SYMBOL INDEX (1694 symbols across 136 files)

FILE: GPT_SoVITS/AR/data/bucket_sampler.py
  class DistributedBucketSampler (line 20) | class DistributedBucketSampler(Sampler[T_co]):
    method __init__ (line 29) | def __init__(
    method _get_sample_lengths (line 76) | def _get_sample_lengths(self):
    method make_buckets (line 83) | def make_buckets(self, bucket_width: float = 2.0):
    method __iter__ (line 98) | def __iter__(self) -> Iterator[T_co]:
    method __len__ (line 137) | def __len__(self) -> int:
    method set_epoch (line 140) | def set_epoch(self, epoch: int) -> None:

FILE: GPT_SoVITS/AR/data/data_module.py
  class Text2SemanticDataModule (line 10) | class Text2SemanticDataModule(LightningDataModule):
    method __init__ (line 11) | def __init__(
    method prepare_data (line 27) | def prepare_data(self):
    method setup (line 30) | def setup(self, stage=None, output_logs=False):
    method train_dataloader (line 45) | def train_dataloader(self):
    method val_dataloader (line 63) | def val_dataloader(self):
    method test_dataloader (line 75) | def test_dataloader(self):

FILE: GPT_SoVITS/AR/data/dataset.py
  function batch_sequences (line 21) | def batch_sequences(sequences: List[np.array], axis: int = 0, pad_value:...
  class Text2SemanticDataset (line 40) | class Text2SemanticDataset(Dataset):
    method __init__ (line 43) | def __init__(
    method init_batch (line 115) | def init_batch(self):
    method __get_item_names__ (line 208) | def __get_item_names__(self) -> List[str]:
    method __len__ (line 211) | def __len__(self) -> int:
    method __getitem__ (line 214) | def __getitem__(self, idx: int) -> Dict:
    method get_sample_length (line 241) | def get_sample_length(self, idx: int):
    method collate (line 246) | def collate(self, examples: List[Dict]) -> Dict:

FILE: GPT_SoVITS/AR/models/t2s_lightning_module.py
  class Text2SemanticLightningModule (line 18) | class Text2SemanticLightningModule(LightningModule):
    method __init__ (line 19) | def __init__(self, config, output_dir, is_train=True):
    method training_step (line 42) | def training_step(self, batch: Dict, batch_idx: int):
    method validation_step (line 83) | def validation_step(self, batch: Dict, batch_idx: int):
    method configure_optimizers (line 120) | def configure_optimizers(self):

FILE: GPT_SoVITS/AR/models/t2s_lightning_module_onnx.py
  class Text2SemanticLightningModule (line 18) | class Text2SemanticLightningModule(LightningModule):
    method __init__ (line 19) | def __init__(self, config, output_dir, is_train=True):
    method training_step (line 41) | def training_step(self, batch: Dict, batch_idx: int):
    method validation_step (line 81) | def validation_step(self, batch: Dict, batch_idx: int):
    method configure_optimizers (line 84) | def configure_optimizers(self):

FILE: GPT_SoVITS/AR/models/t2s_model.py
  function scaled_dot_product_attention (line 39) | def scaled_dot_product_attention(
  class T2SMLP (line 74) | class T2SMLP:
    method __init__ (line 75) | def __init__(self, w1, b1, w2, b2):
    method forward (line 81) | def forward(self, x):
  class T2SBlock (line 88) | class T2SBlock:
    method __init__ (line 89) | def __init__(
    method to_mask (line 122) | def to_mask(
    method process_prompt (line 135) | def process_prompt(
    method decode_next_token (line 176) | def decode_next_token(
  class T2STransformer (line 225) | class T2STransformer:
    method __init__ (line 226) | def __init__(self, num_blocks: int, blocks: List[T2SBlock]):
    method process_prompt (line 230) | def process_prompt(
    method decode_next_token (line 245) | def decode_next_token(
  class Text2SemanticDecoder (line 260) | class Text2SemanticDecoder(nn.Module):
    method __init__ (line 261) | def __init__(self, config, norm_first=False, top_k=3):
    method make_input_data (line 355) | def make_input_data(self, x, x_lens, y, y_lens, bert_feature):
    method forward (line 408) | def forward(self, x, x_lens, y, y_lens, bert_feature):
    method forward_old (line 450) | def forward_old(self, x, x_lens, y, y_lens, bert_feature):
    method infer (line 513) | def infer(
    method pad_y_eos (line 578) | def pad_y_eos(self, y, y_mask_int, eos_id):
    method infer_panel_batch_infer (line 583) | def infer_panel_batch_infer(
    method infer_panel_naive_batched (line 783) | def infer_panel_naive_batched(
    method infer_panel_naive (line 816) | def infer_panel_naive(
    method infer_panel (line 966) | def infer_panel(

FILE: GPT_SoVITS/AR/models/t2s_model_onnx.py
  function logits_to_probs (line 26) | def logits_to_probs(
  function multinomial_sample_one_no_sync (line 74) | def multinomial_sample_one_no_sync(
  function sample (line 81) | def sample(
  class OnnxEncoder (line 95) | class OnnxEncoder(nn.Module):
    method __init__ (line 96) | def __init__(self, ar_text_embedding, bert_proj, ar_text_position):
    method forward (line 102) | def forward(self, x, bert_feature):
  class T2SFirstStageDecoder (line 108) | class T2SFirstStageDecoder(nn.Module):
    method __init__ (line 109) | def __init__(
    method forward (line 132) | def forward(self, x, prompt):
  class T2SStageDecoder (line 189) | class T2SStageDecoder(nn.Module):
    method __init__ (line 190) | def __init__(
    method forward (line 213) | def forward(self, y, k, v, y_emb, x_example):
  class Text2SemanticDecoder (line 249) | class Text2SemanticDecoder(nn.Module):
    method __init__ (line 250) | def __init__(self, config, norm_first=False, top_k=3):
    method init_onnx (line 292) | def init_onnx(self):
    method forward (line 317) | def forward(self, x, prompts, bert_feature):
    method infer (line 337) | def infer(self, x, prompts, bert_feature):

FILE: GPT_SoVITS/AR/models/utils.py
  function sequence_mask (line 9) | def sequence_mask(length, max_length=None):
  function make_pad_mask (line 16) | def make_pad_mask(lengths: torch.Tensor, max_len: int = 0) -> torch.Tensor:
  function make_pad_mask_left (line 44) | def make_pad_mask_left(lengths: torch.Tensor, max_len: int = 0) -> torch...
  function top_k_top_p_filtering (line 78) | def top_k_top_p_filtering(
  function topk_sampling (line 119) | def topk_sampling(logits, top_k=10, top_p=1.0, temperature=1.0):
  function multinomial_sample_one_no_sync (line 140) | def multinomial_sample_one_no_sync(
  function logits_to_probs (line 147) | def logits_to_probs(
  function sample (line 192) | def sample(
  function dpo_loss (line 202) | def dpo_loss(
  function get_batch_logps (line 225) | def get_batch_logps(
  function make_reject_y (line 244) | def make_reject_y(y_o, y_lens):

FILE: GPT_SoVITS/AR/modules/activation.py
  class MultiheadAttention (line 17) | class MultiheadAttention(Module):
    method __init__ (line 78) | def __init__(
    method _reset_parameters (line 180) | def _reset_parameters(self):
    method __setstate__ (line 197) | def __setstate__(self, state):
    method forward (line 204) | def forward(

FILE: GPT_SoVITS/AR/modules/activation_onnx.py
  class MultiheadAttention (line 14) | class MultiheadAttention(Module):
    method __init__ (line 19) | def __init__(
    method _reset_parameters (line 130) | def _reset_parameters(self):
    method __setstate__ (line 147) | def __setstate__(self, state):
    method forward (line 154) | def forward(

FILE: GPT_SoVITS/AR/modules/embedding.py
  class TokenEmbedding (line 8) | class TokenEmbedding(nn.Module):
    method __init__ (line 9) | def __init__(
    method weight (line 24) | def weight(self) -> torch.Tensor:
    method embedding (line 27) | def embedding(self, index: int) -> torch.Tensor:
    method forward (line 30) | def forward(self, x: torch.Tensor):
  class SinePositionalEmbedding (line 36) | class SinePositionalEmbedding(nn.Module):
    method __init__ (line 37) | def __init__(
    method extend_pe (line 54) | def extend_pe(self, x):
    method forward (line 74) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: GPT_SoVITS/AR/modules/embedding_onnx.py
  class TokenEmbedding (line 8) | class TokenEmbedding(nn.Module):
    method __init__ (line 9) | def __init__(
    method weight (line 24) | def weight(self) -> torch.Tensor:
    method embedding (line 27) | def embedding(self, index: int) -> torch.Tensor:
    method forward (line 30) | def forward(self, x: torch.Tensor):
  class SinePositionalEmbedding (line 36) | class SinePositionalEmbedding(nn.Module):
    method __init__ (line 37) | def __init__(
    method extend_pe (line 52) | def extend_pe(self, x):
    method forward (line 59) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: GPT_SoVITS/AR/modules/lr_schedulers.py
  class WarmupCosineLRSchedule (line 11) | class WarmupCosineLRSchedule(torch.optim.lr_scheduler._LRScheduler):
    method __init__ (line 16) | def __init__(
    method set_lr (line 38) | def set_lr(self, lr):
    method step (line 44) | def step(self):

FILE: GPT_SoVITS/AR/modules/optim.py
  class BatchedOptimizer (line 26) | class BatchedOptimizer(Optimizer):
    method __init__ (line 37) | def __init__(self, params, defaults):
    method batched_params (line 41) | def batched_params(self, param_group, group_params_names):
  class ScaledAdam (line 113) | class ScaledAdam(BatchedOptimizer):
    method __init__ (line 156) | def __init__(
    method __setstate__ (line 193) | def __setstate__(self, state):
    method step (line 197) | def step(self, closure=None):
    method _init_state (line 236) | def _init_state(self, group: dict, p: Tensor, state: dict):
    method _get_clipping_scale (line 279) | def _get_clipping_scale(self, group: dict, tuples: List[Tuple[Tensor, ...
    method _show_gradient_dominating_parameter (line 363) | def _show_gradient_dominating_parameter(self, tuples: List[Tuple[Tenso...
    method _step_one_batch (line 426) | def _step_one_batch(self, group: dict, p: Tensor, state: dict, clippin...
    method _size_update (line 470) | def _size_update(
    method _step (line 532) | def _step(self, group: dict, p: Tensor, state: dict):
    method _step_scalar (line 571) | def _step_scalar(self, group: dict, p: Tensor, state: dict):

FILE: GPT_SoVITS/AR/modules/patched_mha_with_cache.py
  function multi_head_attention_forward_patched (line 13) | def multi_head_attention_forward_patched(

FILE: GPT_SoVITS/AR/modules/patched_mha_with_cache_onnx.py
  function multi_head_attention_forward_patched (line 7) | def multi_head_attention_forward_patched(

FILE: GPT_SoVITS/AR/modules/scaling.py
  class DoubleSwishFunction (line 25) | class DoubleSwishFunction(torch.autograd.Function):
    method forward (line 42) | def forward(ctx, x: Tensor) -> Tensor:
    method backward (line 73) | def backward(ctx, y_grad: Tensor) -> Tensor:
  class DoubleSwish (line 82) | class DoubleSwish(torch.nn.Module):
    method forward (line 83) | def forward(self, x: Tensor) -> Tensor:
  class ActivationBalancerFunction (line 92) | class ActivationBalancerFunction(torch.autograd.Function):
    method forward (line 94) | def forward(
    method backward (line 112) | def backward(ctx, x_grad: Tensor) -> Tuple[Tensor, None, None, None]:
  function _compute_scale_factor (line 133) | def _compute_scale_factor(
  function _compute_sign_factor (line 158) | def _compute_sign_factor(
  class ActivationBalancer (line 191) | class ActivationBalancer(torch.nn.Module):
    method __init__ (line 231) | def __init__(
    method forward (line 262) | def forward(self, x: Tensor) -> Tensor:
  function BalancedDoubleSwish (line 312) | def BalancedDoubleSwish(d_model, channel_dim=-1, max_abs=10.0, min_prob=...

FILE: GPT_SoVITS/AR/modules/transformer.py
  class LayerNorm (line 22) | class LayerNorm(nn.Module):
    method __init__ (line 28) | def __init__(
    method reset_parameters (line 53) | def reset_parameters(self) -> None:
    method forward (line 58) | def forward(self, input: Tensor, embedding: Any = None) -> Tensor:
    method extra_repr (line 75) | def extra_repr(self) -> str:
  class IdentityNorm (line 79) | class IdentityNorm(nn.Module):
    method __init__ (line 80) | def __init__(
    method forward (line 89) | def forward(self, input: Tensor, embedding: Any = None) -> Tensor:
  class TransformerEncoder (line 97) | class TransformerEncoder(nn.Module):
    method __init__ (line 118) | def __init__(self, encoder_layer, num_layers, norm=None):
    method forward (line 124) | def forward(
  class TransformerEncoderLayer (line 175) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 178) | def __init__(
    method __setstate__ (line 252) | def __setstate__(self, state):
    method forward (line 257) | def forward(
    method _sa_block (line 305) | def _sa_block(
    method _ff_block (line 328) | def _ff_block(self, x: Tensor) -> Tensor:
  class AdaptiveLayerNorm (line 333) | class AdaptiveLayerNorm(nn.Module):
    method __init__ (line 336) | def __init__(self, d_model, norm) -> None:
    method forward (line 343) | def forward(self, input: Tensor, embedding: Tensor = None) -> Tensor:
  function _get_clones (line 361) | def _get_clones(module, N):

FILE: GPT_SoVITS/AR/modules/transformer_onnx.py
  class LayerNorm (line 22) | class LayerNorm(nn.Module):
    method __init__ (line 28) | def __init__(
    method reset_parameters (line 53) | def reset_parameters(self) -> None:
    method forward (line 58) | def forward(self, input: Tensor, embedding: Any = None) -> Tensor:
    method extra_repr (line 75) | def extra_repr(self) -> str:
  class IdentityNorm (line 79) | class IdentityNorm(nn.Module):
    method __init__ (line 80) | def __init__(
    method forward (line 89) | def forward(self, input: Tensor, embedding: Any = None) -> Tensor:
  class TransformerEncoder (line 97) | class TransformerEncoder(nn.Module):
    method __init__ (line 118) | def __init__(self, encoder_layer, num_layers, norm=None):
    method forward (line 124) | def forward(
  class TransformerEncoderLayer (line 147) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 150) | def __init__(
    method __setstate__ (line 207) | def __setstate__(self, state):
    method forward (line 212) | def forward(
    method _sa_block (line 229) | def _sa_block(
    method _ff_block (line 247) | def _ff_block(self, x: Tensor) -> Tensor:
  class AdaptiveLayerNorm (line 252) | class AdaptiveLayerNorm(nn.Module):
    method __init__ (line 255) | def __init__(self, d_model, norm) -> None:
    method forward (line 262) | def forward(self, input: Tensor, embedding: Tensor = None) -> Tensor:
  function _get_clones (line 280) | def _get_clones(module, N):

FILE: GPT_SoVITS/AR/text_processing/phonemizer.py
  class GruutPhonemizer (line 15) | class GruutPhonemizer:
    method __init__ (line 16) | def __init__(self, language: str):
    method _normalize_punctuation (line 35) | def _normalize_punctuation(self, text: str) -> str:
    method _convert_punctuation (line 41) | def _convert_punctuation(self, word: Word) -> str:
    method phonemize (line 52) | def phonemize(self, text: str, espeak: bool = False) -> str:
    method transform (line 58) | def transform(self, phonemes):

FILE: GPT_SoVITS/AR/utils/__init__.py
  function str2bool (line 4) | def str2bool(str):
  function get_newest_ckpt (line 8) | def get_newest_ckpt(string_list):
  function check_txt_file (line 28) | def check_txt_file(file_path):

FILE: GPT_SoVITS/AR/utils/initialize.py
  function initialize (line 8) | def initialize(model: torch.nn.Module, init: str):

FILE: GPT_SoVITS/AR/utils/io.py
  function load_yaml_config (line 7) | def load_yaml_config(path):
  function save_config_to_yaml (line 13) | def save_config_to_yaml(config, path):
  function write_args (line 20) | def write_args(args, path):

