SYMBOL INDEX (1717 symbols across 145 files) FILE: attentions.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class Decoder (line 123) | class Decoder(nn.Module): method __init__ (line 124) | def __init__( method forward (line 183) | def forward(self, x, x_mask, h, h_mask): class MultiHeadAttention (line 209) | class MultiHeadAttention(nn.Module): method __init__ (line 210) | def __init__( method forward (line 263) | def forward(self, x, c, attn_mask=None): method attention (line 273) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 324) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 333) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 342) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 360) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 381) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 397) | def _attention_bias_proximal(self, length): class FFN (line 409) | class FFN(nn.Module): method __init__ (line 410) | def __init__( method forward (line 438) | def forward(self, x, x_mask): method _causal_padding (line 448) | def _causal_padding(self, x): method _same_padding (line 457) | def _same_padding(self, x): FILE: bert_gen.py function process_line (line 12) | def process_line(x): FILE: 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 convert_pad_shape (line 16) | def convert_pad_shape(pad_shape): 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 37) | def rand_gumbel(shape): function rand_gumbel_like (line 43) | def rand_gumbel_like(x): function slice_segments (line 48) | 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 81) | def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4): function cat_timing_signal_1d (line 87) | def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis... function subsequent_mask (line 93) | def subsequent_mask(length): function fused_add_tanh_sigmoid_multiply (line 99) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): function convert_pad_shape (line 108) | def convert_pad_shape(pad_shape): function shift_1d (line 114) | def shift_1d(x): function sequence_mask (line 119) | def sequence_mask(length, max_length=None): function generate_path (line 126) | def generate_path(duration, mask): function clip_grad_value_ (line 143) | def clip_grad_value_(parameters, clip_value, norm_type=2): FILE: compress_model.py function copyStateDict (line 11) | def copyStateDict(state_dict): function removeOptimizer (line 23) | def removeOptimizer(config: str, input_model: str, ishalf: bool, output_... FILE: config.py class Resample_config (line 13) | class Resample_config: method __init__ (line 16) | def __init__(self, in_dir: str, out_dir: str, sampling_rate: int = 441... method from_dict (line 22) | def from_dict(cls, dataset_path: str, data: Dict[str, any]): class Preprocess_text_config (line 32) | class Preprocess_text_config: method __init__ (line 35) | def __init__( method from_dict (line 66) | def from_dict(cls, dataset_path: str, data: Dict[str, any]): class Bert_gen_config (line 83) | class Bert_gen_config: method __init__ (line 86) | def __init__( method from_dict (line 99) | def from_dict(cls, dataset_path: str, data: Dict[str, any]): class Emo_gen_config (line 105) | class Emo_gen_config: method __init__ (line 108) | def __init__( method from_dict (line 121) | def from_dict(cls, dataset_path: str, data: Dict[str, any]): class Train_ms_config (line 127) | class Train_ms_config: method __init__ (line 130) | def __init__( method from_dict (line 151) | def from_dict(cls, dataset_path: str, data: Dict[str, any]): class Webui_config (line 158) | class Webui_config: method __init__ (line 161) | def __init__( method from_dict (line 182) | def from_dict(cls, dataset_path: str, data: Dict[str, any]): class Server_config (line 188) | class Server_config: method __init__ (line 189) | def __init__( method from_dict (line 197) | def from_dict(cls, data: Dict[str, any]): class Translate_config (line 201) | class Translate_config: method __init__ (line 204) | def __init__(self, app_key: str, secret_key: str): method from_dict (line 209) | def from_dict(cls, data: Dict[str, any]): class Config (line 213) | class Config: method __init__ (line 214) | def __init__(self, config_path: str): FILE: data_utils.py class TextAudioSpeakerLoader (line 16) | class TextAudioSpeakerLoader(torch.utils.data.Dataset): method __init__ (line 23) | def __init__(self, audiopaths_sid_text, hparams): method _filter (line 50) | def _filter(self): method get_audio_text_speaker_pair (line 85) | def get_audio_text_speaker_pair(self, audiopath_sid_text): method get_audio (line 98) | def get_audio(self, filename): method get_text (line 140) | def get_text(self, text, word2ph, phone, tone, language_str, wav_path): method get_sid (line 174) | def get_sid(self, sid): method __getitem__ (line 178) | def __getitem__(self, index): method __len__ (line 181) | def __len__(self): class TextAudioSpeakerCollate (line 185) | class TextAudioSpeakerCollate: method __init__ (line 188) | def __init__(self, return_ids=False): method __call__ (line 191) | def __call__(self, batch): class DistributedBucketSampler (line 277) | class DistributedBucketSampler(torch.utils.data.distributed.DistributedS... method __init__ (line 287) | def __init__( method _create_buckets (line 305) | def _create_buckets(self): method __iter__ (line 337) | def __iter__(self): method _bisect (line 388) | def _bisect(self, x, lo=0, hi=None): method __len__ (line 403) | def __len__(self): FILE: for_deploy/infer.py function get_net_g (line 78) | def get_net_g(model_path: str, version: str, device: str, hps): function get_text (line 101) | def get_text(text, language_str, bert, hps, device): function infer (line 143) | def infer( function infer_multilang (line 290) | def infer_multilang( FILE: for_deploy/infer_utils.py class BertFeature (line 17) | class BertFeature: method __init__ (line 18) | def __init__(self, model_path, language="ZH"): method _get_device (line 27) | def _get_device(self, device=config.bert_gen_config.device): method _prepare (line 38) | def _prepare(self): method get_bert_feature (line 51) | def get_bert_feature(self, text, word2ph): class ClapFeature (line 72) | class ClapFeature: method __init__ (line 73) | def __init__(self, model_path): method _get_device (line 81) | def _get_device(self, device=config.bert_gen_config.device): method _prepare (line 92) | def _prepare(self): method get_clap_audio_feature (line 99) | def get_clap_audio_feature(self, audio_data): method get_clap_text_feature (line 107) | def get_clap_text_feature(self, text): FILE: for_deploy/webui.py function generate_audio (line 56) | def generate_audio( function generate_audio_multilang (line 99) | def generate_audio_multilang( function tts_split (line 140) | def tts_split( function tts_fn (line 225) | def tts_fn( function load_audio (line 385) | def load_audio(path): function gr_util (line 391) | def gr_util(item): FILE: hiyoriUI.py class Model (line 39) | class Model: method __init__ (line 42) | def __init__(self, config_path: str, model_path: str, device: str, lan... method to_dict (line 62) | def to_dict(self) -> Dict[str, any]: class Models (line 74) | class Models: method __init__ (line 75) | def __init__(self): method init_model (line 82) | def init_model( method del_model (line 132) | def del_model(self, index: int) -> Optional[int]: method get_models (line 157) | def get_models(self): function index (line 194) | async def index(): function _voice (line 197) | async def _voice( function voice (line 352) | async def voice( function voice (line 395) | async def voice( function get_loaded_models_info (line 436) | def get_loaded_models_info(request: Request): function delete_model (line 445) | def delete_model( function add_model (line 460) | def add_model( function _get_all_models (line 510) | def _get_all_models(root_dir: str = "Data", only_unloaded: bool = False): function get_unloaded_models_info (line 565) | def get_unloaded_models_info( function get_local_models_info (line 575) | def get_local_models_info( function get_status (line 585) | def get_status(): function translate (line 621) | def translate( function random_example (line 635) | def random_example( function get_audio (line 717) | def get_audio(request: Request, path: str = Query(..., description="本地音频... FILE: infer.py function get_net_g (line 84) | def get_net_g(model_path: str, version: str, device: str, hps): function get_text (line 107) | def get_text(text, language_str, hps, device, style_text=None, style_wei... function infer (line 151) | def infer( function infer_multilang (line 335) | def infer_multilang( FILE: 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): class WavLMLoss (line 63) | class WavLMLoss(torch.nn.Module): method __init__ (line 64) | def __init__(self, model, wd, model_sr, slm_sr=16000): method forward (line 73) | def forward(self, wav, y_rec): method generator (line 90) | def generator(self, y_rec): method discriminator (line 105) | def discriminator(self, wav, y_rec): method discriminator_forward (line 139) | def discriminator_forward(self, wav): FILE: mel_processing.py function dynamic_range_compression_torch (line 11) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5): function dynamic_range_decompression_torch (line 20) | def dynamic_range_decompression_torch(x, C=1): function spectral_normalize_torch (line 29) | def spectral_normalize_torch(magnitudes): function spectral_de_normalize_torch (line 34) | def spectral_de_normalize_torch(magnitudes): function spectrogram_torch (line 43) | def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, cente... function spec_to_mel_torch (line 81) | def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax): function mel_spectrogram_torch (line 95) | def mel_spectrogram_torch( FILE: models.py class DurationDiscriminator (line 18) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 19) | def __init__( method forward_probability (line 52) | def forward_probability(self, x, dur): method forward (line 60) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 82) | class TransformerCouplingBlock(nn.Module): method __init__ (line 83) | def __init__( method forward (line 138) | def forward(self, x, x_mask, g=None, reverse=False): class StochasticDurationPredictor (line 148) | class StochasticDurationPredictor(nn.Module): method __init__ (line 149) | def __init__( method forward (line 197) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal... class DurationPredictor (line 259) | class DurationPredictor(nn.Module): method __init__ (line 260) | def __init__( method forward (line 285) | def forward(self, x, x_mask, g=None): class Bottleneck (line 302) | class Bottleneck(nn.Sequential): method __init__ (line 303) | def __init__(self, in_dim, hidden_dim): class Block (line 309) | class Block(nn.Module): method __init__ (line 310) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 315) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 320) | class MLP(nn.Module): method __init__ (line 321) | def __init__(self, in_dim, hidden_dim): method forward (line 327) | def forward(self, x: torch.Tensor): class TextEncoder (line 333) | class TextEncoder(nn.Module): method __init__ (line 334) | def __init__( method forward (line 377) | def forward(self, x, x_lengths, tone, language, bert, ja_bert, en_bert... class ResidualCouplingBlock (line 403) | class ResidualCouplingBlock(nn.Module): method __init__ (line 404) | def __init__( method forward (line 438) | def forward(self, x, x_mask, g=None, reverse=False): class PosteriorEncoder (line 448) | class PosteriorEncoder(nn.Module): method __init__ (line 449) | def __init__( method forward (line 478) | def forward(self, x, x_lengths, g=None): class Generator (line 490) | class Generator(torch.nn.Module): method __init__ (line 491) | def __init__( method forward (line 538) | def forward(self, x, g=None): method remove_weight_norm (line 559) | def remove_weight_norm(self): class DiscriminatorP (line 567) | class DiscriminatorP(torch.nn.Module): method __init__ (line 568) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 624) | def forward(self, x): class DiscriminatorS (line 646) | class DiscriminatorS(torch.nn.Module): method __init__ (line 647) | def __init__(self, use_spectral_norm=False): method forward (line 662) | def forward(self, x): class MultiPeriodDiscriminator (line 676) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 677) | def __init__(self, use_spectral_norm=False): method forward (line 687) | def forward(self, y, y_hat): class WavLMDiscriminator (line 703) | class WavLMDiscriminator(nn.Module): method __init__ (line 706) | def __init__( method forward (line 738) | def forward(self, x): class ReferenceEncoder (line 752) | class