main (line 90) | def main():

FILE: cosyvoice/cli/cosyvoice.py
  class CosyVoice (line 26) | class CosyVoice:
    method __init__ (line 28) | def __init__(self, model_dir, load_jit=True, load_onnx=False, fp16=True):
    method list_available_spks (line 59) | def list_available_spks(self):
    method inference_sft (line 63) | def inference_sft(self, tts_text, spk_id, stream=False, speed=1.0, tex...
    method inference_zero_shot (line 74) | def inference_zero_shot(self, tts_text, prompt_text, prompt_speech_16k...
    method inference_cross_lingual (line 88) | def inference_cross_lingual(self, tts_text, prompt_speech_16k, stream=...
    method inference_instruct (line 99) | def inference_instruct(self, tts_text, spk_id, instruct_text, stream=F...
    method inference_vc (line 114) | def inference_vc(self, source_speech_16k, prompt_speech_16k, stream=Fa...
  class CosyVoice2 (line 124) | class CosyVoice2(CosyVoice):
    method __init__ (line 126) | def __init__(self, model_dir, load_jit=False, load_onnx=False, load_tr...
    method inference_instruct (line 159) | def inference_instruct(self, *args, **kwargs):
    method inference_instruct2 (line 162) | def inference_instruct2(self, tts_text, instruct_text, prompt_speech_1...

FILE: cosyvoice/cli/frontend.py
  class CosyVoiceFrontEnd (line 37) | class CosyVoiceFrontEnd:
    method __init__ (line 39) | def __init__(self,
    method _extract_text_token (line 73) | def _extract_text_token(self, text):
    method _extract_speech_token (line 79) | def _extract_speech_token(self, speech):
    method _extract_spk_embedding (line 91) | def _extract_spk_embedding(self, speech):
    method _extract_speech_feat (line 102) | def _extract_speech_feat(self, speech):
    method text_normalize (line 108) | def text_normalize(self, text, split=True, text_frontend=True):
    method frontend_sft (line 135) | def frontend_sft(self, tts_text, spk_id):
    method frontend_zero_shot (line 141) | def frontend_zero_shot(self, tts_text, prompt_text, prompt_speech_16k,...
    method frontend_cross_lingual (line 161) | def frontend_cross_lingual(self, tts_text, prompt_speech_16k, resample...
    method frontend_instruct (line 170) | def frontend_instruct(self, tts_text, spk_id, instruct_text):
    method frontend_instruct2 (line 179) | def frontend_instruct2(self, tts_text, instruct_text, prompt_speech_16...
    method frontend_vc (line 185) | def frontend_vc(self, source_speech_16k, prompt_speech_16k, resample_r...

FILE: cosyvoice/cli/model.py
  class CosyVoiceModel (line 24) | class CosyVoiceModel:
    method __init__ (line 26) | def __init__(self,
    method load (line 61) | def load(self, llm_model, flow_model, hift_model):
    method load_jit (line 73) | def load_jit(self, llm_text_encoder_model, llm_llm_model, flow_encoder...
    method load_onnx (line 82) | def load_onnx(self, flow_decoder_estimator_model):
    method llm_job (line 91) | def llm_job(self, text, prompt_text, llm_prompt_speech_token, llm_embe...
    method token2wav (line 105) | def token2wav(self, token, prompt_token, prompt_feat, embedding, uuid,...
    method tts (line 145) | def tts(self, text, flow_embedding, llm_embedding=torch.zeros(0, 192),
    method vc (line 208) | def vc(self, source_speech_token, flow_prompt_speech_token, prompt_spe...
  class CosyVoice2Model (line 262) | class CosyVoice2Model:
    method __init__ (line 264) | def __init__(self,
    method load (line 290) | def load(self, llm_model, flow_model, hift_model):
    method load_jit (line 301) | def load_jit(self, flow_encoder_model):
    method load_onnx (line 305) | def load_onnx(self, flow_decoder_estimator_model):
    method load_trt (line 314) | def load_trt(self, flow_decoder_estimator_model):
    method llm_job (line 324) | def llm_job(self, text, prompt_text, llm_prompt_speech_token, llm_embe...
    method token2wav (line 336) | def token2wav(self, token, prompt_token, prompt_feat, embedding, uuid,...
    method tts (line 370) | def tts(self, text, flow_embedding, llm_embedding=torch.zeros(0, 192),

FILE: cosyvoice/dataset/dataset.py
  class Processor (line 27) | class Processor(IterableDataset):
    method __init__ (line 29) | def __init__(self, source, f, *args, **kw):
    method set_epoch (line 36) | def set_epoch(self, epoch):
    method __iter__ (line 39) | def __iter__(self):
    method apply (line 47) | def apply(self, f):
  class DistributedSampler (line 52) | class DistributedSampler:
    method __init__ (line 54) | def __init__(self, shuffle=True, partition=True):
    method update (line 60) | def update(self):
    method set_epoch (line 80) | def set_epoch(self, epoch):
    method sample (line 83) | def sample(self, data):
  class DataList (line 108) | class DataList(IterableDataset):
    method __init__ (line 110) | def __init__(self, lists, shuffle=True, partition=True):
    method set_epoch (line 114) | def set_epoch(self, epoch):
    method __iter__ (line 117) | def __iter__(self):
  function Dataset (line 126) | def Dataset(data_list_file,

FILE: cosyvoice/dataset/processor.py
  function parquet_opener (line 29) | def parquet_opener(data, mode='train', tts_data={}):
  function filter (line 59) | def filter(data,
  function resample (line 111) | def resample(data, resample_rate=22050, min_sample_rate=16000, mode='tra...
  function truncate (line 139) | def truncate(data, truncate_length=24576, mode='train'):
  function compute_fbank (line 160) | def compute_fbank(data,
  function compute_f0 (line 182) | def compute_f0(data, pitch_extractor, mode='train'):
  function parse_embedding (line 203) | def parse_embedding(data, normalize, mode='train'):
  function tokenize (line 221) | def tokenize(data, get_tokenizer, allowed_special, mode='train'):
  function shuffle (line 240) | def shuffle(data, shuffle_size=10000, mode='train'):
  function sort (line 264) | def sort(data, sort_size=500, mode='train'):
  function static_batch (line 292) | def static_batch(data, batch_size=16):
  function dynamic_batch (line 312) | def dynamic_batch(data, max_frames_in_batch=12000, mode='train'):
  function batch (line 341) | def batch(data, batch_type='static', batch_size=16, max_frames_in_batch=...
  function padding (line 355) | def padding(data, use_spk_embedding, mode='train', gan=False):