FILE: GPT_SoVITS/BigVGAN/activations.py
  class Snake (line 9) | class Snake(nn.Module):
    method __init__ (line 26) | def __init__(self, in_features, alpha=1.0, alpha_trainable=True, alpha...
    method forward (line 49) | def forward(self, x):
  class SnakeBeta (line 63) | class SnakeBeta(nn.Module):
    method __init__ (line 81) | def __init__(self, in_features, alpha=1.0, alpha_trainable=True, alpha...
    method forward (line 109) | def forward(self, x):

FILE: GPT_SoVITS/BigVGAN/alias_free_activation/cuda/activation1d.py
  class FusedAntiAliasActivation (line 14) | class FusedAntiAliasActivation(torch.autograd.Function):
    method forward (line 22) | def forward(ctx, inputs, up_ftr, down_ftr, alpha, beta):
    method backward (line 28) | def backward(ctx, output_grads):
  class Activation1d (line 33) | class Activation1d(nn.Module):
    method __init__ (line 34) | def __init__(
    method forward (line 52) | def forward(self, x):

FILE: GPT_SoVITS/BigVGAN/alias_free_activation/cuda/anti_alias_activation.cpp
  function PYBIND11_MODULE (line 21) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: GPT_SoVITS/BigVGAN/alias_free_activation/cuda/load.py
  function load (line 17) | def load():
  function _get_cuda_bare_metal_version (line 66) | def _get_cuda_bare_metal_version(cuda_dir):
  function _create_build_dir (line 77) | def _create_build_dir(buildpath):

FILE: GPT_SoVITS/BigVGAN/alias_free_activation/torch/act.py
  class Activation1d (line 8) | class Activation1d(nn.Module):
    method __init__ (line 9) | def __init__(
    method forward (line 25) | def forward(self, x):

FILE: GPT_SoVITS/BigVGAN/alias_free_activation/torch/filter.py
  function sinc (line 15) | def sinc(x: torch.Tensor):
  function kaiser_sinc_filter1d (line 30) | def kaiser_sinc_filter1d(cutoff, half_width, kernel_size):  # return fil...
  class LowPassFilter1d (line 63) | class LowPassFilter1d(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 92) | def forward(self, x):

FILE: GPT_SoVITS/BigVGAN/alias_free_activation/torch/resample.py
  class UpSample1d (line 10) | class UpSample1d(nn.Module):
    method __init__ (line 11) | def __init__(self, ratio=2, kernel_size=None):
    method forward (line 23) | def forward(self, x):
  class DownSample1d (line 33) | class DownSample1d(nn.Module):
    method __init__ (line 34) | def __init__(self, ratio=2, kernel_size=None):
    method forward (line 45) | def forward(self, x):

FILE: GPT_SoVITS/BigVGAN/bigvgan.py
  function load_hparams_from_json (line 25) | def load_hparams_from_json(path) -> AttrDict:
  class AMPBlock1 (line 31) | class AMPBlock1(torch.nn.Module):
    method __init__ (line 44) | def __init__(
    method forward (line 122) | def forward(self, x):
    method remove_weight_norm (line 133) | def remove_weight_norm(self):
  class AMPBlock2 (line 140) | class AMPBlock2(torch.nn.Module):
    method __init__ (line 153) | def __init__(
    method forward (line 214) | def forward(self, x):
    method remove_weight_norm (line 221) | def remove_weight_norm(self):
  class BigVGAN (line 226) | class BigVGAN(
    method __init__ (line 249) | def __init__(self, h: AttrDict, use_cuda_kernel: bool = False):
    method forward (line 329) | def forward(self, x):
    method remove_weight_norm (line 357) | def remove_weight_norm(self):
    method _save_pretrained (line 372) | def _save_pretrained(self, save_directory: Path) -> None:
    method _from_pretrained (line 383) | def _from_pretrained(

FILE: GPT_SoVITS/BigVGAN/discriminators.py
  class DiscriminatorP (line 21) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 22) | def __init__(
    method forward (line 86) | def forward(self, x: torch.Tensor) -> Tuple[torch.Tensor, List[torch.T...
  class MultiPeriodDiscriminator (line 108) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 109) | def __init__(self, h: AttrDict):
    method forward (line 117) | def forward(
  class DiscriminatorR (line 140) | class DiscriminatorR(nn.Module):
    method __init__ (line 141) | def __init__(self, cfg: AttrDict, resolution: List[List[int]]):
    method forward (line 199) | def forward(self, x: torch.Tensor) -> Tuple[torch.Tensor, List[torch.T...
    method spectrogram (line 214) | def spectrogram(self, x: torch.Tensor) -> torch.Tensor:
  class MultiResolutionDiscriminator (line 236) | class MultiResolutionDiscriminator(nn.Module):
    method __init__ (line 237) | def __init__(self, cfg, debug=False):
    method forward (line 245) | def forward(
  class DiscriminatorB (line 272) | class DiscriminatorB(nn.Module):
    method __init__ (line 273) | def __init__(
    method spectrogram (line 311) | def spectrogram(self, x: torch.Tensor) -> List[torch.Tensor]:
    method forward (line 323) | def forward(self, x: torch.Tensor) -> Tuple[torch.Tensor, List[torch.T...
  class MultiBandDiscriminator (line 346) | class MultiBandDiscriminator(nn.Module):
    method __init__ (line 347) | def __init__(
    method forward (line 360) | def forward(
  class DiscriminatorCQT (line 386) | class DiscriminatorCQT(nn.Module):
    method __init__ (line 387) | def __init__(self, cfg: AttrDict, hop_length: int, n_octaves: int, bin...
    method get_2d_padding (line 488) | def get_2d_padding(
    method forward (line 498) | def forward(self, x: torch.tensor) -> Tuple[torch.Tensor, List[torch.T...
  class MultiScaleSubbandCQTDiscriminator (line 542) | class MultiScaleSubbandCQTDiscriminator(nn.Module):
    method __init__ (line 543) | def __init__(self, cfg: AttrDict):
    method forward (line 571) | def forward(
  class CombinedDiscriminator (line 595) | class CombinedDiscriminator(nn.Module):
    method __init__ (line 601) | def __init__(self, list_discriminator: List[nn.Module]):
    method forward (line 605) | def forward(

FILE: GPT_SoVITS/BigVGAN/env.py
  class AttrDict (line 8) | class AttrDict(dict):
    method __init__ (line 9) | def __init__(self, *args, **kwargs):
  function build_env (line 14) | def build_env(config, config_name, path):

FILE: GPT_SoVITS/BigVGAN/inference.py
  function inference (line 23) | def inference(a, h):
  function main (line 54) | def main():

FILE: GPT_SoVITS/BigVGAN/inference_e2e.py
  function load_checkpoint (line 22) | def load_checkpoint(filepath, device):
  function scan_checkpoint (line 30) | def scan_checkpoint(cp_dir, prefix):
  function inference (line 38) | def inference(a, h):
  function main (line 69) | def main():

FILE: GPT_SoVITS/BigVGAN/loss.py
  class MultiScaleMelSpectrogramLoss (line 22) | class MultiScaleMelSpectrogramLoss(nn.Module):
    method __init__ (line 51) | def __init__(
    method get_window (line 96) | def get_window(
    method get_mel_filters (line 104) | def get_mel_filters(sr, n_fft, n_mels, fmin, fmax):
    method mel_spectrogram (line 107) | def mel_spectrogram(
    method forward (line 162) | def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
  function feature_loss (line 203) | def feature_loss(fmap_r: List[List[torch.Tensor]], fmap_g: List[List[tor...
  function discriminator_loss (line 212) | def discriminator_loss(
  function generator_loss (line 228) | def generator_loss(

FILE: GPT_SoVITS/BigVGAN/meldataset.py
  function dynamic_range_compression (line 23) | def dynamic_range_compression(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression (line 27) | def dynamic_range_decompression(x, C=1):
  function dynamic_range_compression_torch (line 31) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression_torch (line 35) | def dynamic_range_decompression_torch(x, C=1):
  function spectral_normalize_torch (line 39) | def spectral_normalize_torch(magnitudes):
  function spectral_de_normalize_torch (line 43) | def spectral_de_normalize_torch(magnitudes):
  function mel_spectrogram (line 51) | def mel_spectrogram(
  function get_mel_spectrogram (line 119) | def get_mel_spectrogram(wav, h):
  function get_dataset_filelist (line 142) | def get_dataset_filelist(a):
  class MelDataset (line 172) | class MelDataset(torch.utils.data.Dataset):
    method __init__ (line 173) | def __init__(
    method __getitem__ (line 222) | def __getitem__(self, index: int) -> Tuple[torch.Tensor, torch.Tensor,...
    method __len__ (line 369) | def __len__(self):

FILE: GPT_SoVITS/BigVGAN/tests/test_activation.py
  function test_load_fused_kernels (line 16) | def test_load_fused_kernels():
  function test_anti_alias_activation (line 24) | def test_anti_alias_activation():

FILE: GPT_SoVITS/BigVGAN/tests/test_activation_snake_beta.py
  function test_load_fused_kernels (line 16) | def test_load_fused_kernels():
  function test_anti_alias_activation (line 24) | def test_anti_alias_activation():

FILE: GPT_SoVITS/BigVGAN/tests/test_cuda_vs_torch_model.py
  function generate_soundwave (line 29) | def generate_soundwave(duration=5.0, sr=24000):
  function get_mel (line 44) | def get_mel(x, h):
  function load_checkpoint (line 48) | def load_checkpoint(filepath, device):

FILE: GPT_SoVITS/BigVGAN/train.py
  function train (line 56) | def train(rank, a, h):
  function main (line 611) | def main():

FILE: GPT_SoVITS/BigVGAN/utils0.py
  function plot_spectrogram (line 16) | def plot_spectrogram(spectrogram):
  function plot_spectrogram_clipped (line 27) | def plot_spectrogram_clipped(spectrogram, clip_max=2.0):
  function init_weights (line 45) | def init_weights(m, mean=0.0, std=0.01):
  function apply_weight_norm (line 51) | def apply_weight_norm(m):
  function get_padding (line 57) | def get_padding(kernel_size, dilation=1):
  function load_checkpoint (line 61) | def load_checkpoint(filepath, device):
  function save_checkpoint (line 69) | def save_checkpoint(filepath, obj):
  function scan_checkpoint (line 75) | def scan_checkpoint(cp_dir, prefix, renamed_file=None):
  function save_audio (line 95) | def save_audio(audio, path, sr):

FILE: GPT_SoVITS/TTS_infer_pack/TTS.py
  function resample (line 42) | def resample(audio_tensor, sr0, sr1, device):
  function norm_spec (line 59) | def norm_spec(x):
  function denorm_spec (line 63) | def denorm_spec(x):
  function speed_change (line 96) | def speed_change(input_audio: np.ndarray, speed: float, sr: int):
  class DictToAttrRecursive (line 117) | class DictToAttrRecursive(dict):
    method __init__ (line 118) | def __init__(self, input_dict):
    method __getattr__ (line 126) | def __getattr__(self, item):
    method __setattr__ (line 132) | def __setattr__(self, key, value):
    method __delattr__ (line 138) | def __delattr__(self, item):
  class NO_PROMPT_ERROR (line 145) | class NO_PROMPT_ERROR(Exception):
  function set_seed (line 194) | def set_seed(seed: int):
  class TTS_Config (line 217) | class TTS_Config:
    method __init__ (line 299) | def __init__(self, configs: Union[dict, str] = None):
    method _load_configs (line 366) | def _load_configs(self, configs_path: str) -> dict:
    method save_configs (line 377) | def save_configs(self, configs_path: str = None) -> None:
    method update_configs (line 387) | def update_configs(self):
    method update_version (line 399) | def update_version(self, version: str) -> None:
    method __str__ (line 403) | def __str__(self):
    method __repr__ (line 411) | def __repr__(self):
    method __hash__ (line 414) | def __hash__(self):
    method __eq__ (line 417) | def __eq__(self, other):
  class TTS (line 421) | class TTS:
    method __init__ (line 422) | def __init__(self, configs: Union[dict, str, TTS_Config]):
    method _init_models (line 467) | def _init_models(
    method init_cnhuhbert_weights (line 476) | def init_cnhuhbert_weights(self, base_path: str):
    method init_bert_weights (line 484) | def init_bert_weights(self, base_path: str):
    method init_vits_weights (line 493) | def init_vits_weights(self, weights_path: str):
    method init_t2s_weights (line 594) | def init_t2s_weights(self, weights_path: str):
    method init_vocoder (line 615) | def init_vocoder(self, version: str):
    method init_sr_model (line 676) | def init_sr_model(self):
    method init_sv_model (line 686) | def init_sv_model(self):
    method enable_half_precision (line 691) | def enable_half_precision(self, enable: bool = True, save: bool = True):
    method set_device (line 729) | def set_device(self, device: torch.device, save: bool = True):
    method set_ref_audio (line 751) | def set_ref_audio(self, ref_audio_path: str):
    method _set_ref_audio_path (line 762) | def _set_ref_audio_path(self, ref_audio_path):
    method _set_ref_spec (line 765) | def _set_ref_spec(self, ref_audio_path):
    method _get_ref_spec (line 772) | def _get_ref_spec(self, ref_audio_path):
    method _set_prompt_semantic (line 809) | def _set_prompt_semantic(self, ref_wav_path: str):
    method batch_sequences (line 835) | def batch_sequences(self, sequences: List[torch.Tensor], axis: int = 0...
    method to_batch (line 856) | def to_batch(
    method recovery_order (line 971) | def recovery_order(self, data: list, batch_index_list: list) -> list:
    method stop (line 989) | def stop(
    method run (line 998) | def run(self, inputs: dict):
    method empty_cache (line 1531) | def empty_cache(self):
    method audio_postprocess (line 1541) | def audio_postprocess(
    method using_vocoder_synthesis (line 1601) | def using_vocoder_synthesis(
    method using_vocoder_synthesis_batched_infer (line 1666) | def using_vocoder_synthesis_batched_infer(
    method sola_algorithm (line 1781) | def sola_algorithm(

FILE: GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py
  function get_first (line 28) | def get_first(text: str) -> str:
  function merge_short_text_in_array (line 34) | def merge_short_text_in_array(texts: str, threshold: int) -> list:
  class TextPreprocessor (line 52) | class TextPreprocessor:
    method __init__ (line 53) | def __init__(self, bert_model: AutoModelForMaskedLM, tokenizer: AutoTo...
    method preprocess (line 59) | def preprocess(self, text: str, lang: str, text_split_method: str, ver...
    method pre_seg_text (line 77) | def pre_seg_text(self, text: str, lang: str, text_split_method: str):
    method segment_and_extract_feature_for_text (line 117) | def segment_and_extract_feature_for_text(
    method get_phones_and_bert (line 122) | def get_phones_and_bert(self, text: str, language: str, version: str, ...
    method get_bert_feature (line 191) | def get_bert_feature(self, text: str, word2ph: list) -> torch.Tensor:
    method clean_text_inf (line 206) | def clean_text_inf(self, text: str, language: str, version: str = "v2"):
    method get_bert_inf (line 212) | def get_bert_inf(self, phones: list, word2ph: list, norm_text: str, la...
    method filter_text (line 224) | def filter_text(self, texts):
    method replace_consecutive_punctuation (line 235) | def replace_consecutive_punctuation(self, text):

FILE: GPT_SoVITS/TTS_infer_pack/text_segmentation_method.py
  function get_method (line 8) | def get_method(name: str) -> Callable:
  function get_method_names (line 15) | def get_method_names() -> list:
  function register_method (line 19) | def register_method(name):
  function split_big_text (line 44) | def split_big_text(text, max_len=510):
  function split (line 70) | def split(todo_text):
  function cut0 (line 91) | def cut0(inp):
  function cut1 (line 100) | def cut1(inp):
  function cut2 (line 117) | def cut2(inp):
  function cut3 (line 144) | def cut3(inp):
  function cut4 (line 153) | def cut4(inp):
  function cut5 (line 163) | def cut5(inp):