ReferenceEncoder(nn.Module): method __init__ (line 758) | def __init__(self, spec_channels, gin_channels=0): method forward (line 787) | def forward(self, inputs, mask=None): method calculate_channels (line 805) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 811) | class SynthesizerTrn(nn.Module): method __init__ (line 816) | def __init__( method forward (line 937) | def forward( method infer (line 1026) | def infer( FILE: modules.py class LayerNorm (line 17) | class LayerNorm(nn.Module): method __init__ (line 18) | def __init__(self, channels, eps=1e-5): method forward (line 26) | def forward(self, x): class ConvReluNorm (line 32) | class ConvReluNorm(nn.Module): method __init__ (line 33) | def __init__( method forward (line 74) | def forward(self, x, x_mask): class DDSConv (line 84) | class DDSConv(nn.Module): method __init__ (line 89) | def __init__(self, channels, kernel_size, n_layers, p_dropout=0.0): method forward (line 118) | def forward(self, x, x_mask, g=None): class WN (line 133) | class WN(torch.nn.Module): method __init__ (line 134) | def __init__( method forward (line 185) | def forward(self, x, x_mask, g=None, **kwargs): method remove_weight_norm (line 212) | def remove_weight_norm(self): class ResBlock1 (line 221) | class ResBlock1(torch.nn.Module): method __init__ (line 222) | def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)): method forward (line 296) | def forward(self, x, x_mask=None): method remove_weight_norm (line 311) | def remove_weight_norm(self): class ResBlock2 (line 318) | class ResBlock2(torch.nn.Module): method __init__ (line 319) | def __init__(self, channels, kernel_size=3, dilation=(1, 3)): method forward (line 347) | def forward(self, x, x_mask=None): method remove_weight_norm (line 358) | def remove_weight_norm(self): class Log (line 363) | class Log(nn.Module): method forward (line 364) | def forward(self, x, x_mask, reverse=False, **kwargs): class Flip (line 374) | class Flip(nn.Module): method forward (line 375) | def forward(self, x, *args, reverse=False, **kwargs): class ElementwiseAffine (line 384) | class ElementwiseAffine(nn.Module): method __init__ (line 385) | def __init__(self, channels): method forward (line 391) | def forward(self, x, x_mask, reverse=False, **kwargs): class ResidualCouplingLayer (line 402) | class ResidualCouplingLayer(nn.Module): method __init__ (line 403) | def __init__( method forward (line 437) | def forward(self, x, x_mask, g=None, reverse=False): class ConvFlow (line 459) | class ConvFlow(nn.Module): method __init__ (line 460) | def __init__( method forward (line 486) | def forward(self, x, x_mask, g=None, reverse=False): class TransformerCouplingLayer (line 519) | class TransformerCouplingLayer(nn.Module): method __init__ (line 520) | def __init__( method forward (line 561) | def forward(self, x, x_mask, g=None, reverse=False): FILE: monotonic_align/__init__.py function maximum_path (line 7) | def maximum_path(neg_cent, mask): FILE: monotonic_align/core.py function maximum_path_jit (line 14) | def maximum_path_jit(paths, values, t_ys, t_xs): FILE: oldVersion/V101/__init__.py function get_text (line 13) | def get_text(text, language_str, hps, device): function infer (line 36) | def infer( FILE: oldVersion/V101/models.py class DurationDiscriminator (line 18) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 19) | def __init__( method forward_probability (line 55) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 71) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 93) | class TransformerCouplingBlock(nn.Module): method __init__ (line 94) | def __init__( method forward (line 149) | def forward(self, x, x_mask, g=None, reverse=False): class StochasticDurationPredictor (line 159) | class StochasticDurationPredictor(nn.Module): method __init__ (line 160) | def __init__( method forward (line 208) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal... class DurationPredictor (line 270) | class DurationPredictor(nn.Module): method __init__ (line 271) | def __init__( method forward (line 296) | def forward(self, x, x_mask, g=None): class TextEncoder (line 313) | class TextEncoder(nn.Module): method __init__ (line 314) | def __init__( method forward (line 355) | def forward(self, x, x_lengths, tone, language, bert, g=None): class ResidualCouplingBlock (line 376) | class ResidualCouplingBlock(nn.Module): method __init__ (line 377) | def __init__( method forward (line 411) | def forward(self, x, x_mask, g=None, reverse=False): class PosteriorEncoder (line 421) | class PosteriorEncoder(nn.Module): method __init__ (line 422) | def __init__( method forward (line 451) | def forward(self, x, x_lengths, g=None): class Generator (line 463) | class Generator(torch.nn.Module): method __init__ (line 464) | def __init__( method forward (line 511) | def forward(self, x, g=None): method remove_weight_norm (line 532) | def remove_weight_norm(self): class DiscriminatorP (line 540) | class DiscriminatorP(torch.nn.Module): method __init__ (line 541) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 597) | def forward(self, x): class DiscriminatorS (line 619) | class DiscriminatorS(torch.nn.Module): method __init__ (line 620) | def __init__(self, use_spectral_norm=False): method forward (line 635) | def forward(self, x): class MultiPeriodDiscriminator (line 649) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 650) | def __init__(self, use_spectral_norm=False): method forward (line 660) | def forward(self, y, y_hat): class ReferenceEncoder (line 676) | class ReferenceEncoder(nn.Module): method __init__ (line 682) | def __init__(self, spec_channels, gin_channels=0): method forward (line 711) | def forward(self, inputs, mask=None): method calculate_channels (line 729) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 735) | class SynthesizerTrn(nn.Module): method __init__ (line 740) | def __init__( method forward (line 861) | def forward(self, x, x_lengths, y, y_lengths, sid, tone, language, bert): method infer (line 933) | def infer( FILE: oldVersion/V101/text/__init__.py function cleaned_text_to_sequence (line 6) | def cleaned_text_to_sequence(cleaned_text, tones, language): function get_bert (line 21) | def get_bert(norm_text, word2ph, language): FILE: oldVersion/V101/text/chinese.py function replace_punctuation (line 55) | def replace_punctuation(text): function g2p (line 68) | def g2p(text): function _get_initials_finals (line 80) | def _get_initials_finals(word): function _g2p (line 93) | def _g2p(segments): function text_normalize (line 170) | def text_normalize(text): function get_bert_feature (line 178) | def get_bert_feature(text, word2ph): FILE: oldVersion/V101/text/chinese_bert.py function get_bert_feature (line 21) | def get_bert_feature(text, word2ph): FILE: oldVersion/V101/text/cleaner.py function clean_text (line 6) | def clean_text(text, language): function clean_text_bert (line 13) | def clean_text_bert(text, language): function text_to_sequence (line 21) | def text_to_sequence(text, language): FILE: oldVersion/V101/text/english.py function post_replace_ph (line 88) | def post_replace_ph(ph): function read_dict (line 111) | def read_dict(): function cache_dict (line 135) | def cache_dict(g2p_dict, file_path): function get_dict (line 140) | def get_dict(): function refine_ph (line 154) | def refine_ph(phn): function refine_syllables (line 162) | def refine_syllables(syllables): function text_normalize (line 174) | def text_normalize(text): function g2p (line 179) | def g2p(text): FILE: oldVersion/V101/text/english_bert_mock.py function get_bert_feature (line 4) | def get_bert_feature(norm_text, word2ph): FILE: oldVersion/V101/text/japanese.py function post_replace_ph (line 46) | def post_replace_ph(ph): function symbols_to_japanese (line 69) | def symbols_to_japanese(text): function preprocess_jap (line 75) | def preprocess_jap(text): function text_normalize (line 91) | def text_normalize(text): function g2p (line 96) | def g2p(norm_text): FILE: oldVersion/V101/text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 672) | def _merge_continuous_three_tones( method _is_reduplication (line 703) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 707) | def _merge_continuous_three_tones_2( method _merge_er (line 737) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 746) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 755) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 767) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: oldVersion/V110/__init__.py function get_text (line 13) | def get_text(text, language_str, hps, device): function infer (line 48) | def infer( FILE: oldVersion/V110/models.py class DurationDiscriminator (line 18) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 19) | def __init__( method forward_probability (line 55) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 71) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 93) | class TransformerCouplingBlock(nn.Module): method __init__ (line 94) | def __init__( method forward (line 149) | def forward(self, x, x_mask, g=None, reverse=False): class StochasticDurationPredictor (line 159) | class StochasticDurationPredictor(nn.Module): method __init__ (line 160) | def __init__( method forward (line 208) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal... class DurationPredictor (line 270) | class DurationPredictor(nn.Module): method __init__ (line 271) | def __init__( method forward (line 296) | def forward(self, x, x_mask, g=None): class TextEncoder (line 313) | class TextEncoder(nn.Module): method __init__ (line 314) | def __init__( method forward (line 356) | def forward(self, x, x_lengths, tone, language, bert, ja_bert, g=None): class ResidualCouplingBlock (line 380) | class ResidualCouplingBlock(nn.Module): method __init__ (line 381) | def __init__( method forward (line 415) | def forward(self, x, x_mask, g=None, reverse=False): class PosteriorEncoder (line 425) | class PosteriorEncoder(nn.Module): method __init__ (line 426) | def __init__( method forward (line 455) | def forward(self, x, x_lengths, g=None): class Generator (line 467) | class Generator(torch.nn.Module): method __init__ (line 468) | def __init__( method forward (line 515) | def forward(self, x, g=None): method remove_weight_norm (line 536) | def remove_weight_norm(self): class DiscriminatorP (line 544) | class DiscriminatorP(torch.nn.Module): method __init__ (line 545) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 601) | def forward(self, x): class DiscriminatorS (line 623) | class DiscriminatorS(torch.nn.Module): method __init__ (line 624) | def __init__(self, use_spectral_norm=False): method forward (line 639) | def forward(self, x): class MultiPeriodDiscriminator (line 653) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 654) | def __init__(self, use_spectral_norm=False): method forward (line 664) | def forward(self, y, y_hat): class ReferenceEncoder (line 680) | class ReferenceEncoder(nn.Module): method __init__ (line 686) | def __init__(self, spec_channels, gin_channels=0): method forward (line 715) | def forward(self, inputs, mask=None): method calculate_channels (line 733) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 739) | class SynthesizerTrn(nn.Module): method __init__ (line 744) | def __init__( method forward (line 865) | def forward(self, x, x_lengths, y, y_lengths, sid, tone, language, ber... method infer (line 939) | def infer( FILE: oldVersion/V110/text/__init__.py function cleaned_text_to_sequence (line 6) | def cleaned_text_to_sequence(cleaned_text, tones, language): function get_bert (line 21) | def get_bert(norm_text, word2ph, language, device): FILE: oldVersion/V110/text/chinese.py function replace_punctuation (line 54) | def replace_punctuation(text): function g2p (line 67) | def g2p(text): function _get_initials_finals (line 79) | def _get_initials_finals(word): function _g2p (line 92) | def _g2p(segments): function text_normalize (line 169) | def text_normalize(text): function get_bert_feature (line 177) | def get_bert_feature(text, word2ph): FILE: oldVersion/V110/text/chinese_bert.py function get_bert_feature (line 8) | def get_bert_feature(text, word2ph, device=None): FILE: oldVersion/V110/text/cleaner.py function clean_text (line 6) | def clean_text(text, language): function clean_text_bert (line 13) | def clean_text_bert(text, language): function text_to_sequence (line 21) | def text_to_sequence(text, language): FILE: oldVersion/V110/text/english.py function post_replace_ph (line 88) | def post_replace_ph(ph): function read_dict (line 111) | def read_dict(): function cache_dict (line 135) | def cache_dict(g2p_dict, file_path): function get_dict (line 140) | def get_dict(): function refine_ph (line 154) | def refine_ph(phn): function