FILE: cosyvoice/flow/decoder.py
  class Transpose (line 24) | class Transpose(torch.nn.Module):
    method __init__ (line 25) | def __init__(self, dim0: int, dim1: int):
    method forward (line 30) | def forward(self, x: torch.Tensor):
  class CausalBlock1D (line 35) | class CausalBlock1D(Block1D):
    method __init__ (line 36) | def __init__(self, dim: int, dim_out: int):
    method forward (line 46) | def forward(self, x: torch.Tensor, mask: torch.Tensor):
  class CausalResnetBlock1D (line 51) | class CausalResnetBlock1D(ResnetBlock1D):
    method __init__ (line 52) | def __init__(self, dim: int, dim_out: int, time_emb_dim: int, groups: ...
  class CausalConv1d (line 58) | class CausalConv1d(torch.nn.Conv1d):
    method __init__ (line 59) | def __init__(
    method forward (line 81) | def forward(self, x: torch.Tensor):
  class ConditionalDecoder (line 87) | class ConditionalDecoder(nn.Module):
    method __init__ (line 88) | def __init__(
    method initialize_weights (line 203) | def initialize_weights(self):
    method forward (line 217) | def forward(self, x, mask, mu, t, spks=None, cond=None):

FILE: cosyvoice/flow/flow.py
  class MaskedDiffWithXvec (line 24) | class MaskedDiffWithXvec(torch.nn.Module):
    method __init__ (line 25) | def __init__(self,
    method forward (line 60) | def forward(
    method inference (line 105) | def inference(self,
  class CausalMaskedDiffWithXvec (line 151) | class CausalMaskedDiffWithXvec(torch.nn.Module):
    method __init__ (line 152) | def __init__(self,
    method inference (line 190) | def inference(self,

FILE: cosyvoice/flow/flow_matching.py
  class ConditionalCFM (line 20) | class ConditionalCFM(BASECFM):
    method __init__ (line 21) | def __init__(self, in_channels, cfm_params, n_spks=1, spk_emb_dim=64, ...
    method forward (line 36) | def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, c...
    method solve_euler (line 70) | def solve_euler(self, x, t_span, mu, mask, spks, cond):
    method forward_estimator (line 130) | def forward_estimator(self, x, mask, mu, t, spks, cond):
    method compute_loss (line 161) | def compute_loss(self, x1, mask, mu, spks=None, cond=None):
  class CausalConditionalCFM (line 203) | class CausalConditionalCFM(ConditionalCFM):
    method __init__ (line 204) | def __init__(self, in_channels, cfm_params, n_spks=1, spk_emb_dim=64, ...
    method forward (line 209) | def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, c...

FILE: cosyvoice/flow/length_regulator.py
  class InterpolateRegulator (line 21) | class InterpolateRegulator(nn.Module):
    method __init__ (line 22) | def __init__(
    method forward (line 44) | def forward(self, x, ylens=None):
    method inference (line 52) | def inference(self, x1, x2, mel_len1, mel_len2, input_frame_rate=50):

FILE: cosyvoice/hifigan/discriminator.py
  class MultipleDiscriminator (line 9) | class MultipleDiscriminator(nn.Module):
    method __init__ (line 10) | def __init__(
    method forward (line 17) | def forward(self, y: torch.Tensor, y_hat: torch.Tensor):
  class MultiResolutionDiscriminator (line 32) | class MultiResolutionDiscriminator(nn.Module):
    method __init__ (line 33) | def __init__(
    method forward (line 53) | def forward(
  class DiscriminatorR (line 72) | class DiscriminatorR(nn.Module):
    method __init__ (line 73) | def __init__(
    method spectrogram (line 107) | def spectrogram(self, x):
    method forward (line 119) | def forward(self, x: torch.Tensor, cond_embedding_id: torch.Tensor = N...

FILE: cosyvoice/hifigan/f0_predictor.py
  class ConvRNNF0Predictor (line 19) | class ConvRNNF0Predictor(nn.Module):
    method __init__ (line 20) | def __init__(self,
    method forward (line 52) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: cosyvoice/hifigan/generator.py
  class ResBlock (line 43) | class ResBlock(torch.nn.Module):
    method __init__ (line 45) | def __init__(
    method forward (line 91) | def forward(self, x: torch.Tensor) -> torch.Tensor:
    method remove_weight_norm (line 100) | def remove_weight_norm(self):
  class SineGen (line 106) | class SineGen(torch.nn.Module):
    method __init__ (line 122) | def __init__(self, samp_rate, harmonic_num=0,
    method _f02uv (line 132) | def _f02uv(self, f0):
    method forward (line 138) | def forward(self, f0):
  class SourceModuleHnNSF (line 171) | class SourceModuleHnNSF(torch.nn.Module):
    method __init__ (line 189) | def __init__(self, sampling_rate, upsample_scale, harmonic_num=0, sine...
    method forward (line 204) | def forward(self, x):
  class HiFTGenerator (line 223) | class HiFTGenerator(nn.Module):
    method __init__ (line 228) | def __init__(
    method remove_weight_norm (line 319) | def remove_weight_norm(self):
    method _stft (line 333) | def _stft(self, x):
    method _istft (line 341) | def _istft(self, magnitude, phase):
    method decode (line 349) | def decode(self, x: torch.Tensor, s: torch.Tensor = torch.zeros(1, 1, ...
    method forward (line 383) | def forward(
    method inference (line 400) | def inference(self, speech_feat: torch.Tensor, cache_source: torch.Ten...

FILE: cosyvoice/hifigan/hifigan.py
  class HiFiGan (line 9) | class HiFiGan(nn.Module):
    method __init__ (line 10) | def __init__(self, generator, discriminator, mel_spec_transform,
    method forward (line 22) | def forward(
    method forward_generator (line 32) | def forward_generator(self, batch, device):
    method forward_discriminator (line 53) | def forward_discriminator(self, batch, device):

FILE: cosyvoice/llm/llm.py
  class TransformerLM (line 25) | class TransformerLM(torch.nn.Module):
    method __init__ (line 26) | def __init__(
    method encode (line 71) | def encode(
    method pad_unpad_sequence (line 81) | def pad_unpad_sequence(self, sos_eos_emb, embedding, text_token, text_...
    method forward (line 90) | def forward(
    method sampling_ids (line 140) | def sampling_ids(
    method inference (line 154) | def inference(
  class Qwen2Encoder (line 219) | class Qwen2Encoder(torch.nn.Module):
    method __init__ (line 220) | def __init__(self, pretrain_path):
    method forward_one_step (line 224) | def forward_one_step(self, xs, masks, cache=None):
  class Qwen2LM (line 239) | class Qwen2LM(torch.nn.Module):
    method __init__ (line 240) | def __init__(
    method sampling_ids (line 276) | def sampling_ids(
    method inference (line 294) | def inference(