FILE: GPT_SoVITS/eres2net/ERes2Net.py
  class ReLU (line 19) | class ReLU(nn.Hardtanh):
    method __init__ (line 20) | def __init__(self, inplace=False):
    method __repr__ (line 23) | def __repr__(self):
  class BasicBlockERes2Net (line 28) | class BasicBlockERes2Net(nn.Module):
    method __init__ (line 31) | def __init__(self, in_planes, planes, stride=1, baseWidth=32, scale=2):
    method forward (line 59) | def forward(self, x):
  class BasicBlockERes2Net_diff_AFF (line 88) | class BasicBlockERes2Net_diff_AFF(nn.Module):
    method __init__ (line 91) | def __init__(self, in_planes, planes, stride=1, baseWidth=32, scale=2):
    method forward (line 124) | def forward(self, x):
  class ERes2Net (line 154) | class ERes2Net(nn.Module):
    method __init__ (line 155) | def __init__(
    method _make_layer (line 206) | def _make_layer(self, block, planes, num_blocks, stride):
    method forward (line 214) | def forward(self, x):
    method forward3 (line 239) | def forward3(self, x):

FILE: GPT_SoVITS/eres2net/ERes2NetV2.py
  class ReLU (line 19) | class ReLU(nn.Hardtanh):
    method __init__ (line 20) | def __init__(self, inplace=False):
    method __repr__ (line 23) | def __repr__(self):
  class BasicBlockERes2NetV2 (line 28) | class BasicBlockERes2NetV2(nn.Module):
    method __init__ (line 29) | def __init__(self, in_planes, planes, stride=1, baseWidth=26, scale=2,...
    method forward (line 58) | def forward(self, x):
  class BasicBlockERes2NetV2AFF (line 87) | class BasicBlockERes2NetV2AFF(nn.Module):
    method __init__ (line 88) | def __init__(self, in_planes, planes, stride=1, baseWidth=26, scale=2,...
    method forward (line 122) | def forward(self, x):
  class ERes2NetV2 (line 152) | class ERes2NetV2(nn.Module):
    method __init__ (line 153) | def __init__(
    method _make_layer (line 207) | def _make_layer(self, block, planes, num_blocks, stride):
    method forward (line 219) | def forward(self, x):
    method forward3 (line 240) | def forward3(self, x):

FILE: GPT_SoVITS/eres2net/ERes2Net_huge.py
  class ReLU (line 20) | class ReLU(nn.Hardtanh):
    method __init__ (line 21) | def __init__(self, inplace=False):
    method __repr__ (line 24) | def __repr__(self):
  class BasicBlockERes2Net (line 29) | class BasicBlockERes2Net(nn.Module):
    method __init__ (line 32) | def __init__(self, in_planes, planes, stride=1, baseWidth=24, scale=3):
    method forward (line 60) | def forward(self, x):
  class BasicBlockERes2Net_diff_AFF (line 89) | class BasicBlockERes2Net_diff_AFF(nn.Module):
    method __init__ (line 92) | def __init__(self, in_planes, planes, stride=1, baseWidth=24, scale=3):
    method forward (line 125) | def forward(self, x):
  class ERes2Net (line 155) | class ERes2Net(nn.Module):
    method __init__ (line 156) | def __init__(
    method _make_layer (line 206) | def _make_layer(self, block, planes, num_blocks, stride):
    method forward (line 214) | def forward(self, x):
    method forward2 (line 240) | def forward2(self, x, if_mean):
    method forward3 (line 271) | def forward3(self, x):

FILE: GPT_SoVITS/eres2net/fusion.py
  class AFF (line 8) | class AFF(nn.Module):
    method __init__ (line 9) | def __init__(self, channels=64, r=4):
    method forward (line 21) | def forward(self, x, ds_y):

FILE: GPT_SoVITS/eres2net/kaldi.py
  function _get_epsilon (line 35) | def _get_epsilon(device, dtype):
  function _next_power_of_2 (line 39) | def _next_power_of_2(x: int) -> int:
  function _get_strided (line 44) | def _get_strided(waveform: Tensor, window_size: int, window_shift: int, ...
  function _feature_window_function (line 86) | def _feature_window_function(
  function _get_log_energy (line 116) | def _get_log_energy(strided_input: Tensor, epsilon: Tensor, energy_floor...
  function _get_waveform_and_window_properties (line 125) | def _get_waveform_and_window_properties(
  function _get_window (line 154) | def _get_window(
  function _subtract_column_mean (line 220) | def _subtract_column_mean(tensor: Tensor, subtract_mean: bool) -> Tensor:
  function spectrogram (line 229) | def spectrogram(
  function inverse_mel_scale_scalar (line 318) | def inverse_mel_scale_scalar(mel_freq: float) -> float:
  function inverse_mel_scale (line 322) | def inverse_mel_scale(mel_freq: Tensor) -> Tensor:
  function mel_scale_scalar (line 326) | def mel_scale_scalar(freq: float) -> float:
  function mel_scale (line 330) | def mel_scale(freq: Tensor) -> Tensor:
  function vtln_warp_freq (line 334) | def vtln_warp_freq(
  function vtln_warp_mel_freq (line 409) | def vtln_warp_mel_freq(
  function get_mel_banks (line 436) | def get_mel_banks(
  function fbank (line 519) | def fbank(
  function _get_dct_matrix (line 679) | def _get_dct_matrix(num_ceps: int, num_mel_bins: int) -> Tensor:
  function _get_lifter_coeffs (line 692) | def _get_lifter_coeffs(num_ceps: int, cepstral_lifter: float) -> Tensor:
  function mfcc (line 700) | def mfcc(

FILE: GPT_SoVITS/eres2net/pooling_layers.py
  class TAP (line 10) | class TAP(nn.Module):
    method __init__ (line 15) | def __init__(self, **kwargs):
    method forward (line 18) | def forward(self, x):
  class TSDP (line 25) | class TSDP(nn.Module):
    method __init__ (line 30) | def __init__(self, **kwargs):
    method forward (line 33) | def forward(self, x):
  class TSTP (line 40) | class TSTP(nn.Module):
    method __init__ (line 47) | def __init__(self, **kwargs):
    method forward (line 50) | def forward(self, x):
  class ASTP (line 61) | class ASTP(nn.Module):
    method __init__ (line 66) | def __init__(self, in_dim, bottleneck_dim=128, global_context_att=False):
    method forward (line 78) | def forward(self, x):

FILE: GPT_SoVITS/export_torch_script.py
  function init_sv_cn (line 42) | def init_sv_cn(device, is_half):
  function load_sovits_new (line 47) | def load_sovits_new(sovits_path):
  function get_raw_t2s_model (line 59) | def get_raw_t2s_model(dict_s1) -> Text2SemanticLightningModule:
  function logits_to_probs (line 69) | def logits_to_probs(
  function multinomial_sample_one_no_sync (line 107) | def multinomial_sample_one_no_sync(probs_sort):
  function sample (line 114) | def sample(
  function spectrogram_torch (line 135) | def spectrogram_torch(
  class DictToAttrRecursive (line 161) | class DictToAttrRecursive(dict):
    method __init__ (line 162) | def __init__(self, input_dict):
    method __getattr__ (line 170) | def __getattr__(self, item):
    method __setattr__ (line 176) | def __setattr__(self, key, value):
    method __delattr__ (line 182) | def __delattr__(self, item):
  class T2SMLP (line 190) | class T2SMLP:
    method __init__ (line 191) | def __init__(self, w1, b1, w2, b2):
    method forward (line 197) | def forward(self, x):
  class T2SBlock (line 204) | class T2SBlock:
    method __init__ (line 205) | def __init__(
    method to_mask (line 238) | def to_mask(self, x: torch.Tensor, padding_mask: Optional[torch.Tensor]):
    method process_prompt (line 247) | def process_prompt(self, x: torch.Tensor, attn_mask: torch.Tensor, pad...
    method decode_next_token (line 281) | def decode_next_token(self, x: torch.Tensor, k_cache: torch.Tensor, v_...
  class T2STransformer (line 316) | class T2STransformer:
    method __init__ (line 317) | def __init__(self, num_blocks: int, blocks: list[T2SBlock]):
    method process_prompt (line 321) | def process_prompt(self, x: torch.Tensor, attn_mask: torch.Tensor, pad...
    method decode_next_token (line 330) | def decode_next_token(self, x: torch.Tensor, k_cache: list[torch.Tenso...
  class VitsModel (line 336) | class VitsModel(nn.Module):
    method __init__ (line 337) | def __init__(self, vits_path, version=None, is_half=True, device="cpu"):
    method forward (line 372) | def forward(self, text_seq, pred_semantic, ref_audio, speed=1.0, sv_em...
  class T2SModel (line 385) | class T2SModel(nn.Module):
    method __init__ (line 386) | def __init__(self, raw_t2s: Text2SemanticLightningModule):
    method forward (line 443) | def forward(
  function build_phone_level_feature (line 554) | def build_phone_level_feature(res: Tensor, word2ph: IntTensor):
  class MyBertModel (line 564) | class MyBertModel(torch.nn.Module):
    method __init__ (line 565) | def __init__(self, bert_model):
    method forward (line 569) | def forward(
  class SSLModel (line 578) | class SSLModel(torch.nn.Module):
    method __init__ (line 579) | def __init__(self):
    method forward (line 583) | def forward(self, ref_audio_16k) -> torch.Tensor:
  class ExportSSLModel (line 588) | class ExportSSLModel(torch.nn.Module):
    method __init__ (line 589) | def __init__(self, ssl: SSLModel):
    method forward (line 593) | def forward(self, ref_audio: torch.Tensor):
    method resample (line 597) | def resample(self, ref_audio: torch.Tensor, src_sr: int, dst_sr: int) ...
  function export_bert (line 602) | def export_bert(output_path):
  function export (line 636) | def export(gpt_path, vits_path, ref_audio_path, ref_text, output_path, e...
  function export_prov2 (line 709) | def export_prov2(
  function parse_audio (line 828) | def parse_audio(ref_audio):
  function resamplex (line 835) | def resamplex(ref_audio: torch.Tensor, src_sr: int, dst_sr: int) -> torc...
  class GPT_SoVITS (line 839) | class GPT_SoVITS(nn.Module):
    method __init__ (line 840) | def __init__(self, t2s: T2SModel, vits: VitsModel):
    method forward (line 845) | def forward(
  class ExportERes2NetV2 (line 865) | class ExportERes2NetV2(nn.Module):
    method __init__ (line 866) | def __init__(self, sv_cn_model: SV):
    method forward (line 878) | def forward(self, audio_16k):
  class GPT_SoVITS_V2Pro (line 896) | class GPT_SoVITS_V2Pro(nn.Module):
    method __init__ (line 897) | def __init__(self, t2s: T2SModel, vits: VitsModel, sv_model: ExportERe...
    method forward (line 903) | def forward(
  function test (line 926) | def test():
  function export_symbel (line 1028) | def export_symbel(version="v2"):
  function main (line 1039) | def main():

FILE: GPT_SoVITS/export_torch_script_v3v4.py
  class MelSpectrgram (line 34) | class MelSpectrgram(torch.nn.Module):
    method __init__ (line 35) | def __init__(
    method forward (line 57) | def forward(self, y):
  class ExportDitBlocks (line 86) | class ExportDitBlocks(torch.nn.Module):
    method __init__ (line 87) | def __init__(self, dit: DiT):
    method forward (line 94) | def forward(self, x, t, mask, rope):
  class ExportDitEmbed (line 102) | class ExportDitEmbed(torch.nn.Module):
    method __init__ (line 103) | def __init__(self, dit: DiT):
    method forward (line 112) | def forward(
  class ExportDiT (line 134) | class ExportDiT(torch.nn.Module):
    method __init__ (line 135) | def __init__(self, dit: DiT):
    method forward (line 144) | def forward(  # x, prompt_x, x_lens, t, style,cond
  class ExportCFM (line 158) | class ExportCFM(torch.nn.Module):
    method __init__ (line 159) | def __init__(self, cfm: CFM):
    method forward (line 163) | def forward(
  function norm_spec (line 211) | def norm_spec(x):
  function denorm_spec (line 217) | def denorm_spec(x):
  class ExportGPTSovitsHalf (line 223) | class ExportGPTSovitsHalf(torch.nn.Module):
    method __init__ (line 224) | def __init__(self, hps, t2s_m: T2SModel, vq_model: SynthesizerTrnV3):
    method forward (line 248) | def forward(
  class ExportGPTSovitsV4Half (line 303) | class ExportGPTSovitsV4Half(torch.nn.Module):
    method __init__ (line 304) | def __init__(self, hps, t2s_m: T2SModel, vq_model: SynthesizerTrnV3):
    method forward (line 328) | def forward(
  class GPTSoVITSV3 (line 383) | class GPTSoVITSV3(torch.nn.Module):
    method __init__ (line 384) | def __init__(self, gpt_sovits_half, cfm, bigvgan):
    method forward (line 390) | def forward(
  class GPTSoVITSV4 (line 443) | class GPTSoVITSV4(torch.nn.Module):
    method __init__ (line 444) | def __init__(self, gpt_sovits_half, cfm, hifigan):
    method forward (line 450) | def forward(
  function init_bigvgan (line 503) | def init_bigvgan():
  function init_hifigan (line 520) | def init_hifigan():
  class Sovits (line 545) | class Sovits:
    method __init__ (line 546) | def __init__(self, vq_model: SynthesizerTrnV3, cfm: CFM, hps):
  class DictToAttrRecursive (line 553) | class DictToAttrRecursive(dict):
    method __init__ (line 554) | def __init__(self, input_dict):
    method __getattr__ (line 562) | def __getattr__(self, item):
    method __setattr__ (line 568) | def __setattr__(self, key, value):
    method __delattr__ (line 574) | def __delattr__(self, item):
  function get_sovits_weights (line 586) | def get_sovits_weights(sovits_path):
  function export_cfm (line 642) | def export_cfm(
  function export_1 (line 708) | def export_1(ref_wav_path, ref_wav_text, version="v3"):
  function test_export (line 931) | def test_export(
  function test_export (line 1050) | def test_export(
  function export_2 (line 1125) | def export_2(version="v3"):
  function test_export_gpt_sovits_v3 (line 1236) | def test_export_gpt_sovits_v3():

FILE: GPT_SoVITS/f5_tts/model/backbones/dit.py
  class TextEmbedding (line 31) | class TextEmbedding(nn.Module):
    method __init__ (line 32) | def __init__(self, text_dim, conv_layers=0, conv_mult=2):
    method forward (line 44) | def forward(self, text: int["b nt"], seq_len, drop_text=False):  # noq...
  class InputEmbedding (line 70) | class InputEmbedding(nn.Module):
    method __init__ (line 71) | def __init__(self, mel_dim, text_dim, out_dim):
    method forward (line 76) | def forward(self, x: float["b n d"], cond: float["b n d"], text_embed:...
  class DiT (line 88) | class DiT(nn.Module):
    method __init__ (line 89) | def __init__(
    method ckpt_wrapper (line 125) | def ckpt_wrapper(self, module):
    method forward (line 133) | def forward(  # x, prompt_x, x_lens, t, style,cond

FILE: GPT_SoVITS/f5_tts/model/backbones/mmdit.py
  class TextEmbedding (line 30) | class TextEmbedding(nn.Module):
    method __init__ (line 31) | def __init__(self, out_dim, text_num_embeds):
    method forward (line 38) | def forward(self, text: int["b nt"], drop_text=False) -> int["b nt d"]...
  class AudioEmbedding (line 58) | class AudioEmbedding(nn.Module):
    method __init__ (line 59) | def __init__(self, in_dim, out_dim):
    method forward (line 64) | def forward(self, x: float["b n d"], cond: float["b n d"], drop_audio_...
  class MMDiT (line 76) | class MMDiT(nn.Module):
    method __init__ (line 77) | def __init__(
    method forward (line 116) | def forward(

FILE: GPT_SoVITS/f5_tts/model/backbones/unett.py
  class TextEmbedding (line 35) | class TextEmbedding(nn.Module):
    method __init__ (line 36) | def __init__(self, text_num_embeds, text_dim, conv_layers=0, conv_mult...
    method forward (line 50) | def forward(self, text: int["b nt"], seq_len, drop_text=False):  # noq...
  class InputEmbedding (line 78) | class InputEmbedding(nn.Module):
    method __init__ (line 79) | def __init__(self, mel_dim, text_dim, out_dim):
    method forward (line 84) | def forward(self, x: float["b n d"], cond: float["b n d"], text_embed:...
  class UNetT (line 96) | class UNetT(nn.Module):
    method __init__ (line 97) | def __init__(
    method forward (line 164) | def forward(