refine_syllables (line 162) | def refine_syllables(syllables): function text_normalize (line 174) | def text_normalize(text): function g2p (line 179) | def g2p(text): FILE: oldVersion/V110/text/english_bert_mock.py function get_bert_feature (line 4) | def get_bert_feature(norm_text, word2ph): FILE: oldVersion/V110/text/japanese.py function _makerulemap (line 316) | def _makerulemap(): function kata2phoneme (line 324) | def kata2phoneme(text: str) -> str: function hira2kata (line 351) | def hira2kata(text: str) -> str: function text2kata (line 361) | def text2kata(text: str) -> str: function japanese_convert_numbers_to_words (line 455) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 462) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function japanese_text_to_phonemes (line 466) | def japanese_text_to_phonemes(text: str) -> str: function is_japanese_character (line 476) | def is_japanese_character(char): function replace_punctuation (line 512) | def replace_punctuation(text): function text_normalize (line 528) | def text_normalize(text): function distribute_phone (line 536) | def distribute_phone(n_phone, n_word): function g2p (line 548) | def g2p(norm_text): FILE: oldVersion/V110/text/japanese_bert.py function get_bert_feature (line 8) | def get_bert_feature(text, word2ph, device=None): FILE: oldVersion/V110/text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 672) | def _merge_continuous_three_tones( method _is_reduplication (line 703) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 707) | def _merge_continuous_three_tones_2( method _merge_er (line 737) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 746) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 755) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 767) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: oldVersion/V111/__init__.py function get_text (line 13) | def get_text(text, language_str, hps, device): function get_text_fix (line 48) | def get_text_fix(text, language_str, hps, device): function infer (line 83) | def infer( function infer_fix (line 129) | def infer_fix( FILE: oldVersion/V111/models.py class DurationDiscriminator (line 18) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 19) | def __init__( method forward_probability (line 55) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 71) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 93) | class TransformerCouplingBlock(nn.Module): method __init__ (line 94) | def __init__( method forward (line 149) | def forward(self, x, x_mask, g=None, reverse=False): class StochasticDurationPredictor (line 159) | class StochasticDurationPredictor(nn.Module): method __init__ (line 160) | def __init__( method forward (line 208) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal... class DurationPredictor (line 270) | class DurationPredictor(nn.Module): method __init__ (line 271) | def __init__( method forward (line 296) | def forward(self, x, x_mask, g=None): class TextEncoder (line 313) | class TextEncoder(nn.Module): method __init__ (line 314) | def __init__( method forward (line 356) | def forward(self, x, x_lengths, tone, language, bert, ja_bert, g=None): class ResidualCouplingBlock (line 380) | class ResidualCouplingBlock(nn.Module): method __init__ (line 381) | def __init__( method forward (line 415) | def forward(self, x, x_mask, g=None, reverse=False): class PosteriorEncoder (line 425) | class PosteriorEncoder(nn.Module): method __init__ (line 426) | def __init__( method forward (line 455) | def forward(self, x, x_lengths, g=None): class Generator (line 467) | class Generator(torch.nn.Module): method __init__ (line 468) | def __init__( method forward (line 515) | def forward(self, x, g=None): method remove_weight_norm (line 536) | def remove_weight_norm(self): class DiscriminatorP (line 544) | class DiscriminatorP(torch.nn.Module): method __init__ (line 545) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 601) | def forward(self, x): class DiscriminatorS (line 623) | class DiscriminatorS(torch.nn.Module): method __init__ (line 624) | def __init__(self, use_spectral_norm=False): method forward (line 639) | def forward(self, x): class MultiPeriodDiscriminator (line 653) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 654) | def __init__(self, use_spectral_norm=False): method forward (line 664) | def forward(self, y, y_hat): class ReferenceEncoder (line 680) | class ReferenceEncoder(nn.Module): method __init__ (line 686) | def __init__(self, spec_channels, gin_channels=0): method forward (line 715) | def forward(self, inputs, mask=None): method calculate_channels (line 733) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 739) | class SynthesizerTrn(nn.Module): method __init__ (line 744) | def __init__( method forward (line 865) | def forward(self, x, x_lengths, y, y_lengths, sid, tone, language, ber... method infer (line 939) | def infer( FILE: oldVersion/V111/text/__init__.py function cleaned_text_to_sequence (line 6) | def cleaned_text_to_sequence(cleaned_text, tones, language): function get_bert (line 21) | def get_bert(norm_text, word2ph, language, device): function get_bert_fix (line 31) | def get_bert_fix(norm_text, word2ph, language, device): FILE: oldVersion/V111/text/chinese.py function replace_punctuation (line 54) | def replace_punctuation(text): function g2p (line 67) | def g2p(text): function _get_initials_finals (line 79) | def _get_initials_finals(word): function _g2p (line 92) | def _g2p(segments): function text_normalize (line 169) | def text_normalize(text): function get_bert_feature (line 177) | def get_bert_feature(text, word2ph): FILE: oldVersion/V111/text/chinese_bert.py function get_bert_feature (line 10) | def get_bert_feature(text, word2ph, device=None): FILE: oldVersion/V111/text/cleaner.py function clean_text (line 8) | def clean_text(text, language): function clean_text_fix (line 15) | def clean_text_fix(text, language): function clean_text_bert (line 23) | def clean_text_bert(text, language): function text_to_sequence (line 31) | def text_to_sequence(text, language): FILE: oldVersion/V111/text/english.py function post_replace_ph (line 88) | def post_replace_ph(ph): function read_dict (line 111) | def read_dict(): function cache_dict (line 135) | def cache_dict(g2p_dict, file_path): function get_dict (line 140) | def get_dict(): function refine_ph (line 154) | def refine_ph(phn): function refine_syllables (line 162) | def refine_syllables(syllables): function text_normalize (line 174) | def text_normalize(text): function g2p (line 179) | def g2p(text): FILE: oldVersion/V111/text/english_bert_mock.py function get_bert_feature (line 4) | def get_bert_feature(norm_text, word2ph): FILE: oldVersion/V111/text/fix/japanese.py function kata2phoneme (line 16) | def kata2phoneme(text: str) -> str: function hira2kata (line 41) | def hira2kata(text: str) -> str: function text2kata (line 52) | def text2kata(text: str) -> str: function text2sep_kata (line 82) | def text2sep_kata(text: str) -> (list, list): function japanese_convert_numbers_to_words (line 185) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 192) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function japanese_text_to_phonemes (line 196) | def japanese_text_to_phonemes(text: str) -> str: function is_japanese_character (line 206) | def is_japanese_character(char): function replace_punctuation (line 267) | def replace_punctuation(text): function text_normalize (line 283) | def text_normalize(text): function distribute_phone (line 291) | def distribute_phone(n_phone, n_word): function handle_long (line 300) | def handle_long(sep_phonemes): function g2p (line 314) | def g2p(norm_text): FILE: oldVersion/V111/text/fix/japanese_bert.py function get_bert_feature (line 12) | def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): function get_bert_feature_with_token (line 20) | def get_bert_feature_with_token(tokens, word2ph, device=config.bert_gen_... FILE: oldVersion/V111/text/japanese.py function _makerulemap (line 316) | def _makerulemap(): function kata2phoneme (line 324) | def kata2phoneme(text: str) -> str: function hira2kata (line 351) | def hira2kata(text: str) -> str: function text2kata (line 361) | def text2kata(text: str) -> str: function japanese_convert_numbers_to_words (line 455) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 462) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function japanese_text_to_phonemes (line 466) | def japanese_text_to_phonemes(text: str) -> str: function is_japanese_character (line 476) | def is_japanese_character(char): function replace_punctuation (line 512) | def replace_punctuation(text): function text_normalize (line 528) | def text_normalize(text): function distribute_phone (line 536) | def distribute_phone(n_phone, n_word): function g2p (line 548) | def g2p(norm_text): FILE: oldVersion/V111/text/japanese_bert.py function get_bert_feature (line 10) | def get_bert_feature(text, word2ph, device=None): FILE: oldVersion/V111/text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 672) | def _merge_continuous_three_tones( method _is_reduplication (line 703) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 707) | def _merge_continuous_three_tones_2( method _merge_er (line 737) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 746) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 755) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 767) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: oldVersion/V200/__init__.py function get_text (line 11) | def get_text(text, language_str, hps, device): function infer (line 52) | def infer( FILE: oldVersion/V200/models.py class DurationDiscriminator (line 17) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 18) | def __init__( method forward_probability (line 54) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 70) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 92) | class TransformerCouplingBlock(nn.Module): method __init__ (line 93) | def __init__( method forward (line 148) | def forward(self, x, x_mask, g=None, reverse=False): class StochasticDurationPredictor (line 158) | class StochasticDurationPredictor(nn.Module): method __init__ (line 159) | def __init__( method forward (line 207) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal... class DurationPredictor (line 269) | class DurationPredictor(nn.Module): method __init__ (line 270) | def __init__( method forward (line 295) | def forward(self, x, x_mask, g=None): class TextEncoder (line 312) | class TextEncoder(nn.Module): method __init__ (line 313) | def __init__( method forward (line 356) | def forward( class ResidualCouplingBlock (line 384) | class ResidualCouplingBlock(nn.Module): method __init__ (line 385) | def __init__( method forward (line 419) | def forward(self, x, x_mask, g=None, reverse=False): class PosteriorEncoder (line 429) | class PosteriorEncoder(nn.Module): method __init__ (line 430) | def __init__( method forward (line 459) | def forward(self, x, x_lengths, g=None): class Generator (line 471) | class Generator(torch.nn.Module): method __init__ (line 472) | def __init__( method forward (line 519) | def forward(self, x, g=None): method remove_weight_norm (line 540) | def remove_weight_norm(self): class DiscriminatorP (line 548) | class DiscriminatorP(torch.nn.Module): method __init__ (line 549) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 605) | def forward(self, x): class DiscriminatorS (line 627) | class DiscriminatorS(torch.nn.Module): method __init__ (line 628) | def __init__(self, use_spectral_norm=False): method forward (line 643) | def forward(self, x): class MultiPeriodDiscriminator (line 657) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 658) | def __init__(self, use_spectral_norm=False): method forward (line 668) | def forward(self, y, y_hat): class ReferenceEncoder (line 684) | class ReferenceEncoder(nn.Module): method __init__ (line 690) | def __init__(self, spec_channels, gin_channels=0): method forward (line 719) | def forward(self, inputs, mask=None): method calculate_channels (line 737) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 743) | class SynthesizerTrn(nn.Module): method __init__ (line 748) | def __init__( method forward (line 869) | def forward( method infer (line 956) | def infer( FILE: oldVersion/V200/text/__init__.py function cleaned_text_to_sequence (line 6) | def cleaned_text_to_sequence(cleaned_text, tones, language): function get_bert (line 21) | def get_bert(norm_text, word2ph, language, device): function check_bert_models (line 31) | def check_bert_models(): FILE: oldVersion/V200/text/bert_utils.py function _check_bert (line 10) | def _check_bert(repo_id, files, local_path): FILE: oldVersion/V200/text/chinese.py function replace_punctuation (line 54) | def replace_punctuation(text): function g2p (line 67) | def g2p(text): function _get_initials_finals (line 79) | def _get_initials_finals(word): function _g2p (line 92) | def _g2p(segments): function text_normalize (line 169) | def text_normalize(text): function get_bert_feature (line 177) | def get_bert_feature(text, word2ph): FILE: oldVersion/V200/text/chinese_bert.py function get_bert_feature (line 15) | def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): FILE: oldVersion/V200/text/cleaner.py function clean_text (line 6) | def clean_text(text, language): function clean_text_bert (line 13) | def clean_text_bert(text, language): function text_to_sequence (line 21) | def text_to_sequence(text, language): FILE: oldVersion/V200/text/english.py function post_replace_ph (line 88) | def post_replace_ph(ph): function read_dict (line 111) | def read_dict(): function cache_dict (line 135) | def cache_dict(g2p_dict, file_path): function get_dict (line 140) | def get_dict(): function refine_ph (line 154) | def refine_ph(phn): function refine_syllables (line 162) | def refine_syllables(syllables): function _expand_dollars (line 248) | def _expand_dollars(m): function _remove_commas (line 269) | def _remove_commas(m): function _expand_ordinal (line 273) | def _expand_ordinal(m): function _expand_number (line 277) | def _expand_number(m): function _expand_decimal_point (line 294) | def _expand_decimal_point(m): function normalize_numbers (line 298) | def normalize_numbers(text): function text_normalize (line 308) | def text_normalize(text): function g2p (line 313) | def g2p(text): function get_bert_feature (line 346) | def get_bert_feature(text, word2ph): FILE: oldVersion/V200/text/english_bert_mock.py function get_bert_feature (line 15) | def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): FILE: oldVersion/V200/text/japanese.py function kata2phoneme (line 16) | def kata2phoneme(text: str) -> str: function hira2kata (line 41) | def hira2kata(text: str) -> str: function text2kata (line 52) | def text2kata(text: str) -> str: function text2sep_kata (line 84) | def text2sep_kata(text: str) -> (list, list): function get_accent (line 118) | def get_accent(parsed): function japanese_convert_numbers_to_words (line 217) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 224) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function japanese_text_to_phonemes (line 228) | def japanese_text_to_phonemes(text: str) -> str: function is_japanese_character (line 238) | def is_japanese_character(char): function replace_punctuation (line 299) | def replace_punctuation(text): function text_normalize (line 315) | def text_normalize(text): function distribute_phone (line 323) | def distribute_phone(n_phone, n_word): function handle_long (line 332) | def handle_long(sep_phonemes): function align_tones (line 346) | def align_tones(phones, tones): function g2p (line 368) | def g2p(norm_text): FILE: oldVersion/V200/text/japanese_bert.py function get_bert_feature (line 16) | def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): function get_bert_feature_with_token (line 24) | def get_bert_feature_with_token(tokens, word2ph, device=config.bert_gen_... FILE: oldVersion/V200/text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 672) | def _merge_continuous_three_tones( method _is_reduplication (line 703) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 707) | def _merge_continuous_three_tones_2( method _merge_er (line 737) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 746) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 755) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 767) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: oldVersion/V210/__init__.py function get_text (line 11) | def get_text(text, language_str, hps, device, style_text=None, style_wei... function get_emo_ (line 54) | def get_emo_(reference_audio, emotion): function infer (line 65) | def infer( function infer_multilang (line 138) | def infer_multilang( FILE: oldVersion/V210/emo_gen.py class RegressionHead (line 15) | class RegressionHead(nn.Module): method __init__ (line 18) | def __init__(self, config): method forward (line 25) | def forward(self, features, **kwargs): class EmotionModel (line 36) | class EmotionModel(Wav2Vec2PreTrainedModel): method __init__ (line 39) | def __init__(self, config): method forward (line 47) | def forward( class AudioDataset (line 59) | class AudioDataset(Dataset): method __init__ (line 60) | def __init__(self, list_of_wav_files, sr, processor): method __len__ (line 65) | def __len__(self): method __getitem__ (line 68) | def __getitem__(self, idx): function process_func (line 83) | def process_func( function get_emo (line 107) | def get_emo(path): FILE: oldVersion/V210/models.py class DurationDiscriminator (line 19) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 20) | def __init__( method forward_probability (line 56) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 72) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 94) | class TransformerCouplingBlock(nn.Module): method __init__ (line 95) | def __init__( method forward (line 150) | def forward(self, x, x_mask, g=None, reverse=False): class StochasticDurationPredictor (line 160) | class StochasticDurationPredictor(nn.Module): method __init__ (line 161) | def __init__( method forward (line 209) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal... class DurationPredictor (line 271) | class DurationPredictor(nn.Module): method __init__ (line 272) | def __init__( method forward (line 297) | def forward(self, x, x_mask, g=None): class TextEncoder (line 314) | class TextEncoder(nn.Module): method __init__ (line 315) | def __init__( method forward (line 369) | def forward( class ResidualCouplingBlock (line 417) | class ResidualCouplingBlock(nn.Module): method __init__ (line 418) | def __init__( method forward (line 452) | def forward(self, x, x_mask, g=None, reverse=False): class PosteriorEncoder (line 462) | class PosteriorEncoder(nn.Module): method __init__ (line 463) | def __init__( method forward (line 492) | def forward(self, x, x_lengths, g=None): class Generator (line 504) | class Generator(torch.nn.Module): method __init__ (line 505) | def __init__( method forward (line 552) | def forward(self, x, g=None): method remove_weight_norm (line 573) | def remove_weight_norm(self): class DiscriminatorP (line 581) | class DiscriminatorP(torch.nn.Module): method __init__ (line 582) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 638) | def forward(self, x): class DiscriminatorS (line 660) | class DiscriminatorS(torch.nn.Module): method __init__ (line 661) | def __init__(self, use_spectral_norm=False): method forward (line 676) | def forward(self, x): class MultiPeriodDiscriminator (line 690) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 691) | def __init__(self, use_spectral_norm=False): method forward (line 701) | def forward(self, y, y_hat): class ReferenceEncoder (line 717) | class ReferenceEncoder(nn.Module): method __init__ (line 723) | def __init__(self, spec_channels, gin_channels=0): method forward (line 752) | def forward(self, inputs, mask=None): method calculate_channels (line 770) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 776) | class SynthesizerTrn(nn.Module): method __init__ (line 781) | def __init__( method forward (line 903) | def forward( method infer (line 991) | def infer( FILE: oldVersion/V210/text/__init__.py function cleaned_text_to_sequence (line 6) | def cleaned_text_to_sequence(cleaned_text, tones, language): function get_bert (line 21) | def get_bert(norm_text, word2ph, language, device, style_text, style_wei... function check_bert_models (line 33) | def check_bert_models(): FILE: oldVersion/V210/text/bert_utils.py function _check_bert (line 10) | def _check_bert(repo_id, files, local_path): FILE: oldVersion/V210/text/chinese.py function replace_punctuation (line 55) | def replace_punctuation(text): function g2p (line 68) | def g2p(text): function _get_initials_finals (line 80) | def _get_initials_finals(word): function _g2p (line 93) | def _g2p(segments): function text_normalize (line 170) | def text_normalize(text): function get_bert_feature (line 178) | def get_bert_feature(text, word2ph): FILE: oldVersion/V210/text/chinese_bert.py function get_bert_feature (line 15) | def get_bert_feature( FILE: oldVersion/V210/text/cleaner.py function clean_text (line 6) | def clean_text(text, language): function clean_text_bert (line 13) | def clean_text_bert(text, language): function text_to_sequence (line 21) | def text_to_sequence(text, language): FILE: oldVersion/V210/text/english.py function post_replace_ph (line 91) | def post_replace_ph(ph): function replace_punctuation (line 156) | def replace_punctuation(text): function read_dict (line 172) | def read_dict(): function cache_dict (line 196) | def cache_dict(g2p_dict, file_path): function get_dict (line 201) | def get_dict(): function refine_ph (line 215) | def refine_ph(phn): function refine_syllables (line 223) | def refine_syllables(syllables): function _expand_dollars (line 309) | def _expand_dollars(m): function _remove_commas (line 330) | def _remove_commas(m): function _expand_ordinal (line 334) | def _expand_ordinal(m): function _expand_number (line 338) | def _expand_number(m): function _expand_decimal_point (line 355) | def _expand_decimal_point(m): function normalize_numbers (line 359) | def normalize_numbers(text): function text_normalize (line 369) | def text_normalize(text): function distribute_phone (line 376) | def distribute_phone(n_phone, n_word): function sep_text (line 385) | def sep_text(text): function g2p (line 391) | def g2p(text): function get_bert_feature (line 437) | def get_bert_feature(text, word2ph): FILE: oldVersion/V210/text/english_bert_mock.py function get_bert_feature (line 15) | def get_bert_feature( FILE: oldVersion/V210/text/japanese.py function kata2phoneme (line 16) | def kata2phoneme(text: str) -> str: function hira2kata (line 41) | def hira2kata(text: str) -> str: function text2kata (line 52) | def text2kata(text: str) -> str: function text2sep_kata (line 84) | def text2sep_kata(text: str) -> (list, list): function get_accent (line 118) | def get_accent(parsed): function japanese_convert_numbers_to_words (line 217) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 224) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function japanese_text_to_phonemes (line 228) | def japanese_text_to_phonemes(text: str) -> str: function is_japanese_character (line 238) | def is_japanese_character(char): function replace_punctuation (line 300) | def replace_punctuation(text): function text_normalize (line 316) | def text_normalize(text): function distribute_phone (line 325) | def distribute_phone(n_phone, n_word): function handle_long (line 334) | def handle_long(sep_phonemes): function align_tones (line 348) | def align_tones(phones, tones): function rearrange_tones (line 370) | def rearrange_tones(tones, phones): function g2p (line 390) | def g2p(norm_text): FILE: oldVersion/V210/text/japanese_bert.py function get_bert_feature (line 16) | def get_bert_feature( FILE: oldVersion/V210/text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 672) | def _merge_continuous_three_tones( method _is_reduplication (line 703) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 707) | def _merge_continuous_three_tones_2( method _merge_er (line 737) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 746) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 755) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 767) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: oldVersion/V220/__init__.py function get_text (line 13) | def get_text(text, language_str, hps, device, style_text=None, style_wei... function infer (line 56) | def infer( function infer_multilang (line 134) | def infer_multilang( FILE: oldVersion/V220/clap_gen.py function process_line (line 18) | def process_line(line): FILE: oldVersion/V220/clap_wrapper.py function get_clap_audio_feature (line 12) | def get_clap_audio_feature(audio_data, device=config.bert_gen_config.dev... function get_clap_text_feature (line 33) | def get_clap_text_feature(text, device=config.bert_gen_config.device): FILE: oldVersion/V220/models.py class DurationDiscriminator (line 20) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 21) | def __init__( method forward_probability (line 57) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 73) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 95) | class TransformerCouplingBlock(nn.Module): method __init__ (line 96) | def __init__( method forward (line 151) | def