FILE: cosyvoice/tokenizer/tokenizer.py
  function get_encoding (line 170) | def get_encoding(name: str = "gpt2", num_languages: int = 99):
  function get_tokenizer (line 210) | def get_tokenizer(
  class QwenTokenizer (line 241) | class QwenTokenizer():
    method __init__ (line 242) | def __init__(self, token_path, skip_special_tokens=True):
    method encode (line 263) | def encode(self, text, **kwargs):
    method decode (line 268) | def decode(self, tokens):
  function get_qwen_tokenizer (line 275) | def get_qwen_tokenizer(

FILE: cosyvoice/transformer/activation.py
  class Swish (line 24) | class Swish(torch.nn.Module):
    method forward (line 27) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Snake (line 34) | class Snake(nn.Module):
    method __init__ (line 50) | def __init__(self, in_features, alpha=1.0, alpha_trainable=True, alpha...
    method forward (line 73) | def forward(self, x):

FILE: cosyvoice/transformer/attention.py
  class MultiHeadedAttention (line 26) | class MultiHeadedAttention(nn.Module):
    method __init__ (line 36) | def __init__(self,
    method forward_qkv (line 53) | def forward_qkv(
    method forward_attention (line 82) | def forward_attention(
    method forward (line 129) | def forward(
  class RelPositionMultiHeadedAttention (line 200) | class RelPositionMultiHeadedAttention(MultiHeadedAttention):
    method __init__ (line 209) | def __init__(self,
    method rel_shift (line 225) | def rel_shift(self, x: torch.Tensor) -> torch.Tensor:
    method forward (line 249) | def forward(

FILE: cosyvoice/transformer/convolution.py
  class ConvolutionModule (line 24) | class ConvolutionModule(nn.Module):
    method __init__ (line 27) | def __init__(self,
    method forward (line 90) | def forward(

FILE: cosyvoice/transformer/decoder.py
  class TransformerDecoder (line 33) | class TransformerDecoder(torch.nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 116) | def forward(
    method forward_layers (line 169) | def forward_layers(self, x: torch.Tensor, tgt_mask: torch.Tensor,
    method forward_layers_checkpointed (line 178) | def forward_layers_checkpointed(self, x: torch.Tensor,
    method forward_one_step (line 187) | def forward_one_step(
    method tie_or_clone_weights (line 230) | def tie_or_clone_weights(self, jit_mode: bool = True):
  class BiTransformerDecoder (line 256) | class BiTransformerDecoder(torch.nn.Module):
    method __init__ (line 276) | def __init__(
    method forward (line 332) | def forward(
    method forward_one_step (line 367) | def forward_one_step(
    method tie_or_clone_weights (line 392) | def tie_or_clone_weights(self, jit_mode: bool = True):

FILE: cosyvoice/transformer/decoder_layer.py
  class DecoderLayer (line 22) | class DecoderLayer(nn.Module):
    method __init__ (line 41) | def __init__(
    method forward (line 62) | def forward(

FILE: cosyvoice/transformer/embedding.py
  class PositionalEncoding (line 26) | class PositionalEncoding(torch.nn.Module):
    method __init__ (line 37) | def __init__(self,
    method forward (line 59) | def forward(self,
    method position_encoding (line 79) | def position_encoding(self,
  class RelPositionalEncoding (line 120) | class RelPositionalEncoding(PositionalEncoding):
    method __init__ (line 129) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 5...
    method forward (line 133) | def forward(self,
  class WhisperPositionalEncoding (line 150) | class WhisperPositionalEncoding(PositionalEncoding):
    method __init__ (line 154) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 1...
  class LearnablePositionalEncoding (line 167) | class LearnablePositionalEncoding(PositionalEncoding):
    method __init__ (line 171) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 4...
  class NoPositionalEncoding (line 178) | class NoPositionalEncoding(torch.nn.Module):
    method __init__ (line 182) | def __init__(self, d_model: int, dropout_rate: float):
    method forward (line 187) | def forward(self,
    method position_encoding (line 196) | def position_encoding(self, offset: Union[int, torch.Tensor],
  class EspnetRelPositionalEncoding (line 201) | class EspnetRelPositionalEncoding(torch.nn.Module):
    method __init__ (line 215) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 5...
    method extend_pe (line 224) | def extend_pe(self, x: torch.Tensor):
    method forward (line 256) | def forward(self, x: torch.Tensor, offset: Union[int, torch.Tensor] = ...
    method position_encoding (line 272) | def position_encoding(self,

FILE: cosyvoice/transformer/encoder.py
  class BaseEncoder (line 37) | class BaseEncoder(torch.nn.Module):
    method __init__ (line 39) | def __init__(
    method output_size (line 108) | def output_size(self) -> int:
    method forward (line 111) | def forward(
    method forward_layers (line 165) | def forward_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,
    method forward_layers_checkpointed (line 173) | def forward_layers_checkpointed(self, xs: torch.Tensor,
    method forward_chunk (line 184) | def forward_chunk(
    method forward_chunk_by_chunk (line 275) | def forward_chunk_by_chunk(
  class TransformerEncoder (line 338) | class TransformerEncoder(BaseEncoder):
    method __init__ (line 341) | def __init__(
  class ConformerEncoder (line 387) | class ConformerEncoder(BaseEncoder):
    method __init__ (line 390) | def __init__(

FILE: cosyvoice/transformer/encoder_layer.py
  class TransformerEncoderLayer (line 24) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 40) | def __init__(
    method forward (line 58) | def forward(
  class ConformerEncoderLayer (line 109) | class ConformerEncoderLayer(nn.Module):
    method __init__ (line 129) | def __init__(
    method forward (line 160) | def forward(

FILE: cosyvoice/transformer/label_smoothing_loss.py
  class LabelSmoothingLoss (line 21) | class LabelSmoothingLoss(nn.Module):
    method __init__ (line 54) | def __init__(self,
    method forward (line 68) | def forward(self, x: torch.Tensor, target: torch.Tensor) -> torch.Tensor:

FILE: cosyvoice/transformer/positionwise_feed_forward.py
  class PositionwiseFeedForward (line 20) | class PositionwiseFeedForward(torch.nn.Module):
    method __init__ (line 33) | def __init__(
    method forward (line 47) | def forward(self, xs: torch.Tensor) -> torch.Tensor:
  class MoEFFNLayer (line 58) | class MoEFFNLayer(torch.nn.Module):
    method __init__ (line 75) | def __init__(
    method forward (line 91) | def forward(self, xs: torch.Tensor) -> torch.Tensor:

FILE: cosyvoice/transformer/subsampling.py
  class BaseSubsampling (line 23) | class BaseSubsampling(torch.nn.Module):
    method __init__ (line 25) | def __init__(self):
    method position_encoding (line 30) | def position_encoding(self, offset: Union[int, torch.Tensor],
  class EmbedinigNoSubsampling (line 35) | class EmbedinigNoSubsampling(BaseSubsampling):
    method __init__ (line 39) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 45) | def forward(
  class LinearNoSubsampling (line 69) | class LinearNoSubsampling(BaseSubsampling):
    method __init__ (line 79) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 92) | def forward(
  class Conv1dSubsampling2 (line 116) | class Conv1dSubsampling2(BaseSubsampling):
    method __init__ (line 128) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 145) | def forward(
  class Conv2dSubsampling4 (line 173) | class Conv2dSubsampling4(BaseSubsampling):
    method __init__ (line 183) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 202) | def forward(
  class Conv2dSubsampling6 (line 230) | class Conv2dSubsampling6(BaseSubsampling):
    method __init__ (line 239) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 256) | def forward(
  class Conv2dSubsampling8 (line 282) | class Conv2dSubsampling8(BaseSubsampling):
    method __init__ (line 292) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 311) | def forward(
  class LegacyLinearNoSubsampling (line 338) | class LegacyLinearNoSubsampling(BaseSubsampling):
    method __init__ (line 348) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 362) | def forward(

FILE: cosyvoice/transformer/upsample_encoder.py
  class Upsample1D (line 37) | class Upsample1D(nn.Module):
    method __init__ (line 51) | def __init__(self, channels: int, out_channels: int, stride: int = 2):
    method forward (line 59) | def forward(self, inputs: torch.Tensor, input_lengths: torch.Tensor):
  class PreLookaheadLayer (line 66) | class PreLookaheadLayer(nn.Module):
    method __init__ (line 67) | def __init__(self, channels: int, pre_lookahead_len: int = 1):
    method forward (line 81) | def forward(self, inputs: torch.Tensor) -> torch.Tensor:
  class UpsampleConformerEncoder (line 99) | class UpsampleConformerEncoder(torch.nn.Module):
    method __init__ (line 101) | def __init__(
    method output_size (line 234) | def output_size(self) -> int:
    method forward (line 237) | def forward(
    method forward_layers (line 306) | def forward_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,
    method forward_up_layers (line 313) | def forward_up_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,

FILE: cosyvoice/utils/class_utils.py
  function get_model_type (line 77) | def get_model_type(configs):

FILE: cosyvoice/utils/common.py
  function pad_list (line 27) | def pad_list(xs: List[torch.Tensor], pad_value: int):
  function th_accuracy (line 76) | def th_accuracy(pad_outputs: torch.Tensor, pad_targets: torch.Tensor,
  function get_padding (line 98) | def get_padding(kernel_size, dilation=1):
  function init_weights (line 102) | def init_weights(m, mean=0.0, std=0.01):
  function ras_sampling (line 109) | def ras_sampling(weighted_scores, decoded_tokens, sampling, top_p=0.8, t...
  function nucleus_sampling (line 117) | def nucleus_sampling(weighted_scores, top_p=0.8, top_k=25):
  function random_sampling (line 135) | def random_sampling(weighted_scores, decoded_tokens, sampling):
  function fade_in_out (line 140) | def fade_in_out(fade_in_mel, fade_out_mel, window):
  function set_all_random_seed (line 151) | def set_all_random_seed(seed):
  function mask_to_bias (line 158) | def mask_to_bias(mask: torch.Tensor, dtype: torch.dtype) -> torch.Tensor:

FILE: cosyvoice/utils/executor.py
  class Executor (line 26) | class Executor:
    method __init__ (line 28) | def __init__(self, gan: bool = False):
    method train_one_epoc (line 35) | def train_one_epoc(self, model, optimizer, scheduler, train_data_loade...
    method train_one_epoc_gan (line 84) | def train_one_epoc_gan(self, model, optimizer, scheduler, optimizer_d,...
    method cv (line 143) | def cv(self, model, cv_data_loader, writer, info_dict, on_batch_end=Tr...

FILE: cosyvoice/utils/file_utils.py
  function read_lists (line 24) | def read_lists(list_file):
  function read_json_lists (line 32) | def read_json_lists(list_file):
  function load_wav (line 41) | def load_wav(wav, target_sr):

FILE: cosyvoice/utils/frontend_utils.py
  function contains_chinese (line 21) | def contains_chinese(text):
  function replace_corner_mark (line 26) | def replace_corner_mark(text):
  function remove_bracket (line 33) | def remove_bracket(text):
  function spell_out_number (line 42) | def spell_out_number(text: str, inflect_parser):
  function split_paragraph (line 65) | def split_paragraph(text: str, tokenize, lang="zh", token_max_n=80, toke...
  function replace_blank (line 121) | def replace_blank(text: str):
  function is_only_punctuation (line 133) | def is_only_punctuation(text):

FILE: cosyvoice/utils/losses.py
  function tpr_loss (line 5) | def tpr_loss(disc_real_outputs, disc_generated_outputs, tau):
  function mel_loss (line 14) | def mel_loss(real_speech, generated_speech, mel_transforms):

FILE: cosyvoice/utils/mask.py
  function subsequent_mask (line 53) | def subsequent_mask(
  function subsequent_chunk_mask (line 89) | def subsequent_chunk_mask(
  function add_optional_chunk_mask (line 127) | def add_optional_chunk_mask(xs: torch.Tensor,
  function make_pad_mask (line 201) | def make_pad_mask(lengths: torch.Tensor, max_len: int = 0) -> torch.Tensor:

FILE: cosyvoice/utils/scheduler.py
  class WarmupLR (line 27) | class WarmupLR(_LRScheduler):
    method __init__ (line 44) | def __init__(
    method __repr__ (line 56) | def __repr__(self):
    method get_lr (line 59) | def get_lr(self):
    method set_step (line 70) | def set_step(self, step: int):
  class WarmupPolicy (line 74) | class WarmupPolicy(_LRScheduler):
    method __init__ (line 84) | def __init__(self,
    method get_lr (line 110) | def get_lr(self):
    method _get_warmup_lr (line 128) | def _get_warmup_lr(self, step):
    method _get_lr (line 132) | def _get_lr(self, step):
  class SquareRootConstantPolicy (line 137) | class SquareRootConstantPolicy(_LRScheduler):
    method __init__ (line 147) | def __init__(self,
    method get_lr (line 175) | def get_lr(self):
    method _get_lr (line 193) | def _get_lr(self, step):
  class WarmupHoldPolicy (line 198) | class WarmupHoldPolicy(WarmupPolicy):
    method __init__ (line 212) | def __init__(
    method get_lr (line 257) | def get_lr(self):
  class WarmupAnnealHoldPolicy (line 282) | class WarmupAnnealHoldPolicy(_LRScheduler):
    method __init__ (line 295) | def __init__(
    method get_lr (line 340) | def get_lr(self):
    method _get_warmup_lr (line 365) | def _get_warmup_lr(self, step):
    method _get_constant_lr (line 369) | def _get_constant_lr(self, step):
    method _get_lr (line 372) | def _get_lr(self, step):
  function _squareroot_annealing (line 377) | def _squareroot_annealing(initial_lr, step, max_steps, min_lr):
  function _square_annealing (line 384) | def _square_annealing(initial_lr, step, max_steps, min_lr):
  function _cosine_annealing (line 391) | def _cosine_annealing(initial_lr, step, max_steps, min_lr):
  function _linear_warmup_with_cosine_annealing (line 397) | def _linear_warmup_with_cosine_annealing(max_lr, warmup_steps, step,
  function _poly_decay (line 421) | def _poly_decay(initial_lr, step, decay_steps, power, min_lr, cycle):
  function _noam_hold_annealing (line 433) | def _noam_hold_annealing(initial_lr, step, warmup_steps, hold_steps,
  class SquareAnnealing (line 444) | class SquareAnnealing(WarmupPolicy):
    method __init__ (line 446) | def __init__(self,
    method _get_lr (line 459) | def _get_lr(self, step):
  class SquareRootAnnealing (line 471) | class SquareRootAnnealing(WarmupPolicy):
    method __init__ (line 473) | def __init__(self,
    method _get_lr (line 486) | def _get_lr(self, step):
  class CosineAnnealing (line 497) | class CosineAnnealing(WarmupAnnealHoldPolicy):
    method __init__ (line 499) | def __init__(self,
    method _get_lr (line 512) | def _get_lr(self, step):
    method _get_warmup_lr (line 532) | def _get_warmup_lr(self, step):
    method _get_constant_lr (line 539) | def _get_constant_lr(self, step):
    method _get_linear_warmup_with_cosine_annealing_lr (line 543) | def _get_linear_warmup_with_cosine_annealing_lr(self, step):
  class NoamAnnealing (line 558) | class NoamAnnealing(_LRScheduler):
    method __init__ (line 560) | def __init__(self,
    method get_lr (line 588) | def get_lr(self):
    method _noam_annealing (line 610) | def _noam_annealing(self, initial_lr, step):
  class NoamHoldAnnealing (line 623) | class NoamHoldAnnealing(WarmupHoldPolicy):
    method __init__ (line 625) | def __init__(self,
    method _get_lr (line 693) | def _get_lr(self, step):
    method set_step (line 715) | def set_step(self, step: int):
  class ConstantLR (line 719) | class ConstantLR(_LRScheduler):
    method __init__ (line 726) | def __init__(
    method get_lr (line 734) | def get_lr(self):
    method set_step (line 737) | def set_step(self, step: int):

FILE: cosyvoice/utils/train_utils.py
  function init_distributed (line 39) | def init_distributed(args):
  function init_dataset_and_dataloader (line 53) | def init_dataset_and_dataloader(args, configs, gan):
  function check_modify_and_save_config (line 72) | def check_modify_and_save_config(args, configs):
  function wrap_cuda_model (line 94) | def wrap_cuda_model(args, model):
  function init_optimizer_and_scheduler (line 111) | def init_optimizer_and_scheduler(args, configs, model, gan):
  function init_summarywriter (line 187) | def init_summarywriter(args):
  function save_model (line 195) | def save_model(model, model_name, info_dict):
  function cosyvoice_join (line 217) | def cosyvoice_join(group_join, info_dict):
  function batch_forward (line 238) | def batch_forward(model, batch, scaler, info_dict):
  function batch_backward (line 259) | def batch_backward(model, scaler, info_dict):
  function update_parameter_and_lr (line 273) | def update_parameter_and_lr(model, optimizer, scheduler, scaler, info_di...
  function log_per_step (line 301) | def log_per_step(writer, info_dict):
  function log_per_save (line 330) | def log_per_save(writer, info_dict):

FILE: third_party/Matcha-TTS/matcha/app.py
  function MATCHA_TTS_LOC (line 33) | def MATCHA_TTS_LOC(x):
  function VOCODER_LOC (line 37) | def VOCODER_LOC(x):
  function load_model (line 66) | def load_model(model_name, vocoder_name):
  function load_model_ui (line 72) | def load_model_ui(model_type, textbox):
  function process_text_gradio (line 102) | def process_text_gradio(text):
  function synthesise_mel (line 108) | def synthesise_mel(text, text_length, n_timesteps, temperature, length_s...
  function multispeaker_example_cacher (line 125) | def multispeaker_example_cacher(text, n_timesteps, mel_temp, length_scal...
  function ljspeech_example_cacher (line 137) | def ljspeech_example_cacher(text, n_timesteps, mel_temp, length_scale, s...
  function main (line 149) | def main():

FILE: third_party/Matcha-TTS/matcha/cli.py
  function plot_spectrogram_to_numpy (line 37) | def plot_spectrogram_to_numpy(spectrogram, filename):
  function process_text (line 48) | def process_text(i: int, text: str, device: torch.device):
  function get_texts (line 62) | def get_texts(args):
  function assert_required_models_available (line 71) | def assert_required_models_available(args):
  function load_hifigan (line 84) | def load_hifigan(checkpoint_path, device):
  function load_vocoder (line 93) | def load_vocoder(vocoder_name, checkpoint_path, device):
  function load_matcha (line 108) | def load_matcha(model_name, checkpoint_path, device):
  function to_waveform (line 117) | def to_waveform(mel, vocoder, denoiser=None):
  function save_to_folder (line 125) | def save_to_folder(filename: str, output: dict, folder: str):
  function validate_args (line 134) | def validate_args(args):
  function validate_args_for_multispeaker_model (line 163) | def validate_args_for_multispeaker_model(args):
  function validate_args_for_single_speaker_model (line 188) | def validate_args_for_single_speaker_model(args):
  function cli (line 208) | def cli():
  class BatchedSynthesisDataset (line 292) | class BatchedSynthesisDataset(torch.utils.data.Dataset):
    method __init__ (line 293) | def __init__(self, processed_texts):
    method __len__ (line 296) | def __len__(self):
    method __getitem__ (line 299) | def __getitem__(self, idx):
  function batched_collate_fn (line 303) | def batched_collate_fn(batch):
  function batched_synthesis (line 316) | def batched_synthesis(args, device, model, vocoder, denoiser, texts, spk):
  function unbatched_synthesis (line 358) | def unbatched_synthesis(args, device, model, vocoder, denoiser, texts, s...
  function print_config (line 397) | def print_config(args):
  function get_device (line 407) | def get_device(args):