FILE: GPT_SoVITS/f5_tts/model/modules.py
  function get_bigvgan_mel_spectrogram (line 30) | def get_bigvgan_mel_spectrogram(
  function get_vocos_mel_spectrogram (line 75) | def get_vocos_mel_spectrogram(
  class MelSpec (line 104) | class MelSpec(nn.Module):
    method __init__ (line 105) | def __init__(
    method forward (line 130) | def forward(self, wav):
  class SinusPositionEmbedding (line 149) | class SinusPositionEmbedding(nn.Module):
    method __init__ (line 150) | def __init__(self, dim):
    method forward (line 154) | def forward(self, x, scale=1000):
  class ConvPositionEmbedding (line 167) | class ConvPositionEmbedding(nn.Module):
    method __init__ (line 168) | def __init__(self, dim, kernel_size=31, groups=16):
    method forward (line 178) | def forward(self, x: float["b n d"], mask: bool["b n"] | None = None):...
  function precompute_freqs_cis (line 196) | def precompute_freqs_cis(dim: int, end: int, theta: float = 10000.0, the...
  function get_pos_embed_indices (line 210) | def get_pos_embed_indices(start, length, max_pos, scale=1.0):
  class GRN (line 225) | class GRN(nn.Module):
    method __init__ (line 226) | def __init__(self, dim):
    method forward (line 231) | def forward(self, x):
  class ConvNeXtV2Block (line 241) | class ConvNeXtV2Block(nn.Module):
    method __init__ (line 242) | def __init__(
    method forward (line 259) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class AdaLayerNormZero (line 276) | class AdaLayerNormZero(nn.Module):
    method __init__ (line 277) | def __init__(self, dim):
    method forward (line 285) | def forward(self, x, emb=None):
  class AdaLayerNormZero_Final (line 297) | class AdaLayerNormZero_Final(nn.Module):
    method __init__ (line 298) | def __init__(self, dim):
    method forward (line 306) | def forward(self, x, emb):
  class FeedForward (line 317) | class FeedForward(nn.Module):
    method __init__ (line 318) | def __init__(self, dim, dim_out=None, mult=4, dropout=0.0, approximate...
    method forward (line 327) | def forward(self, x):
  class Attention (line 335) | class Attention(nn.Module):
    method __init__ (line 336) | def __init__(
    method forward (line 378) | def forward(
  class AttnProcessor (line 397) | class AttnProcessor:
    method __init__ (line 398) | def __init__(self):
    method __call__ (line 401) | def __call__(
  class JointAttnProcessor (line 464) | class JointAttnProcessor:
    method __init__ (line 465) | def __init__(self):
    method __call__ (line 468) | def __call__(
  class DiTBlock (line 550) | class DiTBlock(nn.Module):
    method __init__ (line 551) | def __init__(self, dim, heads, dim_head, ff_mult=4, dropout=0.1):
    method forward (line 566) | def forward(self, x, t, mask=None, rope=None):  # x: noised input, t: ...
  class MMDiTBlock (line 586) | class MMDiTBlock(nn.Module):
    method __init__ (line 596) | def __init__(self, dim, heads, dim_head, ff_mult=4, dropout=0.1, conte...
    method forward (line 622) | def forward(self, x, c, t, mask=None, rope=None, c_rope=None):  # x: n...
  class TimestepEmbedding (line 656) | class TimestepEmbedding(nn.Module):
    method __init__ (line 657) | def __init__(self, dim, freq_embed_dim=256):
    method forward (line 662) | def forward(self, timestep: float["b"]):  # noqa: F821

FILE: GPT_SoVITS/feature_extractor/cnhubert.py
  class CNHubert (line 22) | class CNHubert(nn.Module):
    method __init__ (line 23) | def __init__(self, base_path: str = None):
    method forward (line 34) | def forward(self, x):
  function get_model (line 71) | def get_model():
  function get_content (line 93) | def get_content(hmodel, wav_16k_tensor):

FILE: GPT_SoVITS/feature_extractor/whisper_enc.py
  function get_model (line 4) | def get_model():
  function get_content (line 12) | def get_content(model=None, wav_16k_tensor=None):

FILE: GPT_SoVITS/inference_cli.py
  function synthesize (line 11) | def synthesize(
  function main (line 53) | def main():

FILE: GPT_SoVITS/inference_gui.py
  class GPTSoVITSGUI (line 15) | class GPTSoVITSGUI(QMainWindow):
    method __init__ (line 19) | def __init__(self):
    method dragEnterEvent (line 199) | def dragEnterEvent(self, event):
    method dropEvent (line 203) | def dropEvent(self, event):
    method add_drag_drop_events (line 211) | def add_drag_drop_events(self, widgets):
    method eventFilter (line 216) | def eventFilter(self, obj, event):
    method select_GPT_model (line 224) | def select_GPT_model(self):
    method select_SoVITS_model (line 229) | def select_SoVITS_model(self):
    method select_ref_audio (line 234) | def select_ref_audio(self):
    method upload_ref_text (line 239) | def upload_ref_text(self):
    method upload_target_text (line 246) | def upload_target_text(self):
    method select_output_path (line 253) | def select_output_path(self):
    method update_ref_audio (line 266) | def update_ref_audio(self, file_path):
    method clear_output (line 269) | def clear_output(self):
    method synthesize (line 272) | def synthesize(self):

FILE: GPT_SoVITS/inference_webui.py
  function set_high_priority (line 12) | def set_high_priority():
  function set_seed (line 106) | def set_seed(seed):
  function get_bert_feature (line 171) | def get_bert_feature(text, word2ph):
  class DictToAttrRecursive (line 187) | class DictToAttrRecursive(dict):
    method __init__ (line 188) | def __init__(self, input_dict):
    method __getattr__ (line 196) | def __getattr__(self, item):
    method __setattr__ (line 202) | def __setattr__(self, key, value):
    method __delattr__ (line 208) | def __delattr__(self, item):
  function change_sovits_weights (line 229) | def change_sovits_weights(sovits_path, prompt_language=None, text_langua...
  function change_gpt_weights (line 376) | def change_gpt_weights(gpt_path):
  function clean_hifigan_model (line 407) | def clean_hifigan_model():
  function clean_bigvgan_model (line 418) | def clean_bigvgan_model():
  function clean_sv_cn_model (line 429) | def clean_sv_cn_model():
  function init_bigvgan (line 440) | def init_bigvgan():
  function init_hifigan (line 459) | def init_hifigan():
  function init_sv_cn (line 491) | def init_sv_cn():
  function resample (line 509) | def resample(audio_tensor, sr0, sr1, device):
  function get_spepc (line 517) | def get_spepc(hps, filename, dtype, device, is_v2pro=False):
  function clean_text_inf (line 552) | def clean_text_inf(text, language, version):
  function get_bert_inf (line 562) | def get_bert_inf(phones, word2ph, norm_text, language):
  function get_first (line 592) | def get_first(text):
  function get_phones_and_bert (line 601) | def get_phones_and_bert(text, language, version, final=False):
  function norm_spec (line 676) | def norm_spec(x):
  function denorm_spec (line 680) | def denorm_spec(x):
  function merge_short_text_in_array (line 712) | def merge_short_text_in_array(texts, threshold):
  function audio_sr (line 733) | def audio_sr(audio, sr):
  function get_tts_wav (line 751) | def get_tts_wav(
  function split (line 1004) | def split(todo_text):
  function cut1 (line 1023) | def cut1(inp):
  function cut2 (line 1038) | def cut2(inp):
  function cut3 (line 1063) | def cut3(inp):
  function cut4 (line 1070) | def cut4(inp):
  function cut5 (line 1078) | def cut5(inp):
  function custom_sort_key (line 1102) | def custom_sort_key(s):
  function process_text (line 1110) | def process_text(texts):
  function html_center (line 1122) | def html_center(text, label="p"):
  function html_left (line 1128) | def html_left(text, label="p"):

FILE: GPT_SoVITS/inference_webui_fast.py
  function set_high_priority (line 12) | def set_high_priority():
  function inference (line 150) | def inference(
  function custom_sort_key (line 204) | def custom_sort_key(s):
  function change_sovits_weights (line 233) | def change_sovits_weights(sovits_path, prompt_language=None, text_langua...
  function change_gpt_weights (line 300) | def change_gpt_weights(gpt_path):
  function to_cut (line 506) | def to_cut(text_inp, how_to_cut):

FILE: GPT_SoVITS/module/attentions.py
  class Encoder (line 10) | class Encoder(nn.Module):
    method __init__ (line 11) | def __init__(
    method forward (line 64) | def forward(self, x, x_mask, g=None):
  class Decoder (line 87) | class Decoder(nn.Module):
    method __init__ (line 88) | def __init__(
    method forward (line 145) | def forward(self, x, x_mask, h, h_mask):
  class MultiHeadAttention (line 169) | class MultiHeadAttention(nn.Module):
    method __init__ (line 170) | def __init__(
    method forward (line 217) | def forward(self, x, c, attn_mask=None):
    method attention (line 227) | def attention(self, query, key, value, mask=None):
    method _matmul_with_relative_values (line 260) | def _matmul_with_relative_values(self, x, y):
    method _matmul_with_relative_keys (line 269) | def _matmul_with_relative_keys(self, x, y):
    method _get_relative_embeddings (line 278) | def _get_relative_embeddings(self, relative_embeddings, length):
    method _relative_position_to_absolute_position (line 294) | def _relative_position_to_absolute_position(self, x):
    method _absolute_position_to_relative_position (line 311) | def _absolute_position_to_relative_position(self, x):
    method _attention_bias_proximal (line 325) | def _attention_bias_proximal(self, length):
  class FFN (line 337) | class FFN(nn.Module):
    method __init__ (line 338) | def __init__(
    method forward (line 366) | def forward(self, x, x_mask):
    method _causal_padding (line 376) | def _causal_padding(self, x):
    method _same_padding (line 385) | def _same_padding(self, x):
  class Depthwise_Separable_Conv1D (line 399) | class Depthwise_Separable_Conv1D(nn.Module):
    method __init__ (line 400) | def __init__(
    method forward (line 436) | def forward(self, input):
    method weight_norm (line 439) | def weight_norm(self):
    method remove_weight_norm (line 443) | def remove_weight_norm(self):
  class Depthwise_Separable_TransposeConv1D (line 448) | class Depthwise_Separable_TransposeConv1D(nn.Module):
    method __init__ (line 449) | def __init__(
    method forward (line 487) | def forward(self, input):
    method weight_norm (line 490) | def weight_norm(self):
    method remove_weight_norm (line 494) | def remove_weight_norm(self):
  function weight_norm_modules (line 499) | def weight_norm_modules(module, name="weight", dim=0):
  function remove_weight_norm_modules (line 507) | def remove_weight_norm_modules(module, name="weight"):
  class FFT (line 514) | class FFT(nn.Module):
    method __init__ (line 515) | def __init__(
    method forward (line 571) | def forward(self, x, x_mask, g=None):
  class TransformerCouplingLayer (line 598) | class TransformerCouplingLayer(nn.Module):
    method __init__ (line 599) | def __init__(
    method forward (line 640) | def forward(self, x, x_mask, g=None, reverse=False):

FILE: GPT_SoVITS/module/attentions_onnx.py
  class LayerNorm (line 11) | class LayerNorm(nn.Module):
    method __init__ (line 12) | def __init__(self, channels, eps=1e-5):
    method forward (line 20) | def forward(self, x):
  function fused_add_tanh_sigmoid_multiply (line 27) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
  class Encoder (line 36) | class Encoder(nn.Module):
    method __init__ (line 37) | def __init__(
    method forward (line 118) | def forward(self, x, x_mask):
  class MultiHeadAttention (line 135) | class MultiHeadAttention(nn.Module):
    method __init__ (line 136) | def __init__(
    method forward (line 183) | def forward(self, x, c, attn_mask: Optional[torch.Tensor] = None):
    method attention (line 194) | def attention(self, query, key, value, mask: Optional[torch.Tensor] = ...
    method _matmul_with_relative_values (line 223) | def _matmul_with_relative_values(self, x, y):
    method _matmul_with_relative_keys (line 232) | def _matmul_with_relative_keys(self, x, y):
    method _get_relative_embeddings (line 241) | def _get_relative_embeddings(self, relative_embeddings, length):
    method _relative_position_to_absolute_position (line 257) | def _relative_position_to_absolute_position(self, x):
    method _absolute_position_to_relative_position (line 274) | def _absolute_position_to_relative_position(self, x):
    method _attention_bias_proximal (line 288) | def _attention_bias_proximal(self, length):
  class FFN (line 300) | class FFN(nn.Module):
    method __init__ (line 301) | def __init__(
    method forward (line 330) | def forward(self, x, x_mask):
    method padding (line 340) | def padding(self, x):
    method _causal_padding (line 343) | def _causal_padding(self, x):
    method _same_padding (line 352) | def _same_padding(self, x):
  class MRTE (line 362) | class MRTE(nn.Module):
    method __init__ (line 363) | def __init__(
    method forward (line 378) | def forward(self, ssl_enc, ssl_mask, text, text_mask, ge):

FILE: GPT_SoVITS/module/commons.py
  function init_weights (line 6) | def init_weights(m, mean=0.0, std=0.01):
  function get_padding (line 12) | def get_padding(kernel_size, dilation=1):
  function intersperse (line 22) | def intersperse(lst, item):
  function kl_divergence (line 28) | def kl_divergence(m_p, logs_p, m_q, logs_q):
  function rand_gumbel (line 35) | def rand_gumbel(shape):
  function rand_gumbel_like (line 41) | def rand_gumbel_like(x):
  function slice_segments (line 46) | def slice_segments(x, ids_str, segment_size=4):
  function rand_slice_segments (line 55) | def rand_slice_segments(x, x_lengths=None, segment_size=4):
  function get_timing_signal_1d (line 65) | def get_timing_signal_1d(length, channels, min_timescale=1.0, max_timesc...
  function add_timing_signal_1d (line 79) | def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
  function cat_timing_signal_1d (line 85) | def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis...
  function subsequent_mask (line 91) | def subsequent_mask(length):
  function fused_add_tanh_sigmoid_multiply (line 97) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
  function convert_pad_shape (line 106) | def convert_pad_shape(pad_shape):
  function shift_1d (line 112) | def shift_1d(x):
  function sequence_mask (line 117) | def sequence_mask(length, max_length=None):
  function generate_path (line 124) | def generate_path(duration, mask):
  function clip_grad_value_ (line 142) | def clip_grad_value_(parameters, clip_value, norm_type=2):
  function squeeze (line 160) | def squeeze(x, x_mask=None, n_sqz=2):
  function unsqueeze (line 175) | def unsqueeze(x, x_mask=None, n_sqz=2):

FILE: GPT_SoVITS/module/core_vq.py
  function default (line 47) | def default(val: tp.Any, d: tp.Any) -> tp.Any:
  function ema_inplace (line 51) | def ema_inplace(moving_avg, new, decay: float):
  function laplace_smoothing (line 55) | def laplace_smoothing(x, n_categories: int, epsilon: float = 1e-5):
  function uniform_init (line 59) | def uniform_init(*shape: int):
  function sample_vectors (line 65) | def sample_vectors(samples, num: int):
  function kmeans (line 76) | def kmeans(samples, num_clusters: int, num_iters: int = 10, frames_to_us...
  class EuclideanCodebook (line 114) | class EuclideanCodebook(nn.Module):
    method __init__ (line 130) | def __init__(
    method init_embed_ (line 157) | def init_embed_(self, data):
    method replace_ (line 180) | def replace_(self, samples, mask):
    method expire_codes_ (line 184) | def expire_codes_(self, batch_samples):
    method preprocess (line 204) | def preprocess(self, x):
    method quantize (line 208) | def quantize(self, x):
    method postprocess_emb (line 214) | def postprocess_emb(self, embed_ind, shape):
    method dequantize (line 217) | def dequantize(self, embed_ind):
    method encode (line 221) | def encode(self, x):
    method decode (line 231) | def decode(self, embed_ind):
    method forward (line 235) | def forward(self, x):
  class VectorQuantization (line 271) | class VectorQuantization(nn.Module):
    method __init__ (line 288) | def __init__(
    method codebook (line 322) | def codebook(self):
    method encode (line 325) | def encode(self, x):
    method decode (line 331) | def decode(self, embed_ind):
    method forward (line 337) | def forward(self, x):
  class ResidualVectorQuantization (line 359) | class ResidualVectorQuantization(nn.Module):
    method __init__ (line 364) | def __init__(self, *, num_quantizers, **kwargs):
    method forward (line 368) | def forward(self, x, n_q: tp.Optional[int] = None, layers: tp.Optional...
    method encode (line 391) | def encode(self, x: torch.Tensor, n_q: tp.Optional[int] = None, st: tp...
    method decode (line 404) | def decode(self, q_indices: torch.Tensor, st: int = 0) -> torch.Tensor:

FILE: GPT_SoVITS/module/data_utils.py
  class TextAudioSpeakerLoader (line 17) | class TextAudioSpeakerLoader(torch.utils.data.Dataset):
    method __init__ (line 24) | def __init__(self, hparams, version=None, val=False):
    method get_audio_text_speaker_pair (line 109) | def get_audio_text_speaker_pair(self, audiopath_sid_text):
    method get_audio (line 136) | def get_audio(self, filename):
    method get_sid (line 147) | def get_sid(self, sid):
    method __getitem__ (line 151) | def __getitem__(self, index):
    method __len__ (line 155) | def __len__(self):
    method random_slice (line 158) | def random_slice(self, ssl, wav, mel):
  class TextAudioSpeakerCollate (line 192) | class TextAudioSpeakerCollate:
    method __init__ (line 195) | def __init__(self, return_ids=False, version=None):
    method __call__ (line 199) | def __call__(self, batch):
  class TextAudioSpeakerLoaderV3 (line 279) | class TextAudioSpeakerLoaderV3(torch.utils.data.Dataset):
    method __init__ (line 286) | def __init__(self, hparams, val=False):
    method norm_spec (line 372) | def norm_spec(self, x):
    method get_audio_text_speaker_pair (line 375) | def get_audio_text_speaker_pair(self, audiopath_sid_text):
    method get_audio (line 396) | def get_audio(self, filename):
    method get_sid (line 429) | def get_sid(self, sid):
    method __getitem__ (line 433) | def __getitem__(self, index):
    method __len__ (line 437) | def __len__(self):
  class TextAudioSpeakerCollateV3 (line 441) | class TextAudioSpeakerCollateV3:
    method __init__ (line 444) | def __init__(self, return_ids=False):
    method __call__ (line 447) | def __call__(self, batch):
  class TextAudioSpeakerLoaderV4 (line 517) | class TextAudioSpeakerLoaderV4(torch.utils.data.Dataset):
    method __init__ (line 524) | def __init__(self, hparams, val=False):
    method norm_spec (line 610) | def norm_spec(self, x):
    method get_audio_text_speaker_pair (line 613) | def get_audio_text_speaker_pair(self, audiopath_sid_text):
    method get_audio (line 634) | def get_audio(self, filename):
    method get_sid (line 648) | def get_sid(self, sid):
    method __getitem__ (line 652) | def __getitem__(self, index):
    method __len__ (line 656) | def __len__(self):
  class TextAudioSpeakerCollateV4 (line 660) | class TextAudioSpeakerCollateV4:
    method __init__ (line 663) | def __init__(self, return_ids=False):
    method __call__ (line 666) | def __call__(self, batch):
  class TextAudioSpeakerLoaderV3b (line 728) | class TextAudioSpeakerLoaderV3b(torch.utils.data.Dataset):
    method __init__ (line 735) | def __init__(self, hparams, val=False):
    method norm_spec (line 821) | def norm_spec(self, x):
    method get_audio_text_speaker_pair (line 824) | def get_audio_text_speaker_pair(self, audiopath_sid_text):
    method get_audio (line 845) | def get_audio(self, filename):
    method get_sid (line 878) | def get_sid(self, sid):
    method __getitem__ (line 882) | def __getitem__(self, index):
    method __len__ (line 886) | def __len__(self):
  class TextAudioSpeakerCollateV3b (line 890) | class TextAudioSpeakerCollateV3b:
    method __init__ (line 893) | def __init__(self, return_ids=False):
    method __call__ (line 896) | def __call__(self, batch):
  class DistributedBucketSampler (line 976) | class DistributedBucketSampler(torch.utils.data.distributed.DistributedS...
    method __init__ (line 986) | def __init__(self, dataset, batch_size, boundaries, num_replicas=None,...
    method _create_buckets (line 996) | def _create_buckets(self):
    method __iter__ (line 1019) | def __iter__(self):
    method _bisect (line 1055) | def _bisect(self, x, lo=0, hi=None):
    method __len__ (line 1070) | def __len__(self):

FILE: GPT_SoVITS/module/ddp_utils.py
  class SyncFunction (line 8) | class SyncFunction(torch.autograd.Function):
    method forward (line 11) | def forward(ctx, tensor):
    method backward (line 44) | def backward(ctx, grad_output):
  class DDP (line 53) | class DDP(DistributedDataParallel):
    method forward (line 58) | def forward(self, *inputs, **kwargs):  # pragma: no cover

FILE: GPT_SoVITS/module/distrib.py
  function rank (line 14) | def rank():
  function world_size (line 21) | def world_size():
  function is_distributed (line 28) | def is_distributed():
  function all_reduce (line 32) | def all_reduce(tensor: torch.Tensor, op=torch.distributed.ReduceOp.SUM):
  function _is_complex_or_float (line 37) | def _is_complex_or_float(tensor):
  function _check_number_of_params (line 41) | def _check_number_of_params(params: tp.List[torch.Tensor]):
  function broadcast_tensors (line 57) | def broadcast_tensors(tensors: tp.Iterable[torch.Tensor], src: int = 0):
  function sync_buffer (line 73) | def sync_buffer(buffers, average=True):
  function sync_grad (line 93) | def sync_grad(params):
  function average_metrics (line 111) | def average_metrics(metrics: tp.Dict[str, float], count=1.0):

FILE: GPT_SoVITS/module/losses.py
  function feature_loss (line 6) | def feature_loss(fmap_r, fmap_g):
  function discriminator_loss (line 17) | def discriminator_loss(disc_real_outputs, disc_generated_outputs):
  function generator_loss (line 33) | def generator_loss(disc_outputs):
  function kl_loss (line 45) | def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):
  function mle_loss (line 63) | def mle_loss(z, m, logs, logdet, mask):

FILE: GPT_SoVITS/module/mel_processing.py
  function dynamic_range_compression_torch (line 8) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression_torch (line 17) | def dynamic_range_decompression_torch(x, C=1):
  function spectral_normalize_torch (line 26) | def spectral_normalize_torch(magnitudes):
  function spectral_de_normalize_torch (line 31) | def spectral_de_normalize_torch(magnitudes):
  function spectrogram_torch (line 40) | def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, cente...
  function spec_to_mel_torch (line 77) | def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
  function mel_spectrogram_torch (line 93) | def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, w...

FILE: GPT_SoVITS/module/models.py
  class StochasticDurationPredictor (line 28) | class StochasticDurationPredictor(nn.Module):
    method __init__ (line 29) | def __init__(
    method forward (line 69) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal...
  class DurationPredictor (line 117) | class DurationPredictor(nn.Module):
    method __init__ (line 118) | def __init__(self, in_channels, filter_channels, kernel_size, p_dropou...
    method forward (line 137) | def forward(self, x, x_mask, g=None):
  class TextEncoder (line 156) | class TextEncoder(nn.Module):
    method __init__ (line 157) | def __init__(
    method forward (line 214) | def forward(self, y, y_lengths, text, text_lengths, ge, speed=1, test=...
    method extract_latent (line 266) | def extract_latent(self, x):
    method decode_latent (line 271) | def decode_latent(self, codes, y_mask, refer, refer_mask, ge):
  class ResidualCouplingBlock (line 286) | class ResidualCouplingBlock(nn.Module):
    method __init__ (line 287) | def __init__(
    method forward (line 321) | def forward(self, x, x_mask, g=None, reverse=False):
  class PosteriorEncoder (line 331) | class PosteriorEncoder(nn.Module):
    method __init__ (line 332) | def __init__(
    method forward (line 361) | def forward(self, x, x_lengths, g=None):
  class Encoder (line 373) | class Encoder(nn.Module):
    method __init__ (line 374) | def __init__(
    method forward (line 390) | def forward(self, x, x_lengths, g=None):
  class WNEncoder (line 400) | class WNEncoder(nn.Module):
    method __init__ (line 401) | def __init__(
    method forward (line 431) | def forward(self, x, x_lengths, g=None):
  class Generator (line 440) | class Generator(torch.nn.Module):
    method __init__ (line 441) | def __init__(
    method forward (line 485) | def forward(self, x, g=None):
    method remove_weight_norm (line 506) | def remove_weight_norm(self):
  class DiscriminatorP (line 514) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 515) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=...
    method forward (line 571) | def forward(self, x):
  class DiscriminatorS (line 593) | class DiscriminatorS(torch.nn.Module):
    method __init__ (line 594) | def __init__(self, use_spectral_norm=False):
    method forward (line 609) | def forward(self, x):
  class MultiPeriodDiscriminator (line 626) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 627) | def __init__(self, use_spectral_norm=False, version=None):
    method forward (line 638) | def forward(self, y, y_hat):
  class ReferenceEncoder (line 654) | class ReferenceEncoder(nn.Module):
    method __init__ (line 660) | def __init__(self, spec_channels, gin_channels=0):
    method forward (line 689) | def forward(self, inputs):
    method calculate_channels (line 707) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs):
  class Quantizer_module (line 713) | class Quantizer_module(torch.nn.Module):
    method __init__ (line 714) | def __init__(self, n_e, e_dim):
    method forward (line 719) | def forward(self, x):
  class Quantizer (line 730) | class Quantizer(torch.nn.Module):
    method __init__ (line 731) | def __init__(self, embed_dim=512, n_code_groups=4, n_codes=160):
    method forward (line 740) | def forward(self, xin):
    method embed (line 759) | def embed(self, x):
  class CodePredictor (line 771) | class CodePredictor(nn.Module):
    method __init__ (line 772) | def __init__(
    method forward (line 801) | def forward(self, x, x_mask, refer, codes, infer=False):
  class SynthesizerTrn (line 829) | class SynthesizerTrn(nn.Module):
    method __init__ (line 834) | def __init__(
    method forward (line 934) | def forward(self, ssl, y, y_lengths, text, text_lengths, sv_emb=None):
    method infer (line 973) | def infer(self, ssl, y, y_lengths, text, text_lengths, test=None, nois...
    method decode (line 995) | def decode(self, codes, text, refer, noise_scale=0.5, speed=1, sv_emb=...
    method decode_streaming (line 1043) | def decode_streaming(self, codes, text, refer, noise_scale=0.5, speed=...
    method extract_latent (line 1094) | def extract_latent(self, x):
  class CFM (line 1100) | class CFM(torch.nn.Module):
    method __init__ (line 1101) | def __init__(self, in_channels, dit):
    method inference (line 1114) | def inference(self, mu, x_lens, prompt, n_timesteps, temperature=1.0, ...
    method forward (line 1174) | def forward(self, x1, x_lens, prompt_lens, mu, use_grad_ckpt):
  function set_no_grad (line 1210) | def set_no_grad(net_g):
  class SynthesizerTrnV3 (line 1215) | class SynthesizerTrnV3(nn.Module):
    method __init__ (line 1220) | def __init__(
    method forward (line 1301) | def forward(
    method decode_encp (line 1332) | def decode_encp(self, codes, text, refer, ge=None, speed=1):
    method extract_latent (line 1357) | def extract_latent(self, x):
  class SynthesizerTrnV3b (line 1363) | class SynthesizerTrnV3b(nn.Module):
    method __init__ (line 1368) | def __init__(
    method forward (line 1453) | def forward(self, ssl, y, mel, ssl_lengths, y_lengths, text, text_leng...
    method decode_encp (line 1496) | def decode_encp(self, codes, text, refer, ge=None):
    method extract_latent (line 1517) | def extract_latent(self, x):

FILE: GPT_SoVITS/module/models_onnx.py
  class StochasticDurationPredictor (line 23) | class StochasticDurationPredictor(nn.Module):
    method __init__ (line 24) | def __init__(
    method forward (line 64) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal...
  class DurationPredictor (line 112) | class DurationPredictor(nn.Module):
    method __init__ (line 113) | def __init__(self, in_channels, filter_channels, kernel_size, p_dropou...
    method forward (line 132) | def forward(self, x, x_mask, g=None):
  class TextEncoder (line 149) | class TextEncoder(nn.Module):
    method __init__ (line 150) | def __init__(
    method forward (line 207) | def forward(self, y, text, ge, speed=1):
  class ResidualCouplingBlock (line 229) | class ResidualCouplingBlock(nn.Module):
    method __init__ (line 230) | def __init__(
    method forward (line 264) | def forward(self, x, x_mask, g=None, reverse=False):
  class PosteriorEncoder (line 274) | class PosteriorEncoder(nn.Module):
    method __init__ (line 275) | def __init__(
    method forward (line 304) | def forward(self, x, x_lengths, g=None):
  class Encoder (line 316) | class Encoder(nn.Module):
    method __init__ (line 317) | def __init__(
    method forward (line 333) | def forward(self, x, x_lengths, g=None):
  class WNEncoder (line 343) | class WNEncoder(nn.Module):
    method __init__ (line 344) | def __init__(
    method forward (line 374) | def forward(self, x, x_lengths, g=None):
  class Generator (line 383) | class Generator(torch.nn.Module):
    method __init__ (line 384) | def __init__(
    method forward (line 428) | def forward(self, x, g: Optional[torch.Tensor] = None):
    method remove_weight_norm (line 449) | def remove_weight_norm(self):
  class DiscriminatorP (line 457) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 458) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=...
    method forward (line 514) | def forward(self, x):
  class DiscriminatorS (line 536) | class DiscriminatorS(torch.nn.Module):
    method __init__ (line 537) | def __init__(self, use_spectral_norm=False):
    method forward (line 552) | def forward(self, x):
  class MultiPeriodDiscriminator (line 566) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 567) | def __init__(self, use_spectral_norm=False):
    method forward (line 575) | def forward(self, y, y_hat):
  class ReferenceEncoder (line 591) | class ReferenceEncoder(nn.Module):
    method __init__ (line 597) | def __init__(self, spec_channels, gin_channels=0):
    method forward (line 626) | def forward(self, inputs):
    method calculate_channels (line 644) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs):
  class Quantizer_module (line 650) | class Quantizer_module(torch.nn.Module):
    method __init__ (line 651) | def __init__(self, n_e, e_dim):
    method forward (line 656) | def forward(self, x):
  class Quantizer (line 667) | class Quantizer(torch.nn.Module):
    method __init__ (line 668) | def __init__(self, embed_dim=512, n_code_groups=4, n_codes=160):
    method forward (line 677) | def forward(self, xin):
    method embed (line 696) | def embed(self, x):
  class CodePredictor (line 708) | class CodePredictor(nn.Module):
    method __init__ (line 709) | def __init__(
    method forward (line 738) | def forward(self, x, x_mask, refer, codes, infer=False):
  class SynthesizerTrn (line 769) | class SynthesizerTrn(nn.Module):
    method __init__ (line 774) | def __init__(
    method forward (line 879) | def forward(self, codes, text, refer, noise_scale=0.5, speed=1, sv_emb...
    method extract_latent (line 908) | def extract_latent(self, x):
  class CFM (line 914) | class CFM(torch.nn.Module):
    method __init__ (line 915) | def __init__(self, in_channels, dit):
    method forward (line 925) | def forward(
  function set_no_grad (line 962) | def set_no_grad(net_g):
  function compile_codes_length (line 968) | def compile_codes_length(codes):
  function compile_ref_length (line 974) | def compile_ref_length(refer):
  class SynthesizerTrnV3 (line 979) | class SynthesizerTrnV3(nn.Module):
    method __init__ (line 984) | def __init__(
    method create_ge (line 1065) | def create_ge(self, refer):
    method forward (line 1071) | def forward(self, codes, text, ge, speed=1):
    method extract_latent (line 1084) | def extract_latent(self, x):