forward(self, x, x_mask, g=None, reverse=False): class StochasticDurationPredictor (line 161) | class StochasticDurationPredictor(nn.Module): method __init__ (line 162) | def __init__( method forward (line 210) | def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scal... class DurationPredictor (line 272) | class DurationPredictor(nn.Module): method __init__ (line 273) | def __init__( method forward (line 298) | def forward(self, x, x_mask, g=None): class Bottleneck (line 315) | class Bottleneck(nn.Sequential): method __init__ (line 316) | def __init__(self, in_dim, hidden_dim): class Block (line 322) | class Block(nn.Module): method __init__ (line 323) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 328) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 333) | class MLP(nn.Module): method __init__ (line 334) | def __init__(self, in_dim, hidden_dim): method forward (line 340) | def forward(self, x: torch.Tensor): class TextEncoder (line 346) | class TextEncoder(nn.Module): method __init__ (line 347) | def __init__( method forward (line 416) | def forward( class ResidualCouplingBlock (line 451) | class ResidualCouplingBlock(nn.Module): method __init__ (line 452) | def __init__( method forward (line 486) | def forward(self, x, x_mask, g=None, reverse=False): class PosteriorEncoder (line 496) | class PosteriorEncoder(nn.Module): method __init__ (line 497) | def __init__( method forward (line 526) | def forward(self, x, x_lengths, g=None): class Generator (line 538) | class Generator(torch.nn.Module): method __init__ (line 539) | def __init__( method forward (line 586) | def forward(self, x, g=None): method remove_weight_norm (line 607) | def remove_weight_norm(self): class DiscriminatorP (line 615) | class DiscriminatorP(torch.nn.Module): method __init__ (line 616) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 672) | def forward(self, x): class DiscriminatorS (line 694) | class DiscriminatorS(torch.nn.Module): method __init__ (line 695) | def __init__(self, use_spectral_norm=False): method forward (line 710) | def forward(self, x): class MultiPeriodDiscriminator (line 724) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 725) | def __init__(self, use_spectral_norm=False): method forward (line 735) | def forward(self, y, y_hat): class ReferenceEncoder (line 751) | class ReferenceEncoder(nn.Module): method __init__ (line 757) | def __init__(self, spec_channels, gin_channels=0): method forward (line 786) | def forward(self, inputs, mask=None): method calculate_channels (line 804) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 810) | class SynthesizerTrn(nn.Module): method __init__ (line 815) | def __init__( method forward (line 937) | def forward( method infer (line 1026) | def infer( FILE: oldVersion/V220/text/__init__.py function cleaned_text_to_sequence (line 6) | def cleaned_text_to_sequence(cleaned_text, tones, language): function get_bert (line 21) | def get_bert(norm_text, word2ph, language, device, style_text=None, styl... function check_bert_models (line 33) | def check_bert_models(): function init_openjtalk (line 53) | def init_openjtalk(): FILE: oldVersion/V220/text/bert_utils.py function _check_bert (line 10) | def _check_bert(repo_id, files, local_path): FILE: oldVersion/V220/text/chinese.py function replace_punctuation (line 55) | def replace_punctuation(text): function g2p (line 68) | def g2p(text): function _get_initials_finals (line 80) | def _get_initials_finals(word): function _g2p (line 93) | def _g2p(segments): function text_normalize (line 170) | def text_normalize(text): function get_bert_feature (line 178) | def get_bert_feature(text, word2ph): FILE: oldVersion/V220/text/chinese_bert.py function get_bert_feature (line 15) | def get_bert_feature( FILE: oldVersion/V220/text/cleaner.py function clean_text (line 6) | def clean_text(text, language): function clean_text_bert (line 13) | def clean_text_bert(text, language): function text_to_sequence (line 21) | def text_to_sequence(text, language): FILE: oldVersion/V220/text/english.py function post_replace_ph (line 91) | def post_replace_ph(ph): function replace_punctuation (line 156) | def replace_punctuation(text): function read_dict (line 172) | def read_dict(): function cache_dict (line 196) | def cache_dict(g2p_dict, file_path): function get_dict (line 201) | def get_dict(): function refine_ph (line 215) | def refine_ph(phn): function refine_syllables (line 223) | def refine_syllables(syllables): function _expand_dollars (line 309) | def _expand_dollars(m): function _remove_commas (line 330) | def _remove_commas(m): function _expand_ordinal (line 334) | def _expand_ordinal(m): function _expand_number (line 338) | def _expand_number(m): function _expand_decimal_point (line 355) | def _expand_decimal_point(m): function normalize_numbers (line 359) | def normalize_numbers(text): function text_normalize (line 369) | def text_normalize(text): function distribute_phone (line 376) | def distribute_phone(n_phone, n_word): function sep_text (line 385) | def sep_text(text): function g2p (line 391) | def g2p(text): function get_bert_feature (line 437) | def get_bert_feature(text, word2ph): FILE: oldVersion/V220/text/english_bert_mock.py function get_bert_feature (line 15) | def get_bert_feature( FILE: oldVersion/V220/text/japanese.py function kata2phoneme (line 16) | def kata2phoneme(text: str) -> str: function hira2kata (line 41) | def hira2kata(text: str) -> str: function text2kata (line 52) | def text2kata(text: str) -> str: function text2sep_kata (line 84) | def text2sep_kata(text: str) -> (list, list): function get_accent (line 118) | def get_accent(parsed): function japanese_convert_numbers_to_words (line 217) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 224) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function japanese_text_to_phonemes (line 228) | def japanese_text_to_phonemes(text: str) -> str: function is_japanese_character (line 238) | def is_japanese_character(char): function replace_punctuation (line 300) | def replace_punctuation(text): function text_normalize (line 316) | def text_normalize(text): function distribute_phone (line 325) | def distribute_phone(n_phone, n_word): function handle_long (line 334) | def handle_long(sep_phonemes): function align_tones (line 348) | def align_tones(phones, tones): function rearrange_tones (line 370) | def rearrange_tones(tones, phones): function g2p (line 390) | def g2p(norm_text): FILE: oldVersion/V220/text/japanese_bert.py function get_bert_feature (line 16) | def get_bert_feature( FILE: oldVersion/V220/text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 672) | def _merge_continuous_three_tones( method _is_reduplication (line 703) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 707) | def _merge_continuous_three_tones_2( method _merge_er (line 737) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 746) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 755) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 767) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: onnx_modules/V200/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V200/models_onnx.py class DurationDiscriminator (line 16) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 17) | def __init__( method forward_probability (line 53) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 69) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 91) | class TransformerCouplingBlock(nn.Module): method __init__ (line 92) | def __init__( method forward (line 147) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 157) | class StochasticDurationPredictor(nn.Module): method __init__ (line 158) | def __init__( method forward (line 206) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 224) | class DurationPredictor(nn.Module): method __init__ (line 225) | def __init__( method forward (line 250) | def forward(self, x, x_mask, g=None): class TextEncoder (line 267) | class TextEncoder(nn.Module): method __init__ (line 268) | def __init__( method forward (line 311) | def forward(self, x, x_lengths, tone, language, bert, ja_bert, en_bert... class ResidualCouplingBlock (line 340) | class ResidualCouplingBlock(nn.Module): method __init__ (line 341) | def __init__( method forward (line 375) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 385) | class PosteriorEncoder(nn.Module): method __init__ (line 386) | def __init__( method forward (line 415) | def forward(self, x, x_lengths, g=None): class Generator (line 427) | class Generator(torch.nn.Module): method __init__ (line 428) | def __init__( method forward (line 475) | def forward(self, x, g=None): method remove_weight_norm (line 496) | def remove_weight_norm(self): class DiscriminatorP (line 504) | class DiscriminatorP(torch.nn.Module): method __init__ (line 505) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 561) | def forward(self, x): class DiscriminatorS (line 583) | class DiscriminatorS(torch.nn.Module): method __init__ (line 584) | def __init__(self, use_spectral_norm=False): method forward (line 599) | def forward(self, x): class MultiPeriodDiscriminator (line 613) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 614) | def __init__(self, use_spectral_norm=False): method forward (line 624) | def forward(self, y, y_hat): class ReferenceEncoder (line 640) | class ReferenceEncoder(nn.Module): method __init__ (line 646) | def __init__(self, spec_channels, gin_channels=0): method forward (line 675) | def forward(self, inputs, mask=None): method calculate_channels (line 693) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 699) | class SynthesizerTrn(nn.Module): method __init__ (line 704) | def __init__( method export_onnx (line 825) | def export_onnx( FILE: onnx_modules/V200/text/bert_utils.py function _check_bert (line 10) | def _check_bert(repo_id, files, local_path): FILE: onnx_modules/V200/text/chinese.py function replace_punctuation (line 54) | def replace_punctuation(text): function g2p (line 67) | def g2p(text): function _get_initials_finals (line 79) | def _get_initials_finals(word): function _g2p (line 92) | def _g2p(segments): function text_normalize (line 169) | def text_normalize(text): function get_bert_feature (line 177) | def get_bert_feature(text, word2ph): FILE: onnx_modules/V200/text/chinese_bert.py function get_bert_feature (line 15) | def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): FILE: onnx_modules/V200/text/cleaner.py function clean_text (line 6) | def clean_text(text, language): function clean_text_bert (line 13) | def clean_text_bert(text, language): function text_to_sequence (line 21) | def text_to_sequence(text, language): FILE: onnx_modules/V200/text/english.py function post_replace_ph (line 88) | def post_replace_ph(ph): function read_dict (line 111) | def read_dict(): function cache_dict (line 135) | def cache_dict(g2p_dict, file_path): function get_dict (line 140) | def get_dict(): function refine_ph (line 154) | def refine_ph(phn): function refine_syllables (line 162) | def refine_syllables(syllables): function _expand_dollars (line 248) | def _expand_dollars(m): function _remove_commas (line 269) | def _remove_commas(m): function _expand_ordinal (line 273) | def _expand_ordinal(m): function _expand_number (line 277) | def _expand_number(m): function _expand_decimal_point (line 294) | def _expand_decimal_point(m): function normalize_numbers (line 298) | def normalize_numbers(text): function text_normalize (line 308) | def text_normalize(text): function g2p (line 313) | def g2p(text): function get_bert_feature (line 346) | def get_bert_feature(text, word2ph): FILE: onnx_modules/V200/text/english_bert_mock.py function get_bert_feature (line 15) | def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): FILE: onnx_modules/V200/text/japanese.py function kata2phoneme (line 16) | def kata2phoneme(text: str) -> str: function hira2kata (line 41) | def hira2kata(text: str) -> str: function text2kata (line 52) | def text2kata(text: str) -> str: function text2sep_kata (line 84) | def text2sep_kata(text: str) -> (list, list): function get_accent (line 118) | def get_accent(parsed): function japanese_convert_numbers_to_words (line 217) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 224) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function japanese_text_to_phonemes (line 228) | def japanese_text_to_phonemes(text: str) -> str: function is_japanese_character (line 238) | def is_japanese_character(char): function replace_punctuation (line 299) | def replace_punctuation(text): function text_normalize (line 315) | def text_normalize(text): function distribute_phone (line 323) | def distribute_phone(n_phone, n_word): function handle_long (line 332) | def handle_long(sep_phonemes): function