FILE: third_party/Matcha-TTS/matcha/data/text_mel_datamodule.py
  function parse_filelist (line 15) | def parse_filelist(filelist_path, split_char="|"):
  class TextMelDataModule (line 21) | class TextMelDataModule(LightningDataModule):
    method __init__ (line 22) | def __init__(  # pylint: disable=unused-argument
    method setup (line 49) | def setup(self, stage: Optional[str] = None):  # pylint: disable=unuse...
    method train_dataloader (line 88) | def train_dataloader(self):
    method val_dataloader (line 98) | def val_dataloader(self):
    method teardown (line 108) | def teardown(self, stage: Optional[str] = None):
    method state_dict (line 112) | def state_dict(self):  # pylint: disable=no-self-use
    method load_state_dict (line 116) | def load_state_dict(self, state_dict: Dict[str, Any]):
  class TextMelDataset (line 121) | class TextMelDataset(torch.utils.data.Dataset):
    method __init__ (line 122) | def __init__(
    method get_datapoint (line 156) | def get_datapoint(self, filepath_and_text):
    method get_mel (line 172) | def get_mel(self, filepath):
    method get_text (line 189) | def get_text(self, text, add_blank=True):
    method __getitem__ (line 196) | def __getitem__(self, index):
    method __len__ (line 200) | def __len__(self):
  class TextMelBatchCollate (line 204) | class TextMelBatchCollate:
    method __init__ (line 205) | def __init__(self, n_spks):
    method __call__ (line 208) | def __call__(self, batch):

FILE: third_party/Matcha-TTS/matcha/hifigan/denoiser.py
  class Denoiser (line 7) | class Denoiser(torch.nn.Module):
    method __init__ (line 10) | def __init__(self, vocoder, filter_length=1024, n_overlap=4, win_lengt...
    method forward (line 59) | def forward(self, audio, strength=0.0005):

FILE: third_party/Matcha-TTS/matcha/hifigan/env.py
  class AttrDict (line 7) | class AttrDict(dict):
    method __init__ (line 8) | def __init__(self, *args, **kwargs):
  function build_env (line 13) | def build_env(config, config_name, path):

FILE: third_party/Matcha-TTS/matcha/hifigan/meldataset.py
  function load_wav (line 17) | def load_wav(full_path):
  function dynamic_range_compression (line 22) | def dynamic_range_compression(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression (line 26) | def dynamic_range_decompression(x, C=1):
  function dynamic_range_compression_torch (line 30) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression_torch (line 34) | def dynamic_range_decompression_torch(x, C=1):
  function spectral_normalize_torch (line 38) | def spectral_normalize_torch(magnitudes):
  function spectral_de_normalize_torch (line 43) | def spectral_de_normalize_torch(magnitudes):
  function mel_spectrogram (line 52) | def mel_spectrogram(y, n_fft, num_mels, sampling_rate, hop_size, win_siz...
  function get_dataset_filelist (line 92) | def get_dataset_filelist(a):
  class MelDataset (line 105) | class MelDataset(torch.utils.data.Dataset):
    method __init__ (line 106) | def __init__(
    method __getitem__ (line 146) | def __getitem__(self, index):
    method __len__ (line 216) | def __len__(self):

FILE: third_party/Matcha-TTS/matcha/hifigan/models.py
  class ResBlock1 (line 14) | class ResBlock1(torch.nn.Module):
    method __init__ (line 15) | def __init__(self, h, channels, kernel_size=3, dilation=(1, 3, 5)):
    method forward (line 90) | def forward(self, x):
    method remove_weight_norm (line 99) | def remove_weight_norm(self):
  class ResBlock2 (line 106) | class ResBlock2(torch.nn.Module):
    method __init__ (line 107) | def __init__(self, h, channels, kernel_size=3, dilation=(1, 3)):
    method forward (line 136) | def forward(self, x):
    method remove_weight_norm (line 143) | def remove_weight_norm(self):
  class Generator (line 148) | class Generator(torch.nn.Module):
    method __init__ (line 149) | def __init__(self, h):
    method forward (line 181) | def forward(self, x):
    method remove_weight_norm (line 199) | def remove_weight_norm(self):
  class DiscriminatorP (line 209) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 210) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=...
    method forward (line 225) | def forward(self, x):
  class MultiPeriodDiscriminator (line 247) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 248) | def __init__(self):
    method forward (line 260) | def forward(self, y, y_hat):
  class DiscriminatorS (line 276) | class DiscriminatorS(torch.nn.Module):
    method __init__ (line 277) | def __init__(self, use_spectral_norm=False):
    method forward (line 293) | def forward(self, x):
  class MultiScaleDiscriminator (line 306) | class MultiScaleDiscriminator(torch.nn.Module):
    method __init__ (line 307) | def __init__(self):
    method forward (line 318) | def forward(self, y, y_hat):
  function feature_loss (line 337) | def feature_loss(fmap_r, fmap_g):
  function discriminator_loss (line 346) | def discriminator_loss(disc_real_outputs, disc_generated_outputs):
  function generator_loss (line 360) | def generator_loss(disc_outputs):

FILE: third_party/Matcha-TTS/matcha/hifigan/xutils.py
  function plot_spectrogram (line 14) | def plot_spectrogram(spectrogram):
  function init_weights (line 25) | def init_weights(m, mean=0.0, std=0.01):
  function apply_weight_norm (line 31) | def apply_weight_norm(m):
  function get_padding (line 37) | def get_padding(kernel_size, dilation=1):
  function load_checkpoint (line 41) | def load_checkpoint(filepath, device):
  function save_checkpoint (line 49) | def save_checkpoint(filepath, obj):
  function scan_checkpoint (line 55) | def scan_checkpoint(cp_dir, prefix):