FILE: GPT_SoVITS/module/modules.py
  class LayerNorm (line 20) | class LayerNorm(nn.Module):
    method __init__ (line 21) | def __init__(self, channels, eps=1e-5):
    method forward (line 29) | def forward(self, x):
  class ConvReluNorm (line 35) | class ConvReluNorm(nn.Module):
    method __init__ (line 36) | def __init__(
    method forward (line 73) | def forward(self, x, x_mask):
  class DDSConv (line 83) | class DDSConv(nn.Module):
    method __init__ (line 88) | def __init__(self, channels, kernel_size, n_layers, p_dropout=0.0):
    method forward (line 117) | def forward(self, x, x_mask, g=None):
  class WN (line 132) | class WN(torch.nn.Module):
    method __init__ (line 133) | def __init__(
    method forward (line 182) | def forward(self, x, x_mask, g=None, **kwargs):
    method remove_weight_norm (line 209) | def remove_weight_norm(self):
  class ResBlock1 (line 218) | class ResBlock1(torch.nn.Module):
    method __init__ (line 219) | def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
    method forward (line 293) | def forward(self, x, x_mask=None):
    method remove_weight_norm (line 308) | def remove_weight_norm(self):
  class ResBlock2 (line 315) | class ResBlock2(torch.nn.Module):
    method __init__ (line 316) | def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
    method forward (line 344) | def forward(self, x, x_mask=None):
    method remove_weight_norm (line 355) | def remove_weight_norm(self):
  class Log (line 360) | class Log(nn.Module):
    method forward (line 361) | def forward(self, x, x_mask, reverse=False, **kwargs):
  class Flip (line 371) | class Flip(nn.Module):
    method forward (line 372) | def forward(self, x, *args, reverse=False, **kwargs):
  class ElementwiseAffine (line 381) | class ElementwiseAffine(nn.Module):
    method __init__ (line 382) | def __init__(self, channels):
    method forward (line 388) | def forward(self, x, x_mask, reverse=False, **kwargs):
  class ResidualCouplingLayer (line 399) | class ResidualCouplingLayer(nn.Module):
    method __init__ (line 400) | def __init__(
    method forward (line 434) | def forward(self, x, x_mask, g=None, reverse=False):
  class ConvFlow (line 456) | class ConvFlow(nn.Module):
    method __init__ (line 457) | def __init__(
    method forward (line 481) | def forward(self, x, x_mask, g=None, reverse=False):
  class LinearNorm (line 512) | class LinearNorm(nn.Module):
    method __init__ (line 513) | def __init__(
    method forward (line 526) | def forward(self, input):
  class Mish (line 531) | class Mish(nn.Module):
    method __init__ (line 532) | def __init__(self):
    method forward (line 535) | def forward(self, x):
  class Conv1dGLU (line 539) | class Conv1dGLU(nn.Module):
    method __init__ (line 545) | def __init__(self, in_channels, out_channels, kernel_size, dropout):
    method forward (line 551) | def forward(self, x):
  class ConvNorm (line 560) | class ConvNorm(nn.Module):
    method __init__ (line 561) | def __init__(
    method forward (line 591) | def forward(self, input):
  class MultiHeadAttention (line 596) | class MultiHeadAttention(nn.Module):
    method __init__ (line 599) | def __init__(self, n_head, d_model, d_k, d_v, dropout=0.0, spectral_no...
    method forward (line 621) | def forward(self, x, mask=None):
  class ScaledDotProductAttention (line 649) | class ScaledDotProductAttention(nn.Module):
    method __init__ (line 652) | def __init__(self, temperature, dropout):
    method forward (line 658) | def forward(self, q, k, v, mask=None):
  class MelStyleEncoder (line 672) | class MelStyleEncoder(nn.Module):
    method __init__ (line 675) | def __init__(
    method temporal_avg_pool (line 716) | def temporal_avg_pool(self, x, mask=None):
    method forward (line 728) | def forward(self, x, mask=None):
  class MelStyleEncoderVAE (line 752) | class MelStyleEncoderVAE(nn.Module):
    method __init__ (line 753) | def __init__(self, spec_channels, z_latent_dim, emb_dim):
    method reparameterize (line 761) | def reparameterize(self, mu, logvar):
    method forward (line 769) | def forward(self, inputs, mask=None):
    method infer (line 782) | def infer(self, inputs=None, random_sample=False, manual_latent=None):
  class ActNorm (line 801) | class ActNorm(nn.Module):
    method __init__ (line 802) | def __init__(self, channels, ddi=False, **kwargs):
    method forward (line 810) | def forward(self, x, x_mask=None, g=None, reverse=False, **kwargs):
    method store_inverse (line 827) | def store_inverse(self):
    method set_ddi (line 830) | def set_ddi(self, ddi):
    method initialize (line 833) | def initialize(self, x, x_mask):
  class InvConvNear (line 848) | class InvConvNear(nn.Module):
    method __init__ (line 849) | def __init__(self, channels, n_split=4, no_jacobian=False, **kwargs):
    method forward (line 861) | def forward(self, x, x_mask=None, g=None, reverse=False, **kwargs):
    method store_inverse (line 896) | def store_inverse(self):

FILE: GPT_SoVITS/module/mrte_model.py
  class MRTE (line 9) | class MRTE(nn.Module):
    method __init__ (line 10) | def __init__(
    method forward (line 25) | def forward(self, ssl_enc, ssl_mask, text, text_mask, ge, test=None):
  class SpeakerEncoder (line 47) | class SpeakerEncoder(torch.nn.Module):
    method __init__ (line 48) | def __init__(
    method forward (line 60) | def forward(self, mels):
  class MELEncoder (line 67) | class MELEncoder(nn.Module):
    method __init__ (line 68) | def __init__(
    method forward (line 89) | def forward(self, x):
  class WN (line 97) | class WN(torch.nn.Module):
    method __init__ (line 98) | def __init__(self, hidden_channels, kernel_size, dilation_rate, n_laye...
    method forward (line 132) | def forward(self, x):
    method remove_weight_norm (line 150) | def remove_weight_norm(self):
  function fused_add_tanh_sigmoid_multiply (line 158) | def fused_add_tanh_sigmoid_multiply(input, n_channels):

FILE: GPT_SoVITS/module/quantize.py
  class QuantizedResult (line 19) | class QuantizedResult:
  class ResidualVectorQuantizer (line 27) | class ResidualVectorQuantizer(nn.Module):
    method __init__ (line 41) | def __init__(
    method forward (line 69) | def forward(
    method encode (line 93) | def encode(self, x: torch.Tensor, n_q: tp.Optional[int] = None, st: tp...
    method decode (line 107) | def decode(self, codes: torch.Tensor, st: int = 0) -> torch.Tensor:

FILE: GPT_SoVITS/module/transforms.py
  function piecewise_rational_quadratic_transform (line 12) | def piecewise_rational_quadratic_transform(
  function searchsorted (line 45) | def searchsorted(bin_locations, inputs, eps=1e-6):
  function unconstrained_rational_quadratic_spline (line 50) | def unconstrained_rational_quadratic_spline(
  function rational_quadratic_spline (line 100) | def rational_quadratic_spline(

FILE: GPT_SoVITS/onnx_export.py
  function spectrogram_torch (line 18) | def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, cente...
  class DictToAttrRecursive (line 42) | class DictToAttrRecursive(dict):
    method __init__ (line 43) | def __init__(self, input_dict):
    method __getattr__ (line 51) | def __getattr__(self, item):
    method __setattr__ (line 57) | def __setattr__(self, key, value):
    method __delattr__ (line 63) | def __delattr__(self, item):
  class T2SEncoder (line 70) | class T2SEncoder(nn.Module):
    method __init__ (line 71) | def __init__(self, t2s, vits):
    method forward (line 76) | def forward(self, ref_seq, text_seq, ref_bert, text_bert, ssl_content):
  class T2SModel (line 86) | class T2SModel(nn.Module):
    method __init__ (line 87) | def __init__(self, t2s_path, vits_model):
    method forward (line 106) | def forward(self, ref_seq, text_seq, ref_bert, text_bert, ssl_content):
    method export (line 132) | def export(self, ref_seq, text_seq, ref_bert, text_bert, ssl_content, ...
  class VitsModel (line 192) | class VitsModel(nn.Module):
    method __init__ (line 193) | def __init__(self, vits_path):
    method forward (line 213) | def forward(self, text_seq, pred_semantic, ref_audio):
  class GptSoVits (line 225) | class GptSoVits(nn.Module):
    method __init__ (line 226) | def __init__(self, vits, t2s):
    method forward (line 231) | def forward(self, ref_seq, text_seq, ref_bert, text_bert, ref_audio, s...
    method export (line 249) | def export(self, ref_seq, text_seq, ref_bert, text_bert, ref_audio, ss...
  class SSLModel (line 268) | class SSLModel(nn.Module):
    method __init__ (line 269) | def __init__(self):
    method forward (line 273) | def forward(self, ref_audio_16k):
  function export (line 277) | def export(vits_path, gpt_path, project_name, vits_model="v2"):

FILE: GPT_SoVITS/prepare_datasets/1-get-text.py
  function my_save (line 37) | def my_save(fea, path):  #####fix issue: torch.save doesn't support chin...
  function get_bert_feature (line 68) | def get_bert_feature(text, word2ph):
  function process (line 86) | def process(data, res):

FILE: GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py
  function my_save (line 45) | def my_save(fea, path):  #####fix issue: torch.save doesn't support chin...
  function name2go (line 78) | def name2go(wav_name, wav_path):

FILE: GPT_SoVITS/prepare_datasets/2-get-sv.py
  function my_save (line 33) | def my_save(fea, path):  #####fix issue: torch.save doesn't support chin...
  class SV (line 58) | class SV:
    method __init__ (line 59) | def __init__(self, device, is_half):
    method compute_embedding3 (line 72) | def compute_embedding3(self, wav):  # (1,x)#-1~1
  function name2go (line 87) | def name2go(wav_name, wav_path):

FILE: GPT_SoVITS/prepare_datasets/3-get-semantic.py
  function name2go (line 89) | def name2go(wav_name, lines):

FILE: GPT_SoVITS/process_ckpt.py
  function my_save (line 12) | def my_save(fea, path):  #####fix issue: torch.save doesn't support chin...
  function my_save2 (line 30) | def my_save2(fea, path, model_version):
  function savee (line 41) | def savee(ckpt, name, epoch, steps, hps, model_version=None, lora_rank=N...
  function get_hash_from_file (line 92) | def get_hash_from_file(sovits_path):
  function get_sovits_version_from_path_fast (line 100) | def get_sovits_version_from_path_fast(sovits_path):
  function load_sovits_new (line 129) | def load_sovits_new(sovits_path):

FILE: GPT_SoVITS/s1_train.py
  class my_model_ckpt (line 29) | class my_model_ckpt(ModelCheckpoint):
    method __init__ (line 30) | def __init__(
    method on_train_epoch_end (line 46) | def on_train_epoch_end(self, trainer, pl_module):
  function main (line 85) | def main(args):

FILE: GPT_SoVITS/s2_train.py
  function main (line 53) | def main():
  function run (line 71) | def run(rank, n_gpus, hps):
  function train_and_evaluate (line 318) | def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scale...
  function evaluate (line 582) | def evaluate(hps, generator, eval_loader, writer_eval):

FILE: GPT_SoVITS/s2_train_v3.py
  function main (line 53) | def main():
  function run (line 71) | def run(rank, n_gpus, hps):
  function train_and_evaluate (line 275) | def train_and_evaluate(

FILE: GPT_SoVITS/s2_train_v3_lora.py
  function main (line 53) | def main():
  function run (line 71) | def run(rank, n_gpus, hps):
  function train_and_evaluate (line 248) | def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scale...

FILE: GPT_SoVITS/stream_v2pro.py
  class StreamT2SModel (line 15) | class StreamT2SModel(nn.Module):
    method __init__ (line 16) | def __init__(self, t2s: T2SModel):
    method pre_infer (line 21) | def pre_infer(
    method decode_next_token (line 94) | def decode_next_token(
    method forward (line 141) | def forward(
  class StepVitsModel (line 154) | class StepVitsModel(nn.Module):
    method __init__ (line 155) | def __init__(self, vits: VitsModel,sv_model:ExportERes2NetV2):
    method ref_handle (line 162) | def ref_handle(self, ref_audio_32k):
    method extract_latent (line 177) | def extract_latent(self, ssl_content):
    method forward (line 181) | def forward(self, pred_semantic, text_seq, refer, sv_emb=None):
  function find_best_audio_offset_fast (line 188) | def find_best_audio_offset_fast(reference_audio: Tensor, search_audio: T...
  function test_stream (line 240) | def test_stream(
  function export_prov2 (line 438) | def export_prov2(

FILE: GPT_SoVITS/sv.py
  class SV (line 11) | class SV:
    method __init__ (line 12) | def __init__(self, device, is_half):
    method compute_embedding3 (line 24) | def compute_embedding3(self, wav):

FILE: GPT_SoVITS/text/LangSegmenter/langsegmenter.py
  function full_en (line 17) | def full_en(text):
  function full_cjk (line 22) | def full_cjk(text):
  function split_jako (line 48) | def split_jako(tag_lang,item):
  function merge_lang (line 69) | def merge_lang(lang_list, item):
  class LangSegmenter (line 77) | class LangSegmenter():
    method getTexts (line 90) | def getTexts(text,default_lang = ""):

FILE: GPT_SoVITS/text/__init__.py
  function cleaned_text_to_sequence (line 14) | def cleaned_text_to_sequence(cleaned_text, version=None):

FILE: GPT_SoVITS/text/cantonese.py
  function replace_punctuation (line 95) | def replace_punctuation(text):
  function text_normalize (line 106) | def text_normalize(text):
  function jyuping_to_initials_finals_tones (line 118) | def jyuping_to_initials_finals_tones(jyuping_syllables):
  function get_jyutping (line 176) | def get_jyutping(text):
  function get_bert_feature (line 197) | def get_bert_feature(text, word2ph):
  function g2p (line 203) | def g2p(text):

FILE: GPT_SoVITS/text/chinese.py
  function replace_punctuation (line 47) | def replace_punctuation(text):
  function replace_punctuation_with_en (line 58) | def replace_punctuation_with_en(text):
  function replace_consecutive_punctuation (line 69) | def replace_consecutive_punctuation(text):
  function g2p (line 76) | def g2p(text):
  function _get_initials_finals (line 83) | def _get_initials_finals(word):
  function _g2p (line 94) | def _g2p(segments):
  function text_normalize (line 171) | def text_normalize(text):

FILE: GPT_SoVITS/text/chinese2.py
  function replace_punctuation (line 62) | def replace_punctuation(text):
  function g2p (line 73) | def g2p(text):
  function _get_initials_finals (line 80) | def _get_initials_finals(word):
  function _merge_erhua (line 142) | def _merge_erhua(initials: list[str], finals: list[str], word: str, pos:...
  function _g2p (line 180) | def _g2p(segments):
  function replace_punctuation_with_en (line 298) | def replace_punctuation_with_en(text):
  function replace_consecutive_punctuation (line 309) | def replace_consecutive_punctuation(text):
  function text_normalize (line 316) | def text_normalize(text):

FILE: GPT_SoVITS/text/cleaner.py
  function clean_text (line 21) | def clean_text(text, language, version=None):
  function clean_special (line 58) | def clean_special(text, language, special_s, target_symbol, version=None):
  function text_to_sequence (line 85) | def text_to_sequence(text, language, version=None):

FILE: GPT_SoVITS/text/en_normalization/expend.py
  function _convert_ordinal (line 63) | def _convert_ordinal(m):
  function _remove_commas (line 75) | def _remove_commas(m):
  function _expand_time (line 79) | def _expand_time(m):
  function _expand_measurement (line 101) | def _expand_measurement(m):
  function _expand_pounds (line 117) | def _expand_pounds(m):
  function _expand_dollars (line 141) | def _expand_dollars(m):
  function _expand_decimal_number (line 169) | def _expand_decimal_number(m):
  function _expend_fraction (line 188) | def _expend_fraction(m):
  function _expand_ordinal (line 222) | def _expand_ordinal(m):
  function _expand_number (line 226) | def _expand_number(m):
  function replace_asmd (line 252) | def replace_asmd(match) -> str:
  function replace_negative_num (line 266) | def replace_negative_num(match) -> str:
  function normalize (line 281) | def normalize(text):

FILE: GPT_SoVITS/text/english.py
  function replace_phs (line 111) | def replace_phs(phs):
  function replace_consecutive_punctuation (line 124) | def replace_consecutive_punctuation(text):
  function read_dict (line 131) | def read_dict():
  function read_dict_new (line 155) | def read_dict_new():
  function hot_reload_hot (line 187) | def hot_reload_hot(g2p_dict):
  function cache_dict (line 205) | def cache_dict(g2p_dict, file_path):
  function get_dict (line 210) | def get_dict():
  function get_namedict (line 223) | def get_namedict():
  function text_normalize (line 233) | def text_normalize(text):
  class en_G2p (line 248) | class en_G2p(G2p):
    method __init__ (line 249) | def __init__(self):
    method __call__ (line 270) | def __call__(self, text):
    method qryword (line 309) | def qryword(self, o_word):
  function g2p (line 363) | def g2p(text):

FILE: GPT_SoVITS/text/g2pw/dataset.py
  function prepare_onnx_input (line 30) | def prepare_onnx_input(
  function _truncate_texts (line 97) | def _truncate_texts(window_size: int, texts: List[str], query_ids: List[...
  function _truncate (line 111) | def _truncate(
  function get_phoneme_labels (line 143) | def get_phoneme_labels(polyphonic_chars: List[List[str]]) -> Tuple[List[...
  function get_char_phoneme_labels (line 153) | def get_char_phoneme_labels(polyphonic_chars: List[List[str]]) -> Tuple[...