align_tones (line 346) | def align_tones(phones, tones): function g2p (line 368) | def g2p(norm_text): FILE: onnx_modules/V200/text/japanese_bert.py function get_bert_feature (line 16) | def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): function get_bert_feature_with_token (line 24) | def get_bert_feature_with_token(tokens, word2ph, device=config.bert_gen_... FILE: onnx_modules/V200/text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 672) | def _merge_continuous_three_tones( method _is_reduplication (line 703) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 707) | def _merge_continuous_three_tones_2( method _merge_er (line 737) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 746) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 755) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 767) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: onnx_modules/V200_OnnxInference/__init__.py function convert_pad_shape (line 5) | def convert_pad_shape(pad_shape): function sequence_mask (line 11) | def sequence_mask(length, max_length=None): function generate_path (line 18) | def generate_path(duration, mask): class OnnxInferenceSession (line 35) | class OnnxInferenceSession: method __init__ (line 36) | def __init__(self, path, Providers=["CPUExecutionProvider"]): method __call__ (line 44) | def __call__( FILE: onnx_modules/V210/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V210/models_onnx.py class DurationDiscriminator (line 17) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 18) | def __init__( method forward_probability (line 54) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 70) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 92) | class TransformerCouplingBlock(nn.Module): method __init__ (line 93) | def __init__( method forward (line 148) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 158) | class StochasticDurationPredictor(nn.Module): method __init__ (line 159) | def __init__( method forward (line 207) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 225) | class DurationPredictor(nn.Module): method __init__ (line 226) | def __init__( method forward (line 251) | def forward(self, x, x_mask, g=None): class TextEncoder (line 268) | class TextEncoder(nn.Module): method __init__ (line 269) | def __init__( method init_vq (line 328) | def init_vq(self): method forward (line 338) | def forward( class ResidualCouplingBlock (line 387) | class ResidualCouplingBlock(nn.Module): method __init__ (line 388) | def __init__( method forward (line 422) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 432) | class PosteriorEncoder(nn.Module): method __init__ (line 433) | def __init__( method forward (line 462) | def forward(self, x, x_lengths, g=None): class Generator (line 474) | class Generator(torch.nn.Module): method __init__ (line 475) | def __init__( method forward (line 522) | def forward(self, x, g=None): method remove_weight_norm (line 543) | def remove_weight_norm(self): class DiscriminatorP (line 551) | class DiscriminatorP(torch.nn.Module): method __init__ (line 552) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 608) | def forward(self, x): class DiscriminatorS (line 630) | class DiscriminatorS(torch.nn.Module): method __init__ (line 631) | def __init__(self, use_spectral_norm=False): method forward (line 646) | def forward(self, x): class MultiPeriodDiscriminator (line 660) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 661) | def __init__(self, use_spectral_norm=False): method forward (line 671) | def forward(self, y, y_hat): class ReferenceEncoder (line 687) | class ReferenceEncoder(nn.Module): method __init__ (line 693) | def __init__(self, spec_channels, gin_channels=0): method forward (line 722) | def forward(self, inputs, mask=None): method calculate_channels (line 740) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 746) | class SynthesizerTrn(nn.Module): method __init__ (line 751) | def __init__( method export_onnx (line 873) | def export_onnx( FILE: onnx_modules/V210_OnnxInference/__init__.py function convert_pad_shape (line 5) | def convert_pad_shape(pad_shape): function sequence_mask (line 11) | def sequence_mask(length, max_length=None): function generate_path (line 18) | def generate_path(duration, mask): class OnnxInferenceSession (line 35) | class OnnxInferenceSession: method __init__ (line 36) | def __init__(self, path, Providers=["CPUExecutionProvider"]): method __call__ (line 44) | def __call__( FILE: onnx_modules/V220/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V220/models_onnx.py class DurationDiscriminator (line 17) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 18) | def __init__( method forward_probability (line 54) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 70) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 92) | class TransformerCouplingBlock(nn.Module): method __init__ (line 93) | def __init__( method forward (line 148) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 158) | class StochasticDurationPredictor(nn.Module): method __init__ (line 159) | def __init__( method forward (line 207) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 225) | class DurationPredictor(nn.Module): method __init__ (line 226) | def __init__( method forward (line 251) | def forward(self, x, x_mask, g=None): class Bottleneck (line 268) | class Bottleneck(nn.Sequential): method __init__ (line 269) | def __init__(self, in_dim, hidden_dim): class Block (line 275) | class Block(nn.Module): method __init__ (line 276) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 281) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 286) | class MLP(nn.Module): method __init__ (line 287) | def __init__(self, in_dim, hidden_dim): method forward (line 293) | def forward(self, x: torch.Tensor): class TextEncoder (line 299) | class TextEncoder(nn.Module): method __init__ (line 300) | def __init__( method forward (line 383) | def forward( class ResidualCouplingBlock (line 420) | class ResidualCouplingBlock(nn.Module): method __init__ (line 421) | def __init__( method forward (line 455) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 465) | class PosteriorEncoder(nn.Module): method __init__ (line 466) | def __init__( method forward (line 495) | def forward(self, x, x_lengths, g=None): class Generator (line 507) | class Generator(torch.nn.Module): method __init__ (line 508) | def __init__( method forward (line 555) | def forward(self, x, g=None): method remove_weight_norm (line 576) | def remove_weight_norm(self): class DiscriminatorP (line 584) | class DiscriminatorP(torch.nn.Module): method __init__ (line 585) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 641) | def forward(self, x): class DiscriminatorS (line 663) | class DiscriminatorS(torch.nn.Module): method __init__ (line 664) | def __init__(self, use_spectral_norm=False): method forward (line 679) | def forward(self, x): class MultiPeriodDiscriminator (line 693) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 694) | def __init__(self, use_spectral_norm=False): method forward (line 704) | def forward(self, y, y_hat): class ReferenceEncoder (line 720) | class ReferenceEncoder(nn.Module): method __init__ (line 726) | def __init__(self, spec_channels, gin_channels=0): method forward (line 755) | def forward(self, inputs, mask=None): method calculate_channels (line 773) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 779) | class SynthesizerTrn(nn.Module): method __init__ (line 784) | def __init__( method export_onnx (line 906) | def export_onnx( FILE: onnx_modules/V220_OnnxInference/__init__.py function convert_pad_shape (line 5) | def convert_pad_shape(pad_shape): function sequence_mask (line 11) | def sequence_mask(length, max_length=None): function generate_path (line 18) | def generate_path(duration, mask): class OnnxInferenceSession (line 35) | class OnnxInferenceSession: method __init__ (line 36) | def __init__(self, path, Providers=["CPUExecutionProvider"]): method __call__ (line 44) | def __call__( FILE: onnx_modules/V220_novq_dev/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V220_novq_dev/models_onnx.py class DurationDiscriminator (line 16) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 17) | def __init__( method forward_probability (line 53) | def forward_probability(self, x, x_mask, dur, g=None): method forward (line 69) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 91) | class TransformerCouplingBlock(nn.Module): method __init__ (line 92) | def __init__( method forward (line 147) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 157) | class StochasticDurationPredictor(nn.Module): method __init__ (line 158) | def __init__( method forward (line 206) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 224) | class DurationPredictor(nn.Module): method __init__ (line 225) | def __init__( method forward (line 250) | def forward(self, x, x_mask, g=None): class Bottleneck (line 267) | class Bottleneck(nn.Sequential): method __init__ (line 268) | def __init__(self, in_dim, hidden_dim): class Block (line 274) | class Block(nn.Module): method __init__ (line 275) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 280) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 285) | class MLP(nn.Module): method __init__ (line 286) | def __init__(self, in_dim, hidden_dim): method forward (line 292) | def forward(self, x: torch.Tensor): class TextEncoder (line 298) | class TextEncoder(nn.Module): method __init__ (line 299) | def __init__( method forward (line 359) | def forward( class ResidualCouplingBlock (line 392) | class ResidualCouplingBlock(nn.Module): method __init__ (line 393) | def __init__( method forward (line 427) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 437) | class PosteriorEncoder(nn.Module): method __init__ (line 438) | def __init__( method forward (line 467) | def forward(self, x, x_lengths, g=None): class Generator (line 479) | class Generator(torch.nn.Module): method __init__ (line 480) | def __init__( method forward (line 527) | def forward(self, x, g=None): method remove_weight_norm (line 548) | def remove_weight_norm(self): class DiscriminatorP (line 556) | class DiscriminatorP(torch.nn.Module): method __init__ (line 557) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 613) | def forward(self, x): class DiscriminatorS (line 635) | class DiscriminatorS(torch.nn.Module): method __init__ (line 636) | def __init__(self, use_spectral_norm=False): method forward (line 651) | def forward(self, x): class MultiPeriodDiscriminator (line 665) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 666) | def __init__(self, use_spectral_norm=False): method forward (line 676) | def forward(self, y, y_hat): class ReferenceEncoder (line 692) | class ReferenceEncoder(nn.Module): method __init__ (line 698) | def __init__(self, spec_channels, gin_channels=0): method forward (line 727) | def forward(self, inputs, mask=None): method calculate_channels (line 745) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 751) | class SynthesizerTrn(nn.Module): method __init__ (line 756) | def __init__( method export_onnx (line 878) | def export_onnx( FILE: onnx_modules/V230/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V230/models_onnx.py class DurationDiscriminator (line 18) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 19) | def __init__( method forward_probability (line 52) | def forward_probability(self, x, dur): method forward (line 60) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 82) | class TransformerCouplingBlock(nn.Module): method __init__ (line 83) | def __init__( method forward (line 138) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 148) | class StochasticDurationPredictor(nn.Module): method __init__ (line 149) | def __init__( method forward (line 197) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 215) | class DurationPredictor(nn.Module): method __init__ (line 216) | def __init__( method forward (line 241) | def forward(self, x, x_mask, g=None): class Bottleneck (line 258) | class Bottleneck(nn.Sequential): method __init__ (line 259) | def __init__(self, in_dim, hidden_dim): class Block (line 265) | class Block(nn.Module): method __init__ (line 266) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 271) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 276) | class MLP(nn.Module): method __init__ (line 277) | def __init__(self, in_dim, hidden_dim): method forward (line 283) | def forward(self, x: torch.Tensor): class TextEncoder (line 289) | class TextEncoder(nn.Module): method __init__ (line 290) | def __init__( method forward (line 333) | def forward(self, x, x_lengths, tone, language, bert, ja_bert, en_bert... class ResidualCouplingBlock (line 362) | class