FILE: third_party/Matcha-TTS/matcha/models/baselightningmodule.py
  class BaseLightningClass (line 19) | class BaseLightningClass(LightningModule, ABC):
    method update_data_statistics (line 20) | def update_data_statistics(self, data_statistics):
    method configure_optimizers (line 30) | def configure_optimizers(self) -> Any:
    method get_losses (line 56) | def get_losses(self, batch):
    method on_load_checkpoint (line 75) | def on_load_checkpoint(self, checkpoint: Dict[str, Any]) -> None:
    method training_step (line 78) | def training_step(self, batch: Any, batch_idx: int):
    method validation_step (line 127) | def validation_step(self, batch: Any, batch_idx: int):
    method on_validation_end (line 167) | def on_validation_end(self) -> None:
    method on_before_optimizer_step (line 208) | def on_before_optimizer_step(self, optimizer):

FILE: third_party/Matcha-TTS/matcha/models/components/decoder.py
  class SinusoidalPosEmb (line 14) | class SinusoidalPosEmb(torch.nn.Module):
    method __init__ (line 15) | def __init__(self, dim):
    method forward (line 20) | def forward(self, x, scale=1000):
  class Block1D (line 32) | class Block1D(torch.nn.Module):
    method __init__ (line 33) | def __init__(self, dim, dim_out, groups=8):
    method forward (line 41) | def forward(self, x, mask):
  class ResnetBlock1D (line 46) | class ResnetBlock1D(torch.nn.Module):
    method __init__ (line 47) | def __init__(self, dim, dim_out, time_emb_dim, groups=8):
    method forward (line 56) | def forward(self, x, mask, time_emb):
  class Downsample1D (line 64) | class Downsample1D(nn.Module):
    method __init__ (line 65) | def __init__(self, dim):
    method forward (line 69) | def forward(self, x):
  class TimestepEmbedding (line 73) | class TimestepEmbedding(nn.Module):
    method __init__ (line 74) | def __init__(
    method forward (line 105) | def forward(self, sample, condition=None):
  class Upsample1D (line 120) | class Upsample1D(nn.Module):
    method __init__ (line 134) | def __init__(self, channels, use_conv=False, use_conv_transpose=True, ...
    method forward (line 148) | def forward(self, inputs):
  class ConformerWrapper (line 161) | class ConformerWrapper(ConformerBlock):
    method __init__ (line 162) | def __init__(  # pylint: disable=useless-super-delegation
    method forward (line 189) | def forward(
  class Decoder (line 200) | class Decoder(nn.Module):
    method __init__ (line 201) | def __init__(
    method get_block (line 319) | def get_block(block_type, dim, attention_head_dim, num_heads, dropout,...
    method initialize_weights (line 345) | def initialize_weights(self):
    method forward (line 363) | def forward(self, x, mask, mu, t, spks=None, cond=None):

FILE: third_party/Matcha-TTS/matcha/models/components/flow_matching.py
  class BASECFM (line 12) | class BASECFM(torch.nn.Module, ABC):
    method __init__ (line 13) | def __init__(
    method forward (line 33) | def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, c...
    method solve_euler (line 55) | def solve_euler(self, x, t_span, mu, mask, spks, cond):
    method compute_loss (line 87) | def compute_loss(self, x1, mask, mu, spks=None, cond=None):
  class CFM (line 121) | class CFM(BASECFM):
    method __init__ (line 122) | def __init__(self, in_channels, out_channel, cfm_params, decoder_param...

FILE: third_party/Matcha-TTS/matcha/models/components/text_encoder.py
  class LayerNorm (line 15) | class LayerNorm(nn.Module):
    method __init__ (line 16) | def __init__(self, channels, eps=1e-4):
    method forward (line 24) | def forward(self, x):
  class ConvReluNorm (line 36) | class ConvReluNorm(nn.Module):
    method __init__ (line 37) | def __init__(self, in_channels, hidden_channels, out_channels, kernel_...
    method forward (line 60) | def forward(self, x, x_mask):
  class DurationPredictor (line 70) | class DurationPredictor(nn.Module):
    method __init__ (line 71) | def __init__(self, in_channels, filter_channels, kernel_size, p_dropout):
    method forward (line 84) | def forward(self, x, x_mask):
  class RotaryPositionalEmbeddings (line 97) | class RotaryPositionalEmbeddings(nn.Module):
    method __init__ (line 107) | def __init__(self, d: int, base: int = 10_000):
    method _build_cache (line 119) | def _build_cache(self, x: torch.Tensor):
    method _neg_half (line 147) | def _neg_half(self, x: torch.Tensor):
    method forward (line 154) | def forward(self, x: torch.Tensor):
  class MultiHeadAttention (line 175) | class MultiHeadAttention(nn.Module):
    method __init__ (line 176) | def __init__(
    method forward (line 216) | def forward(self, x, c, attn_mask=None):
    method attention (line 226) | def attention(self, query, key, value, mask=None):
    method _attention_bias_proximal (line 249) | def _attention_bias_proximal(length):
  class FFN (line 255) | class FFN(nn.Module):
    method __init__ (line 256) | def __init__(self, in_channels, out_channels, filter_channels, kernel_...
    method forward (line 268) | def forward(self, x, x_mask):
  class Encoder (line 276) | class Encoder(nn.Module):
    method __init__ (line 277) | def __init__(
    method forward (line 314) | def forward(self, x, x_mask):
  class TextEncoder (line 328) | class TextEncoder(nn.Module):
    method __init__ (line 329) | def __init__(
    method forward (line 378) | def forward(self, x, x_lengths, spks=None):

FILE: third_party/Matcha-TTS/matcha/models/components/transformer.py
  class SnakeBeta (line 17) | class SnakeBeta(nn.Module):
    method __init__ (line 35) | def __init__(self, in_features, out_features, alpha=1.0, alpha_trainab...
    method forward (line 64) | def forward(self, x):
  class FeedForward (line 83) | class FeedForward(nn.Module):
    method __init__ (line 96) | def __init__(
    method forward (line 131) | def forward(self, hidden_states):
  class BasicTransformerBlock (line 138) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 159) | def __init__(
    method set_chunk_feed_forward (line 238) | def set_chunk_feed_forward(self, chunk_size: Optional[int], dim: int):
    method forward (line 243) | def forward(

FILE: third_party/Matcha-TTS/matcha/models/matcha_tts.py
  class MatchaTTS (line 23) | class MatchaTTS(BaseLightningClass):  # 🍵
    method __init__ (line 24) | def __init__(
    method synthesise (line 74) | def synthesise(self, x, x_lengths, n_timesteps, temperature=1.0, spks=...
    method forward (line 150) | def forward(self, x, x_lengths, y, y_lengths, spks=None, out_size=None...