FILE: GPT_SoVITS/text/g2pw/g2pw.py
  class G2PWPinyin (line 19) | class G2PWPinyin(Pinyin):
    method __init__ (line 20) | def __init__(
    method get_seg (line 43) | def get_seg(self, **kwargs):
  class Converter (line 47) | class Converter(UltimateConverter):
    method __init__ (line 48) | def __init__(self, g2pw_instance, v_to_u=False, neutral_tone_with_five...
    method convert (line 55) | def convert(self, words, style, heteronym, errors, strict, **kwargs):
    method _to_pinyin (line 72) | def _to_pinyin(self, han, style, heteronym, errors, strict, **kwargs):
  function _remove_dup_items (line 90) | def _remove_dup_items(lst, remove_empty=False):
  function _remove_dup_and_empty (line 100) | def _remove_dup_and_empty(lst_list):
  function cache_dict (line 112) | def cache_dict(polyphonic_dict, file_path):
  function get_dict (line 117) | def get_dict():
  function read_dict (line 128) | def read_dict():
  function correct_pronunciation (line 147) | def correct_pronunciation(word, word_pinyins):

FILE: GPT_SoVITS/text/g2pw/onnx_api.py
  function predict (line 33) | def predict(session, onnx_input: Dict[str, Any], labels: List[str]) -> T...
  function download_and_decompress (line 58) | def download_and_decompress(model_dir: str = "G2PWModel/"):
  class G2PWOnnxConverter (line 82) | class G2PWOnnxConverter:
    method __init__ (line 83) | def __init__(
    method _convert_bopomofo_to_pinyin (line 178) | def _convert_bopomofo_to_pinyin(self, bopomofo: str) -> str:
    method __call__ (line 188) | def __call__(self, sentences: List[str]) -> List[List[str]]:
    method _prepare_data (line 226) | def _prepare_data(self, sentences: List[str]) -> Tuple[List[str], List...

FILE: GPT_SoVITS/text/g2pw/utils.py
  function wordize_and_map (line 23) | def wordize_and_map(text: str):
  function tokenize_and_map (line 59) | def tokenize_and_map(tokenizer, text: str):
  function _load_config (line 86) | def _load_config(config_path: os.PathLike):
  function load_config (line 132) | def load_config(config_path: os.PathLike, use_default: bool = False):

FILE: GPT_SoVITS/text/japanese.py
  function get_hash (line 50) | def get_hash(fp: str) -> str:
  function post_replace_ph (line 119) | def post_replace_ph(ph):
  function replace_consecutive_punctuation (line 138) | def replace_consecutive_punctuation(text):
  function symbols_to_japanese (line 145) | def symbols_to_japanese(text):
  function preprocess_jap (line 151) | def preprocess_jap(text, with_prosody=False):
  function text_normalize (line 174) | def text_normalize(text):
  function pyopenjtalk_g2p_prosody (line 183) | def pyopenjtalk_g2p_prosody(text, drop_unvoiced_vowels=True):
  function _numeric_feature_by_regex (line 260) | def _numeric_feature_by_regex(regex, s):
  function g2p (line 267) | def g2p(norm_text, with_prosody=True):

FILE: GPT_SoVITS/text/korean.py
  class win_G2p (line 14) | class win_G2p(G2p):
    method check_mecab (line 15) | def check_mecab(self):
  function fix_g2pk2_error (line 155) | def fix_g2pk2_error(text):
  function latin_to_hangul (line 170) | def latin_to_hangul(text):
  function divide_hangul (line 176) | def divide_hangul(text):
  function hangul_number (line 183) | def hangul_number(num, sino=True):
  function number_to_hangul (line 262) | def number_to_hangul(text):
  function korean_to_lazy_ipa (line 280) | def korean_to_lazy_ipa(text):
  function korean_to_ipa (line 292) | def korean_to_ipa(text):
  function post_replace_ph (line 301) | def post_replace_ph(ph):
  function g2p (line 324) | def g2p(text):

FILE: GPT_SoVITS/text/tone_sandhi.py
  class ToneSandhi (line 22) | class ToneSandhi:
    method __init__ (line 23) | def __init__(self):
    method _neural_sandhi (line 495) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li...
    method _bu_sandhi (line 539) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]:
    method _yi_sandhi (line 550) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]:
    method _split_word (line 573) | def _split_word(self, word: str) -> List[str]:
    method _three_sandhi (line 586) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]:
    method _all_tone_three (line 626) | def _all_tone_three(self, finals: List[str]) -> bool:
    method _merge_bu (line 631) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
    method _merge_yi (line 651) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
    method _merge_continuous_three_tones (line 679) | def _merge_continuous_three_tones(self, seg: List[Tuple[str, str]]) ->...
    method _is_reduplication (line 704) | def _is_reduplication(self, word: str) -> bool:
    method _merge_continuous_three_tones_2 (line 708) | def _merge_continuous_three_tones_2(self, seg: List[Tuple[str, str]]) ...
    method _merge_er (line 732) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
    method _merge_reduplication (line 741) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup...
    method pre_merge_for_modify (line 750) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup...
    method modified_tone (line 769) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis...

FILE: GPT_SoVITS/text/zh_normalization/char_convert.py
  function tranditional_to_simplified (line 30) | def tranditional_to_simplified(text: str) -> str:
  function simplified_to_traditional (line 34) | def simplified_to_traditional(text: str) -> str:

FILE: GPT_SoVITS/text/zh_normalization/chronology.py
  function _time_num2str (line 22) | def _time_num2str(num_string: str) -> str:
  function replace_time (line 49) | def replace_time(match) -> str:
  function replace_date (line 98) | def replace_date(match) -> str:
  function replace_date2 (line 122) | def replace_date2(match) -> str:

FILE: GPT_SoVITS/text/zh_normalization/num.py
  function replace_frac (line 40) | def replace_frac(match) -> str:
  function replace_percentage (line 61) | def replace_percentage(match) -> str:
  function replace_negative_num (line 81) | def replace_negative_num(match) -> str:
  function replace_default_num (line 101) | def replace_default_num(match):
  function replace_asmd (line 122) | def replace_asmd(match) -> str:
  function replace_power (line 153) | def replace_power(match) -> str:
  function replace_positive_quantifier (line 175) | def replace_positive_quantifier(match) -> str:
  function replace_number (line 194) | def replace_number(match) -> str:
  function replace_range (line 228) | def replace_range(match) -> str:
  function replace_to_range (line 248) | def replace_to_range(match) -> str:
  function replace_vrsion_num (line 260) | def replace_vrsion_num(match) -> str:
  function _get_value (line 277) | def _get_value(value_string: str, use_zero: bool = True) -> List[str]:
  function verbalize_cardinal (line 293) | def verbalize_cardinal(value_string: str) -> str:
  function verbalize_digit (line 309) | def verbalize_digit(value_string: str, alt_one=False) -> str:
  function num2str (line 317) | def num2str(value_string: str) -> str:

FILE: GPT_SoVITS/text/zh_normalization/phonecode.py
  function phone2str (line 31) | def phone2str(phone_string: str, mobile=True) -> str:
  function replace_phone (line 42) | def replace_phone(match) -> str:
  function replace_mobile (line 52) | def replace_mobile(match) -> str:

FILE: GPT_SoVITS/text/zh_normalization/quantifier.py
  function replace_temperature (line 42) | def replace_temperature(match) -> str:
  function replace_measure (line 59) | def replace_measure(sentence) -> str:

FILE: GPT_SoVITS/text/zh_normalization/text_normlization.py
  class TextNormalizer (line 61) | class TextNormalizer:
    method __init__ (line 62) | def __init__(self):
    method _split (line 65) | def _split(self, text: str, lang="zh") -> List[str]:
    method _post_replace (line 82) | def _post_replace(self, sentence: str) -> str:
    method normalize_sentence (line 130) | def normalize_sentence(self, sentence: str) -> str:
    method normalize (line 172) | def normalize(self, text: str) -> List[str]:

FILE: GPT_SoVITS/utils.py
  function load_checkpoint (line 23) | def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimiz...
  function my_save (line 67) | def my_save(fea, path):  #####fix issue: torch.save doesn't support chin...
  function save_checkpoint (line 75) | def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoi...
  function summarize (line 93) | def summarize(
  function latest_checkpoint_path (line 112) | def latest_checkpoint_path(dir_path, regex="G_*.pth"):
  function plot_spectrogram_to_numpy (line 120) | def plot_spectrogram_to_numpy(spectrogram):
  function plot_alignment_to_numpy (line 145) | def plot_alignment_to_numpy(alignment, info=None):
  function load_wav_to_torch (line 178) | def load_wav_to_torch(full_path):
  function load_filepaths_and_text (line 183) | def load_filepaths_and_text(filename, split="|"):
  function get_hparams (line 189) | def get_hparams(init=True, stage=1):
  function clean_checkpoints (line 236) | def clean_checkpoints(path_to_models="logs/44k/", n_ckpts_to_keep=2, sor...
  function get_hparams_from_dir (line 263) | def get_hparams_from_dir(model_dir):
  function get_hparams_from_file (line 274) | def get_hparams_from_file(config_path):
  function check_git_hash (line 283) | def check_git_hash(model_dir):
  function get_logger (line 309) | def get_logger(model_dir, filename="train.log"):
  class HParams (line 324) | class HParams:
    method __init__ (line 325) | def __init__(self, **kwargs):
    method keys (line 331) | def keys(self):
    method items (line 334) | def items(self):
    method values (line 337) | def values(self):
    method __len__ (line 340) | def __len__(self):
    method __getitem__ (line 343) | def __getitem__(self, key):
    method __setitem__ (line 346) | def __setitem__(self, key, value):
    method __contains__ (line 349) | def __contains__(self, key):
    method __repr__ (line 352) | def __repr__(self):

FILE: api.py
  class DefaultRefer (line 177) | class DefaultRefer:
    method __init__ (line 178) | def __init__(self, path, text, language):
    method is_ready (line 183) | def is_ready(self) -> bool:
  function is_empty (line 187) | def is_empty(*items):  # 任意一项不为空返回False
  function is_full (line 194) | def is_full(*items):  # 任意一项为空返回False
  function clean_hifigan_model (line 204) | def clean_hifigan_model():
  function clean_bigvgan_model (line 215) | def clean_bigvgan_model():
  function clean_sv_cn_model (line 226) | def clean_sv_cn_model():
  function init_bigvgan (line 237) | def init_bigvgan():
  function init_hifigan (line 255) | def init_hifigan():
  function init_sv_cn (line 285) | def init_sv_cn():
  function resample (line 293) | def resample(audio_tensor, sr0, sr1, device):
  function norm_spec (line 307) | def norm_spec(x):
  function denorm_spec (line 311) | def denorm_spec(x):
  function audio_sr (line 346) | def audio_sr(audio, sr):
  class Speaker (line 359) | class Speaker:
    method __init__ (line 360) | def __init__(self, name, gpt, sovits, phones=None, bert=None, prompt=N...
  class Sovits (line 372) | class Sovits:
    method __init__ (line 373) | def __init__(self, vq_model, hps):
  function get_sovits_weights (line 381) | def get_sovits_weights(sovits_path):
  class Gpt (line 467) | class Gpt:
    method __init__ (line 468) | def __init__(self, max_sec, t2s_model):
  function get_gpt_weights (line 477) | def get_gpt_weights(gpt_path):
  function change_gpt_sovits_weights (line 494) | def change_gpt_sovits_weights(gpt_path, sovits_path):
  function get_bert_feature (line 505) | def get_bert_feature(text, word2ph):
  function clean_text_inf (line 522) | def clean_text_inf(text, language, version):
  function get_bert_inf (line 529) | def get_bert_inf(phones, word2ph, norm_text, language):
  function get_phones_and_bert (line 545) | def get_phones_and_bert(text, language, version, final=False):
  class DictToAttrRecursive (line 612) | class DictToAttrRecursive(dict):
    method __init__ (line 613) | def __init__(self, input_dict):
    method __getattr__ (line 621) | def __getattr__(self, item):
    method __setattr__ (line 627) | def __setattr__(self, key, value):
    method __delattr__ (line 633) | def __delattr__(self, item):
  function get_spepc (line 640) | def get_spepc(hps, filename, dtype, device, is_v2pro=False):
  function pack_audio (line 670) | def pack_audio(audio_bytes, data, rate):
  function pack_ogg (line 682) | def pack_ogg(audio_bytes, data, rate):
  function pack_raw (line 728) | def pack_raw(audio_bytes, data, rate):
  function pack_wav (line 734) | def pack_wav(audio_bytes, rate):
  function pack_aac (line 746) | def pack_aac(audio_bytes, data, rate):
  function read_clean_buffer (line 783) | def read_clean_buffer(audio_bytes):
  function cut_text (line 791) | def cut_text(text, punc):
  function only_punc (line 809) | def only_punc(text):
  function get_tts_wav (line 830) | def get_tts_wav(
  function handle_control (line 1071) | def handle_control(command):
  function handle_change (line 1079) | def handle_change(path, text, language):
  function handle (line 1100) | def handle(
  function set_model (line 1302) | async def set_model(request: Request):
  function set_model (line 1310) | async def set_model(
  function control (line 1318) | async def control(request: Request):
  function control (line 1324) | async def control(command: str = None):
  function change_refer (line 1329) | async def change_refer(request: Request):
  function change_refer (line 1337) | async def change_refer(refer_wav_path: str = None, prompt_text: str = No...
  function tts_endpoint (line 1342) | async def tts_endpoint(request: Request):
  function tts_endpoint (line 1362) | async def tts_endpoint(

FILE: api_v2.py
  class TTS_Request (line 154) | class TTS_Request(BaseModel):
  function pack_ogg (line 181) | def pack_ogg(io_buffer: BytesIO, data: np.ndarray, rate: int):
  function pack_raw (line 227) | def pack_raw(io_buffer: BytesIO, data: np.ndarray, rate: int):
  function pack_wav (line 232) | def pack_wav(io_buffer: BytesIO, data: np.ndarray, rate: int):
  function pack_aac (line 238) | def pack_aac(io_buffer: BytesIO, data: np.ndarray, rate: int):
  function pack_audio (line 268) | def pack_audio(io_buffer: BytesIO, data: np.ndarray, rate: int, media_ty...
  function wave_header_chunk (line 282) | def wave_header_chunk(frame_input=b"", channels=1, sample_width=2, sampl...
  function handle_control (line 297) | def handle_control(command: str):
  function check_params (line 305) | def check_params(req: dict):
  function tts_handle (line 345) | async def tts_handle(req: dict):
  function control (line 449) | async def control(command: str = None):
  function tts_get_endpoint (line 456) | async def tts_get_endpoint(
  function tts_post_endpoint (line 512) | async def tts_post_endpoint(request: TTS_Request):
  function set_refer_aduio (line 518) | async def set_refer_aduio(refer_audio_path: str = None):
  function set_gpt_weights (line 546) | async def set_gpt_weights(weights_path: str = None):
  function set_sovits_weights (line 558) | async def set_sovits_weights(weights_path: str = None):

FILE: config.py
  function custom_sort_key (line 78) | def custom_sort_key(s):
  function get_weights_names (line 86) | def get_weights_names():
  function change_choices (line 116) | def change_choices():
  function get_device_dtype_sm (line 149) | def get_device_dtype_sm(idx: int) -> tuple[torch.device, torch.dtype, fl...
  class Config (line 198) | class Config:
    method __init__ (line 199) | def __init__(self):