ResidualCouplingBlock(nn.Module): method __init__ (line 363) | def __init__( method forward (line 397) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 407) | class PosteriorEncoder(nn.Module): method __init__ (line 408) | def __init__( method forward (line 437) | def forward(self, x, x_lengths, g=None): class Generator (line 449) | class Generator(torch.nn.Module): method __init__ (line 450) | def __init__( method forward (line 497) | def forward(self, x, g=None): method remove_weight_norm (line 518) | def remove_weight_norm(self): class DiscriminatorP (line 526) | class DiscriminatorP(torch.nn.Module): method __init__ (line 527) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 583) | def forward(self, x): class DiscriminatorS (line 605) | class DiscriminatorS(torch.nn.Module): method __init__ (line 606) | def __init__(self, use_spectral_norm=False): method forward (line 621) | def forward(self, x): class MultiPeriodDiscriminator (line 635) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 636) | def __init__(self, use_spectral_norm=False): method forward (line 646) | def forward(self, y, y_hat): class WavLMDiscriminator (line 662) | class WavLMDiscriminator(nn.Module): method __init__ (line 665) | def __init__( method forward (line 697) | def forward(self, x): class ReferenceEncoder (line 711) | class ReferenceEncoder(nn.Module): method __init__ (line 717) | def __init__(self, spec_channels, gin_channels=0): method forward (line 746) | def forward(self, inputs, mask=None): method calculate_channels (line 764) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 770) | class SynthesizerTrn(nn.Module): method __init__ (line 775) | def __init__( method export_onnx (line 896) | def export_onnx( FILE: onnx_modules/V230_OnnxInference/__init__.py function convert_pad_shape (line 5) | def convert_pad_shape(pad_shape): function sequence_mask (line 11) | def sequence_mask(length, max_length=None): function generate_path (line 18) | def generate_path(duration, mask): class OnnxInferenceSession (line 35) | class OnnxInferenceSession: method __init__ (line 36) | def __init__(self, path, Providers=["CPUExecutionProvider"]): method __call__ (line 44) | def __call__( FILE: onnx_modules/V240/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V240/models_onnx.py class DurationDiscriminator (line 18) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 19) | def __init__( method forward_probability (line 52) | def forward_probability(self, x, dur): method forward (line 60) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 82) | class TransformerCouplingBlock(nn.Module): method __init__ (line 83) | def __init__( method forward (line 138) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 148) | class StochasticDurationPredictor(nn.Module): method __init__ (line 149) | def __init__( method forward (line 197) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 215) | class DurationPredictor(nn.Module): method __init__ (line 216) | def __init__( method forward (line 241) | def forward(self, x, x_mask, g=None): class Bottleneck (line 258) | class Bottleneck(nn.Sequential): method __init__ (line 259) | def __init__(self, in_dim, hidden_dim): class Block (line 265) | class Block(nn.Module): method __init__ (line 266) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 271) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 276) | class MLP(nn.Module): method __init__ (line 277) | def __init__(self, in_dim, hidden_dim): method forward (line 283) | def forward(self, x: torch.Tensor): class TextEncoder (line 289) | class TextEncoder(nn.Module): method __init__ (line 290) | def __init__( method forward (line 356) | def forward(self, x, x_lengths, tone, language, bert, emo, g=None): class ResidualCouplingBlock (line 383) | class ResidualCouplingBlock(nn.Module): method __init__ (line 384) | def __init__( method forward (line 418) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 428) | class PosteriorEncoder(nn.Module): method __init__ (line 429) | def __init__( method forward (line 458) | def forward(self, x, x_lengths, g=None): class Generator (line 470) | class Generator(torch.nn.Module): method __init__ (line 471) | def __init__( method forward (line 518) | def forward(self, x, g=None): method remove_weight_norm (line 539) | def remove_weight_norm(self): class DiscriminatorP (line 547) | class DiscriminatorP(torch.nn.Module): method __init__ (line 548) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 604) | def forward(self, x): class DiscriminatorS (line 626) | class DiscriminatorS(torch.nn.Module): method __init__ (line 627) | def __init__(self, use_spectral_norm=False): method forward (line 642) | def forward(self, x): class MultiPeriodDiscriminator (line 656) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 657) | def __init__(self, use_spectral_norm=False): method forward (line 667) | def forward(self, y, y_hat): class WavLMDiscriminator (line 683) | class WavLMDiscriminator(nn.Module): method __init__ (line 686) | def __init__( method forward (line 718) | def forward(self, x): class ReferenceEncoder (line 732) | class ReferenceEncoder(nn.Module): method __init__ (line 738) | def __init__(self, spec_channels, gin_channels=0): method forward (line 767) | def forward(self, inputs, mask=None): method calculate_channels (line 785) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 791) | class SynthesizerTrn(nn.Module): method __init__ (line 796) | def __init__( method export_onnx (line 917) | def export_onnx( FILE: onnx_modules/V240_JP/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V240_JP/models_onnx.py class DurationDiscriminator (line 20) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 21) | def __init__( method forward_probability (line 54) | def forward_probability(self, x, dur): method forward (line 62) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 84) | class TransformerCouplingBlock(nn.Module): method __init__ (line 85) | def __init__( method forward (line 140) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 150) | class StochasticDurationPredictor(nn.Module): method __init__ (line 151) | def __init__( method forward (line 199) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 217) | class DurationPredictor(nn.Module): method __init__ (line 218) | def __init__( method forward (line 243) | def forward(self, x, x_mask, g=None): class Bottleneck (line 260) | class Bottleneck(nn.Sequential): method __init__ (line 261) | def __init__(self, in_dim, hidden_dim): class Block (line 267) | class Block(nn.Module): method __init__ (line 268) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 273) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 278) | class MLP(nn.Module): method __init__ (line 279) | def __init__(self, in_dim, hidden_dim): method forward (line 285) | def forward(self, x: torch.Tensor): class TextEncoder (line 291) | class TextEncoder(nn.Module): method __init__ (line 292) | def __init__( method forward (line 361) | def forward(self, x, x_lengths, tone, language, bert, emo, g=None): class ResidualCouplingBlock (line 386) | class ResidualCouplingBlock(nn.Module): method __init__ (line 387) | def __init__( method forward (line 421) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 431) | class PosteriorEncoder(nn.Module): method __init__ (line 432) | def __init__( method forward (line 461) | def forward(self, x, x_lengths, g=None): class Generator (line 473) | class Generator(torch.nn.Module): method __init__ (line 474) | def __init__( method forward (line 521) | def forward(self, x, g=None): method remove_weight_norm (line 542) | def remove_weight_norm(self): class DiscriminatorP (line 550) | class DiscriminatorP(torch.nn.Module): method __init__ (line 551) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 607) | def forward(self, x): class DiscriminatorS (line 629) | class DiscriminatorS(torch.nn.Module): method __init__ (line 630) | def __init__(self, use_spectral_norm=False): method forward (line 645) | def forward(self, x): class MultiPeriodDiscriminator (line 659) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 660) | def __init__(self, use_spectral_norm=False): method forward (line 670) | def forward(self, y, y_hat): class WavLMDiscriminator (line 686) | class WavLMDiscriminator(nn.Module): method __init__ (line 689) | def __init__( method forward (line 721) | def forward(self, x): class ReferenceEncoder (line 735) | class ReferenceEncoder(nn.Module): method __init__ (line 741) | def __init__(self, spec_channels, gin_channels=0): method forward (line 770) | def forward(self, inputs, mask=None): method calculate_channels (line 788) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 794) | class SynthesizerTrn(nn.Module): method __init__ (line 799) | def __init__( method export_onnx (line 920) | def export_onnx( FILE: onnx_modules/V240_OnnxInference/__init__.py function convert_pad_shape (line 5) | def convert_pad_shape(pad_shape): function sequence_mask (line 11) | def sequence_mask(length, max_length=None): function generate_path (line 18) | def generate_path(duration, mask): class OnnxInferenceSession (line 35) | class OnnxInferenceSession: method __init__ (line 36) | def __init__(self, path, Providers=["CPUExecutionProvider"]): method __call__ (line 44) | def __call__( FILE: onnx_modules/V240_ZH/attentions_onnx.py class LayerNorm (line 12) | class LayerNorm(nn.Module): method __init__ (line 13) | def __init__(self, channels, eps=1e-5): method forward (line 21) | def forward(self, x): function fused_add_tanh_sigmoid_multiply (line 28) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): class Encoder (line 37) | class Encoder(nn.Module): method __init__ (line 38) | def __init__( method forward (line 103) | def forward(self, x, x_mask, g=None): class MultiHeadAttention (line 123) | class MultiHeadAttention(nn.Module): method __init__ (line 124) | def __init__( method forward (line 177) | def forward(self, x, c, attn_mask=None): method attention (line 187) | def attention(self, query, key, value, mask=None): method _matmul_with_relative_values (line 238) | def _matmul_with_relative_values(self, x, y): method _matmul_with_relative_keys (line 247) | def _matmul_with_relative_keys(self, x, y): method _get_relative_embeddings (line 256) | def _get_relative_embeddings(self, relative_embeddings, length): method _relative_position_to_absolute_position (line 274) | def _relative_position_to_absolute_position(self, x): method _absolute_position_to_relative_position (line 295) | def _absolute_position_to_relative_position(self, x): method _attention_bias_proximal (line 311) | def _attention_bias_proximal(self, length): class FFN (line 323) | class FFN(nn.Module): method __init__ (line 324) | def __init__( method forward (line 352) | def forward(self, x, x_mask): method _causal_padding (line 362) | def _causal_padding(self, x): method _same_padding (line 371) | def _same_padding(self, x): FILE: onnx_modules/V240_ZH/models_onnx.py class DurationDiscriminator (line 20) | class DurationDiscriminator(nn.Module): # vits2 method __init__ (line 21) | def __init__( method forward_probability (line 54) | def forward_probability(self, x, dur): method forward (line 62) | def forward(self, x, x_mask, dur_r, dur_hat, g=None): class TransformerCouplingBlock (line 84) | class TransformerCouplingBlock(nn.Module): method __init__ (line 85) | def __init__( method forward (line 140) | def forward(self, x, x_mask, g=None, reverse=True): class StochasticDurationPredictor (line 150) | class StochasticDurationPredictor(nn.Module): method __init__ (line 151) | def __init__( method forward (line 199) | def forward(self, x, x_mask, z, g=None): class DurationPredictor (line 217) | class DurationPredictor(nn.Module): method __init__ (line 218) | def __init__( method forward (line 243) | def forward(self, x, x_mask, g=None): class Bottleneck (line 260) | class Bottleneck(nn.Sequential): method __init__ (line 261) | def __init__(self, in_dim, hidden_dim): class Block (line 267) | class Block(nn.Module): method __init__ (line 268) | def __init__(self, in_dim, hidden_dim) -> None: method forward (line 273) | def forward(self, x: torch.Tensor) -> torch.Tensor: class MLP (line 278) | class MLP(nn.Module): method __init__ (line 279) | def __init__(self, in_dim, hidden_dim): method forward (line 285) | def forward(self, x: torch.Tensor): class TextEncoder (line 291) | class TextEncoder(nn.Module): method __init__ (line 292) | def __init__( method forward (line 358) | def forward(self, x, x_lengths, tone, language, bert, emo, g=None): class ResidualCouplingBlock (line 385) | class ResidualCouplingBlock(nn.Module): method __init__ (line 386) | def __init__( method forward (line 420) | def