FILE: third_party/Matcha-TTS/matcha/onnx/export.py
  class MatchaWithVocoder (line 22) | class MatchaWithVocoder(LightningModule):
    method __init__ (line 23) | def __init__(self, matcha, vocoder):
    method forward (line 28) | def forward(self, x, x_lengths, scales, spks=None):
  function get_exportable_module (line 35) | def get_exportable_module(matcha, vocoder, n_timesteps):
  function get_inputs (line 63) | def get_inputs(is_multi_speaker):
  function main (line 91) | def main():

FILE: third_party/Matcha-TTS/matcha/onnx/infer.py
  function validate_args (line 15) | def validate_args(args):
  function write_wavs (line 24) | def write_wavs(model, inputs, output_dir, external_vocoder=None):
  function write_mels (line 66) | def write_mels(model, inputs, output_dir):
  function main (line 85) | def main():

FILE: third_party/Matcha-TTS/matcha/text/__init__.py
  function text_to_sequence (line 10) | def text_to_sequence(text, cleaner_names):
  function cleaned_text_to_sequence (line 27) | def cleaned_text_to_sequence(cleaned_text):
  function sequence_to_text (line 38) | def sequence_to_text(sequence):
  function _clean_text (line 47) | def _clean_text(text, cleaner_names):

FILE: third_party/Matcha-TTS/matcha/text/cleaners.py
  function expand_abbreviations (line 66) | def expand_abbreviations(text):
  function lowercase (line 72) | def lowercase(text):
  function collapse_whitespace (line 76) | def collapse_whitespace(text):
  function convert_to_ascii (line 80) | def convert_to_ascii(text):
  function basic_cleaners (line 84) | def basic_cleaners(text):
  function transliteration_cleaners (line 91) | def transliteration_cleaners(text):
  function english_cleaners2 (line 99) | def english_cleaners2(text):
  function english_cleaners_piper (line 109) | def english_cleaners_piper(text):

FILE: third_party/Matcha-TTS/matcha/text/numbers.py
  function _remove_commas (line 16) | def _remove_commas(m):
  function _expand_decimal_point (line 20) | def _expand_decimal_point(m):
  function _expand_dollars (line 24) | def _expand_dollars(m):
  function _expand_ordinal (line 45) | def _expand_ordinal(m):
  function _expand_number (line 49) | def _expand_number(m):
  function normalize_numbers (line 64) | def normalize_numbers(text):

FILE: third_party/Matcha-TTS/matcha/train.py
  function train (line 35) | def train(cfg: DictConfig) -> Tuple[Dict[str, Any], Dict[str, Any]]:
  function main (line 101) | def main(cfg: DictConfig) -> Optional[float]:

FILE: third_party/Matcha-TTS/matcha/utils/audio.py
  function load_wav (line 10) | def load_wav(full_path):
  function dynamic_range_compression (line 15) | def dynamic_range_compression(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression (line 19) | def dynamic_range_decompression(x, C=1):
  function dynamic_range_compression_torch (line 23) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression_torch (line 27) | def dynamic_range_decompression_torch(x, C=1):
  function spectral_normalize_torch (line 31) | def spectral_normalize_torch(magnitudes):
  function spectral_de_normalize_torch (line 36) | def spectral_de_normalize_torch(magnitudes):
  function mel_spectrogram (line 45) | def mel_spectrogram(y, n_fft, num_mels, sampling_rate, hop_size, win_siz...

FILE: third_party/Matcha-TTS/matcha/utils/generate_data_statistics.py
  function compute_data_statistics (line 25) | def compute_data_statistics(data_loader: torch.utils.data.DataLoader, ou...
  function main (line 50) | def main():

FILE: third_party/Matcha-TTS/matcha/utils/instantiators.py
  function instantiate_callbacks (line 13) | def instantiate_callbacks(callbacks_cfg: DictConfig) -> List[Callback]:
  function instantiate_loggers (line 36) | def instantiate_loggers(logger_cfg: DictConfig) -> List[Logger]:

FILE: third_party/Matcha-TTS/matcha/utils/logging_utils.py
  function log_hyperparameters (line 12) | def log_hyperparameters(object_dict: Dict[str, Any]) -> None:

FILE: third_party/Matcha-TTS/matcha/utils/model.py
  function sequence_mask (line 7) | def sequence_mask(length, max_length=None):
  function fix_len_compatibility (line 14) | def fix_len_compatibility(length, num_downsamplings_in_unet=2):
  function convert_pad_shape (line 23) | def convert_pad_shape(pad_shape):
  function generate_path (line 29) | def generate_path(duration, mask):
  function duration_loss (line 44) | def duration_loss(logw, logw_, lengths):
  function normalize (line 49) | def normalize(data, mu, std):
  function denormalize (line 71) | def denormalize(data, mu, std):

FILE: third_party/Matcha-TTS/matcha/utils/monotonic_align/__init__.py
  function maximum_path (line 7) | def maximum_path(value, mask):

FILE: third_party/Matcha-TTS/matcha/utils/pylogger.py
  function get_pylogger (line 6) | def get_pylogger(name: str = __name__) -> logging.Logger:

FILE: third_party/Matcha-TTS/matcha/utils/rich_utils.py
  function print_config_tree (line 18) | def print_config_tree(
  function enforce_tags (line 80) | def enforce_tags(cfg: DictConfig, save_to_file: bool = False) -> None:

FILE: third_party/Matcha-TTS/matcha/utils/utils.py
  function extras (line 20) | def extras(cfg: DictConfig) -> None:
  function task_wrapper (line 51) | def task_wrapper(task_func: Callable) -> Callable:
  function get_metric_value (line 106) | def get_metric_value(metric_dict: Dict[str, Any], metric_name: str) -> f...
  function intersperse (line 130) | def intersperse(lst, item):
  function save_figure_to_numpy (line 137) | def save_figure_to_numpy(fig):
  function plot_tensor (line 143) | def plot_tensor(tensor):
  function save_plot (line 155) | def save_plot(tensor, savepath):
  function to_numpy (line 166) | def to_numpy(tensor):
  function get_user_data_dir (line 177) | def get_user_data_dir(appname="matcha_tts"):
  function assert_model_downloaded (line 208) | def assert_model_downloaded(checkpoint_path, url, use_wget=True):