FILE: tools/AP_BWE_main/datasets1/dataset.py
  function amp_pha_stft (line 9) | def amp_pha_stft(audio, n_fft, hop_size, win_size, center=True):
  function amp_pha_istft (line 30) | def amp_pha_istft(log_amp, pha, n_fft, hop_size, win_size, center=True):
  function get_dataset_filelist (line 39) | def get_dataset_filelist(a):
  class Dataset (line 49) | class Dataset(torch.utils.data.Dataset):
    method __init__ (line 50) | def __init__(
    method __getitem__ (line 76) | def __getitem__(self, index):
    method __len__ (line 107) | def __len__(self):

FILE: tools/AP_BWE_main/models/model.py
  function get_padding (line 8) | def get_padding(kernel_size, dilation=1):
  function init_weights (line 12) | def init_weights(m, mean=0.0, std=0.01):
  class ConvNeXtBlock (line 24) | class ConvNeXtBlock(nn.Module):
    method __init__ (line 36) | def __init__(
    method forward (line 56) | def forward(self, x, cond_embedding_id=None):
  class APNet_BWE_Model (line 76) | class APNet_BWE_Model(torch.nn.Module):
    method __init__ (line 77) | def __init__(self, h):
    method _init_weights (line 117) | def _init_weights(self, m):
    method forward (line 122) | def forward(self, mag_nb, pha_nb):
  class DiscriminatorP (line 147) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 148) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=...
    method forward (line 163) | def forward(self, x):
  class MultiPeriodDiscriminator (line 186) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 187) | def __init__(self):
    method forward (line 199) | def forward(self, y, y_hat):
  class MultiResolutionAmplitudeDiscriminator (line 215) | class MultiResolutionAmplitudeDiscriminator(nn.Module):
    method __init__ (line 216) | def __init__(
    method forward (line 226) | def forward(
  class DiscriminatorAR (line 245) | class DiscriminatorAR(nn.Module):
    method __init__ (line 246) | def __init__(
    method forward (line 270) | def forward(
    method spectrogram (line 294) | def spectrogram(self, x: torch.Tensor) -> torch.Tensor:
  class MultiResolutionPhaseDiscriminator (line 309) | class MultiResolutionPhaseDiscriminator(nn.Module):
    method __init__ (line 310) | def __init__(
    method forward (line 320) | def forward(
  class DiscriminatorPR (line 339) | class DiscriminatorPR(nn.Module):
    method __init__ (line 340) | def __init__(
    method forward (line 364) | def forward(
    method spectrogram (line 388) | def spectrogram(self, x: torch.Tensor) -> torch.Tensor:
  function feature_loss (line 403) | def feature_loss(fmap_r, fmap_g):
  function discriminator_loss (line 412) | def discriminator_loss(disc_real_outputs, disc_generated_outputs):
  function generator_loss (line 426) | def generator_loss(disc_outputs):
  function phase_losses (line 437) | def phase_losses(phase_r, phase_g):
  function anti_wrapping_function (line 445) | def anti_wrapping_function(x):
  function stft_mag (line 449) | def stft_mag(audio, n_fft=2048, hop_length=512):
  function cal_snr (line 456) | def cal_snr(pred, target):
  function cal_lsd (line 461) | def cal_lsd(pred, target):

FILE: tools/asr/config.py
  function get_models (line 1) | def get_models():

FILE: tools/asr/fasterwhisper_asr.py
  function download_model (line 42) | def download_model(model_size: str):
  function execute_asr (line 104) | def execute_asr(input_folder, output_folder, model_path, language, preci...

FILE: tools/asr/funasr_asr.py
  function only_asr (line 14) | def only_asr(input_file, language):
  function create_model (line 24) | def create_model(language="zh"):
  function execute_asr (line 73) | def execute_asr(input_folder, output_folder, model_size, language):

FILE: tools/audio_sr.py
  class AP_BWE (line 16) | class AP_BWE:
    method __init__ (line 17) | def __init__(self, device, DictToAttrRecursive, checkpoint_file=None):
    method to (line 36) | def to(self, *arg, **kwargs):
    method __call__ (line 41) | def __call__(self, audio, orig_sampling_rate):

FILE: tools/cmd-denoise.py
  function execute_denoise (line 14) | def execute_denoise(input_folder, output_folder):

FILE: tools/i18n/i18n.py
  function load_language_list (line 8) | def load_language_list(language):
  function scan_language_list (line 14) | def scan_language_list():
  class I18nAuto (line 22) | class I18nAuto:
    method __init__ (line 23) | def __init__(self, language=None):
    method __call__ (line 32) | def __call__(self, key):
    method __repr__ (line 35) | def __repr__(self):

FILE: tools/i18n/scan_i18n.py
  function extract_i18n_strings (line 15) | def extract_i18n_strings(node):
  function scan_i18n_strings (line 29) | def scan_i18n_strings():
  function update_i18n_json (line 56) | def update_i18n_json(json_file, standard_keys):

FILE: tools/my_utils.py
  function load_audio (line 16) | def load_audio(file, sr):
  function clean_path (line 40) | def clean_path(path_str: str):
  function check_for_existance (line 49) | def check_for_existance(file_list: list = None, is_train=False, is_datas...
  function check_details (line 90) | def check_details(path_list=None, is_train=False, is_dataset_processing=...
  function load_cudnn (line 140) | def load_cudnn():
  function load_nvrtc (line 187) | def load_nvrtc():

FILE: tools/slice_audio.py
  function slice (line 13) | def slice(inp, opt_root, threshold, min_length, min_interval, hop_size, ...

FILE: tools/slicer2.py
  function get_rms (line 5) | def get_rms(
  class Slicer (line 38) | class Slicer:
    method __init__ (line 39) | def __init__(
    method _apply_slice (line 60) | def _apply_slice(self, waveform, begin, end):
    method slice (line 67) | def slice(self, waveform):
  function main (line 155) | def main():

FILE: tools/subfix_webui.py
  function reload_data (line 38) | def reload_data(index, batch):
  function b_change_index (line 50) | def b_change_index(index, batch):
  function b_next_index (line 80) | def b_next_index(index, batch):
  function b_previous_index (line 88) | def b_previous_index(index, batch):
  function b_submit_change (line 96) | def b_submit_change(*text_list):
  function b_delete_audio (line 110) | def b_delete_audio(*checkbox_list):
  function b_invert_selection (line 134) | def b_invert_selection(*checkbox_list):
  function get_next_path (line 139) | def get_next_path(filename):
  function b_audio_split (line 149) | def b_audio_split(audio_breakpoint, *checkbox_list):
  function b_merge_audio (line 178) | def b_merge_audio(interval_r, *checkbox_list):
  function b_save_json (line 222) | def b_save_json():
  function b_save_list (line 228) | def b_save_list():
  function b_load_json (line 238) | def b_load_json():
  function b_load_list (line 246) | def b_load_list():
  function b_save_file (line 262) | def b_save_file():
  function b_load_file (line 269) | def b_load_file():
  function set_global (line 276) | def set_global(load_json, load_list, json_key_text, json_key_path, batch):

FILE: tools/uvr5/bs_roformer/attend.py
  function exists (line 7) | def exists(val):
  function default (line 11) | def default(v, d):
  class Attend (line 15) | class Attend(nn.Module):
    method __init__ (line 16) | def __init__(self, dropout=0.0, flash=False, scale=None):
    method flash_attn (line 27) | def flash_attn(self, q, k, v):
    method forward (line 38) | def forward(self, q, k, v):

FILE: tools/uvr5/bs_roformer/bs_roformer.py
  function exists (line 23) | def exists(val):
  function default (line 27) | def default(v, d):
  function pack_one (line 31) | def pack_one(t, pattern):
  function unpack_one (line 35) | def unpack_one(t, ps, pattern):
  function l2norm (line 42) | def l2norm(t):
  class RMSNorm (line 46) | class RMSNorm(Module):
    method __init__ (line 47) | def __init__(self, dim):
    method forward (line 52) | def forward(self, x):
  class FeedForward (line 59) | class FeedForward(Module):
    method __init__ (line 60) | def __init__(self, dim, mult=4, dropout=0.0):
    method forward (line 72) | def forward(self, x):
  class Attention (line 76) | class Attention(Module):
    method __init__ (line 77) | def __init__(self, dim, heads=8, dim_head=64, dropout=0.0, rotary_embe...
    method forward (line 94) | def forward(self, x):
  class LinearAttention (line 112) | class LinearAttention(Module):
    method __init__ (line 118) | def __init__(self, *, dim, dim_head=32, heads=8, scale=8, flash=False,...
    method forward (line 133) | def forward(self, x):
  class Transformer (line 146) | class Transformer(Module):
    method __init__ (line 147) | def __init__(
    method forward (line 182) | def forward(self, x):
  class BandSplit (line 193) | class BandSplit(Module):
    method __init__ (line 195) | def __init__(self, dim, dim_inputs: Tuple[int, ...]):
    method forward (line 205) | def forward(self, x):
  function MLP (line 216) | def MLP(dim_in, dim_out, dim_hidden=None, depth=1, activation=nn.Tanh):
  class MaskEstimator (line 235) | class MaskEstimator(Module):
    method __init__ (line 237) | def __init__(self, dim, dim_inputs: Tuple[int, ...], depth, mlp_expans...
    method forward (line 250) | def forward(self, x):
  class BSRoformer (line 330) | class BSRoformer(Module):
    method __init__ (line 332) | def __init__(
    method forward (line 443) | def forward(self, raw_audio, target=None, return_loss_breakdown=False):

FILE: tools/uvr5/bs_roformer/mel_band_roformer.py
  function exists (line 26) | def exists(val):
  function default (line 30) | def default(v, d):
  function pack_one (line 34) | def pack_one(t, pattern):
  function unpack_one (line 38) | def unpack_one(t, ps, pattern):
  function pad_at_dim (line 42) | def pad_at_dim(t, pad, dim=-1, value=0.0):
  function l2norm (line 48) | def l2norm(t):
  class RMSNorm (line 55) | class RMSNorm(Module):
    method __init__ (line 56) | def __init__(self, dim):
    method forward (line 61) | def forward(self, x):
  class FeedForward (line 68) | class FeedForward(Module):
    method __init__ (line 69) | def __init__(self, dim, mult=4, dropout=0.0):
    method forward (line 81) | def forward(self, x):
  class Attention (line 85) | class Attention(Module):
    method __init__ (line 86) | def __init__(self, dim, heads=8, dim_head=64, dropout=0.0, rotary_embe...
    method forward (line 103) | def forward(self, x):
  class LinearAttention (line 121) | class LinearAttention(Module):
    method __init__ (line 127) | def __init__(self, *, dim, dim_head=32, heads=8, scale=8, flash=False,...
    method forward (line 142) | def forward(self, x):
  class Transformer (line 155) | class Transformer(Module):
    method __init__ (line 156) | def __init__(
    method forward (line 191) | def forward(self, x):
  class BandSplit (line 202) | class BandSplit(Module):
    method __init__ (line 204) | def __init__(self, dim, dim_inputs: Tuple[int, ...]):
    method forward (line 214) | def forward(self, x):
  function MLP (line 225) | def MLP(dim_in, dim_out, dim_hidden=None, depth=1, activation=nn.Tanh):
  class MaskEstimator (line 244) | class MaskEstimator(Module):
    method __init__ (line 246) | def __init__(self, dim, dim_inputs: Tuple[int, ...], depth, mlp_expans...
    method forward (line 259) | def forward(self, x):
  class MelBandRoformer (line 274) | class MelBandRoformer(Module):
    method __init__ (line 276) | def __init__(
    method forward (line 422) | def forward(self, raw_audio, target=None, return_loss_breakdown=False):

FILE: tools/uvr5/bsroformer.py
  class Roformer_Loader (line 16) | class Roformer_Loader:
    method get_config (line 17) | def get_config(self, config_path):
    method get_default_config (line 23) | def get_default_config(self):
    method get_model_from_config (line 97) | def get_model_from_config(self):
    method demix_track (line 111) | def demix_track(self, model, mix, device):
    method run_folder (line 199) | def run_folder(self, input, vocal_root, others_root, format):
    method save_audio (line 248) | def save_audio(self, path, data, sr, format):
    method __init__ (line 262) | def __init__(self, model_path, config_path, device, is_half):
    method _path_audio_ (line 303) | def _path_audio_(self, input, others_root, vocal_root, format, is_hp3=...

FILE: tools/uvr5/mdxnet.py
  class ConvTDFNetTrim (line 15) | class ConvTDFNetTrim:
    method __init__ (line 16) | def __init__(self, device, model_name, target_name, L, dim_f, dim_t, n...
    method stft (line 35) | def stft(self, x):
    method istft (line 50) | def istft(self, x, freq_pad=None):
  function get_models (line 62) | def get_models(device, dim_f, dim_t, n_fft):
  class Predictor (line 74) | class Predictor:
    method __init__ (line 75) | def __init__(self, args):
    method demix (line 91) | def demix(self, mix):
    method demix_base (line 125) | def demix_base(self, mixes, margin_size):
    method prediction (line 172) | def prediction(self, m, vocal_root, others_root, format):
  class MDXNetDereverb (line 208) | class MDXNetDereverb:
    method __init__ (line 209) | def __init__(self, chunks):
    method _path_audio_ (line 222) | def _path_audio_(self, input, others_root, vocal_root, format, is_hp3=...

FILE: tools/uvr5/vr.py
  class AudioPre (line 19) | class AudioPre:
    method __init__ (line 20) | def __init__(self, agg, model_path, device, is_half, tta=False):
    method _path_audio_ (line 45) | def _path_audio_(self, music_file, ins_root=None, vocal_root=None, for...
  class AudioPreDeEcho (line 190) | class AudioPreDeEcho:
    method __init__ (line 191) | def __init__(self, agg, model_path, device, is_half, tta=False):
    method _path_audio_ (line 217) | def _path_audio_(

FILE: tools/uvr5/webui.py
  function html_left (line 33) | def html_left(text, label="p"):
  function html_center (line 39) | def html_center(text, label="p"):
  function uvr (line 45) | def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg...

FILE: webui.py
  function set_default (line 104) | def set_default():
  function fix_gpu_number (line 145) | def fix_gpu_number(input):  # 将越界的number强制改到界内
  function fix_gpu_numbers (line 154) | def fix_gpu_numbers(inputs):
  function check_pretrained_is_exist (line 167) | def check_pretrained_is_exist(version):
  function kill_proc_tree (line 211) | def kill_proc_tree(pid, including_parent=True):
  function kill_process (line 234) | def kill_process(pid, process_name=""):
  function process_info (line 244) | def process_info(process_name="", indicator=""):
  function change_label (line 270) | def change_label(path_list):
  function change_uvr5 (line 301) | def change_uvr5():
  function change_tts_inference (line 331) | def change_tts_inference(bert_path, cnhubert_base_path, gpu_number, gpt_...
  function open_asr (line 371) | def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_la...
  function close_asr (line 417) | def close_asr():
  function open_denoise (line 432) | def open_denoise(denoise_inp_dir, denoise_opt_dir):
  function close_denoise (line 473) | def close_denoise():
  function open1Ba (line 489) | def open1Ba(
  function close1Ba (line 574) | def close1Ba():
  function open1Bb (line 590) | def open1Bb(
  function close1Bb (line 666) | def close1Bb():
  function open_slice (line 682) | def open_slice(inp, opt_root, threshold, min_length, min_interval, hop_s...
  function close_slice (line 760) | def close_slice():
  function open1a (line 780) | def open1a(inp_text, inp_wav_dir, exp_name, gpu_numbers, bert_pretrained...
  function close1a (line 849) | def close1a():
  function open1b (line 870) | def open1b(version, inp_text, inp_wav_dir, exp_name, gpu_numbers, ssl_pr...
  function close1b (line 940) | def close1b():
  function open1c (line 960) | def open1c(version, inp_text, inp_wav_dir, exp_name, gpu_numbers, pretra...
  function close1c (line 1026) | def close1c():
  function open1abc (line 1046) | def open1abc(
  function close1abc (line 1248) | def close1abc():
  function switch_version (line 1264) | def switch_version(version_):
  function sync (line 1301) | def sync(text):
  function change_lang_choices (line 1434) | def change_lang_choices(key):  # 根据选择的模型修改可选的语言
  function change_size_choices (line 1437) | def change_size_choices(key):  # 根据选择的模型修改可选的模型尺寸
  function change_precision_choices (line 1440) | def change_precision_choices(key):  # 根据选择的模型修改可选的语言