forward(self, x, x_mask, g=None, reverse=True): class PosteriorEncoder (line 430) | class PosteriorEncoder(nn.Module): method __init__ (line 431) | def __init__( method forward (line 460) | def forward(self, x, x_lengths, g=None): class Generator (line 472) | class Generator(torch.nn.Module): method __init__ (line 473) | def __init__( method forward (line 520) | def forward(self, x, g=None): method remove_weight_norm (line 541) | def remove_weight_norm(self): class DiscriminatorP (line 549) | class DiscriminatorP(torch.nn.Module): method __init__ (line 550) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=... method forward (line 606) | def forward(self, x): class DiscriminatorS (line 628) | class DiscriminatorS(torch.nn.Module): method __init__ (line 629) | def __init__(self, use_spectral_norm=False): method forward (line 644) | def forward(self, x): class MultiPeriodDiscriminator (line 658) | class MultiPeriodDiscriminator(torch.nn.Module): method __init__ (line 659) | def __init__(self, use_spectral_norm=False): method forward (line 669) | def forward(self, y, y_hat): class WavLMDiscriminator (line 685) | class WavLMDiscriminator(nn.Module): method __init__ (line 688) | def __init__( method forward (line 720) | def forward(self, x): class ReferenceEncoder (line 734) | class ReferenceEncoder(nn.Module): method __init__ (line 740) | def __init__(self, spec_channels, gin_channels=0): method forward (line 769) | def forward(self, inputs, mask=None): method calculate_channels (line 787) | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): class SynthesizerTrn (line 793) | class SynthesizerTrn(nn.Module): method __init__ (line 798) | def __init__( method export_onnx (line 919) | def export_onnx( FILE: onnx_modules/__init__.py function export_onnx (line 5) | def export_onnx(export_path, model_path, config_path, novq, dev, Extra): FILE: preprocess_text.py function preprocess (line 34) | def preprocess( FILE: re_matching.py function extract_language_and_text_updated (line 4) | def extract_language_and_text_updated(speaker, dialogue): function validate_text (line 15) | def validate_text(input_text): function text_matching (line 41) | def text_matching(text: str) -> list: function cut_para (line 50) | def cut_para(text): function cut_sent (line 58) | def cut_sent(para): FILE: resample.py function process (line 12) | def process(item): FILE: resample_legacy.py function process (line 12) | def process(item): FILE: spec_gen.py class AudioProcessor (line 8) | class AudioProcessor: method __init__ (line 9) | def __init__( method process_audio (line 31) | def process_audio(self, filename): FILE: text/__init__.py function cleaned_text_to_sequence (line 6) | def cleaned_text_to_sequence(cleaned_text, tones, language): function get_bert (line 21) | def get_bert(norm_text, word2ph, language, device, style_text=None, styl... function check_bert_models (line 33) | def check_bert_models(): function init_openjtalk (line 53) | def init_openjtalk(): FILE: text/bert_utils.py function _check_bert (line 10) | def _check_bert(repo_id, files, local_path): FILE: text/chinese.py function replace_punctuation (line 66) | def replace_punctuation(text): function g2p (line 79) | def g2p(text): function _get_initials_finals (line 91) | def _get_initials_finals(word): function _g2p (line 104) | def _g2p(segments): function text_normalize (line 181) | def text_normalize(text): function get_bert_feature (line 187) | def get_bert_feature(text, word2ph): FILE: text/chinese_bert.py function get_bert_feature (line 15) | def get_bert_feature( FILE: text/cleaner.py function clean_text (line 6) | def clean_text(text, language): function clean_text_bert (line 13) | def clean_text_bert(text, language): function text_to_sequence (line 21) | def text_to_sequence(text, language): FILE: text/english.py function post_replace_ph (line 92) | def post_replace_ph(ph): function replace_punctuation (line 157) | def replace_punctuation(text): function read_dict (line 173) | def read_dict(): function cache_dict (line 197) | def cache_dict(g2p_dict, file_path): function get_dict (line 202) | def get_dict(): function refine_ph (line 216) | def refine_ph(phn): function refine_syllables (line 226) | def refine_syllables(syllables): function _expand_dollars (line 312) | def _expand_dollars(m): function _remove_commas (line 333) | def _remove_commas(m): function _expand_ordinal (line 337) | def _expand_ordinal(m): function _expand_number (line 341) | def _expand_number(m): function _expand_decimal_point (line 358) | def _expand_decimal_point(m): function normalize_numbers (line 362) | def normalize_numbers(text): function text_normalize (line 372) | def text_normalize(text): function distribute_phone (line 379) | def distribute_phone(n_phone, n_word): function sep_text (line 388) | def sep_text(text): function text_to_words (line 394) | def text_to_words(text): function g2p (line 421) | def g2p(text): function get_bert_feature (line 479) | def get_bert_feature(text, word2ph): FILE: text/english_bert_mock.py function get_bert_feature (line 15) | def get_bert_feature( FILE: text/japanese.py function hiragana2p (line 313) | def hiragana2p(txt: str) -> str: function kata2phoneme (line 350) | def kata2phoneme(text: str) -> str: function text2sep_kata (line 382) | def text2sep_kata(text: str): function get_accent (line 415) | def get_accent(parsed): function japanese_convert_numbers_to_words (line 514) | def japanese_convert_numbers_to_words(text: str) -> str: function japanese_convert_alpha_symbols_to_words (line 521) | def japanese_convert_alpha_symbols_to_words(text: str) -> str: function is_japanese_character (line 525) | def is_japanese_character(char): function replace_punctuation (line 587) | def replace_punctuation(text): function text_normalize (line 603) | def text_normalize(text): function distribute_phone (line 612) | def distribute_phone(n_phone, n_word): function handle_long (line 621) | def handle_long(sep_phonemes): function align_tones (line 635) | def align_tones(phones, tones): function rearrange_tones (line 657) | def rearrange_tones(tones, phones): function g2p (line 677) | def g2p(norm_text): FILE: text/japanese_bert.py function get_bert_feature (line 16) | def get_bert_feature( FILE: text/tone_sandhi.py class ToneSandhi (line 22) | class ToneSandhi: method __init__ (line 23) | def __init__(self): method _neural_sandhi (line 466) | def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> Li... method _bu_sandhi (line 525) | def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: method _yi_sandhi (line 536) | def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: method _split_word (line 561) | def _split_word(self, word: str) -> List[str]: method _three_sandhi (line 574) | def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: method _all_tone_three (line 614) | def _all_tone_three(self, finals: List[str]) -> bool: method _merge_bu (line 619) | def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_yi (line 639) | def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_continuous_three_tones (line 676) | def _merge_continuous_three_tones( method _is_reduplication (line 707) | def _is_reduplication(self, word: str) -> bool: method _merge_continuous_three_tones_2 (line 711) | def _merge_continuous_three_tones_2( method _merge_er (line 741) | def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: method _merge_reduplication (line 750) | def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tup... method pre_merge_for_modify (line 759) | def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tup... method modified_tone (line 771) | def modified_tone(self, word: str, pos: str, finals: List[str]) -> Lis... FILE: tools/classify_language.py function classify_language (line 115) | def classify_language(text: str, target_languages: list = None) -> str: function classify_zh_ja (line 142) | def classify_zh_ja(text: str) -> str: function split_alpha_nonalpha (line 163) | def split_alpha_nonalpha(text, mode=1): FILE: tools/sentence.py function check_is_none (line 8) | def check_is_none(item) -> bool: function markup_language (line 17) | def markup_language(text: str, target_languages: list = None) -> str: function split_by_language (line 59) | def split_by_language(text: str, target_languages: list = None) -> list: function sentence_split (line 97) | def sentence_split(text: str, max: int) -> list: function sentence_split_and_markup (line 119) | def sentence_split_and_markup(text, max=50, lang="auto", speaker_lang=No... FILE: tools/translate.py function translate (line 12) | def translate(Sentence: str, to_Language: str = "jp", from_Language: str... FILE: train_ms.py function run (line 54) | def run(): function train_and_evaluate (line 394) | def train_and_evaluate( function evaluate (line 742) | def evaluate(hps, generator, eval_loader, writer_eval): FILE: transforms.py function piecewise_rational_quadratic_transform (line 11) | def piecewise_rational_quadratic_transform( function searchsorted (line 44) | def searchsorted(bin_locations, inputs, eps=1e-6): function unconstrained_rational_quadratic_spline (line 49) | def unconstrained_rational_quadratic_spline( function rational_quadratic_spline (line 99) | def rational_quadratic_spline( FILE: update_status.py function raw_dir_convert_to_path (line 7) | def raw_dir_convert_to_path(target_dir: str, lang): function update_g_files (line 20) | def update_g_files(): function update_c_files (line 32) | def update_c_files(): function update_model_folders (line 46) | def update_model_folders(): function update_wav_lab_pairs (line 60) | def update_wav_lab_pairs(): function update_raw_folders (line 74) | def update_raw_folders(): FILE: utils.py function download_emo_models (line 19) | def download_emo_models(mirror, repo_id, model_name): function download_checkpoint (line 37) | def download_checkpoint( function load_checkpoint (line 65) | def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimiz... function save_checkpoint (line 123) | def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoi... function summarize (line 144) | def summarize( function latest_checkpoint_path (line 163) | def latest_checkpoint_path(dir_path, regex="G_*.pth"): function plot_spectrogram_to_numpy (line 170) | def plot_spectrogram_to_numpy(spectrogram): function plot_alignment_to_numpy (line 196) | def plot_alignment_to_numpy(alignment, info=None): function load_wav_to_torch (line 227) | def load_wav_to_torch(full_path): function load_filepaths_and_text (line 232) | def load_filepaths_and_text(filename, split="|"): function get_hparams (line 238) | def get_hparams(init=True): function clean_checkpoints (line 271) | def clean_checkpoints(path_to_models="logs/44k/", n_ckpts_to_keep=2, sor... function get_hparams_from_dir (line 320) | def get_hparams_from_dir(model_dir): function get_hparams_from_file (line 331) | def get_hparams_from_file(config_path): function check_git_hash (line 341) | def check_git_hash(model_dir): function get_logger (line 366) | def get_logger(model_dir, filename="train.log"): class HParams (line 381) | class HParams: method __init__ (line 382) | def __init__(self, **kwargs): method keys (line 388) | def keys(self): method items (line 391) | def items(self): method values (line 394) | def values(self): method __len__ (line 397) | def __len__(self): method __getitem__ (line 400) | def __getitem__(self, key): method __setitem__ (line 403) | def __setitem__(self, key, value): method __contains__ (line 406) | def __contains__(self, key): method __repr__ (line 409) | def __repr__(self): function load_model (line 413) | def load_model(model_path, config_path): function mix_model (line 428) | def mix_model( function get_steps (line 459) | def get_steps(model_path): FILE: webui.py function free_up_memory (line 36) | def free_up_memory(): function generate_audio (line 44) | def generate_audio( function generate_audio_multilang (line 91) | def generate_audio_multilang( function tts_split (line 134) | def tts_split( function process_mix (line 206) | def process_mix(slice): function process_auto (line 226) | def process_auto(text): function process_text (line 245) | def process_text( function tts_fn (line 319) | def tts_fn( function format_utils (line 361) | def format_utils(text, speaker): function load_audio (line 371) | def load_audio(path): function gr_util (line 377) | def gr_util(item): FILE: webui_preprocess.py function get_path (line 9) | def get_path(data_dir): function generate_config (line 18) | def generate_config(data_dir, batch_size): function resample (line 41) | def resample(data_dir): function preprocess_text (line 61) | def preprocess_text(data_dir): function bert_gen (line 89) | def bert_gen(data_dir):