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Functions298 in github.com/bytedance/MegaTTS3

↓ 1 callersMethodforward
(self, x)
tts/modules/wavvae/encoder/common_modules/conv.py:138
↓ 1 callersMethodforward_embedding
(self, txt_tokens)
tts/modules/ar_dur/commons/transformer.py:760
↓ 1 callersMethodforward_style_embed
(self, spk_embed=None, spk_id=None, mel_ref=None)
tts/modules/ar_dur/ar_dur_predictor.py:148
↓ 1 callersFunctiong2p
(self, text_inp)
tts/frontend_function.py:24
↓ 1 callersFunctionget_all_ckpts
(work_dir, steps=None)
tts/utils/commons/ckpt_utils.py:71
↓ 1 callersFunctionget_extra_padding_for_conv1d
(x: torch.Tensor, kernel_size: int, stride: int, padding_total: int = 0)
tts/modules/wavvae/encoder/common_modules/conv.py:71
↓ 1 callersFunctionget_norm_module
(module: nn.Module, causal: bool = False, norm: str = 'none', **norm_kwargs)
tts/modules/wavvae/encoder/common_modules/conv.py:57
↓ 1 callersMethodinference
(self, inputs, timesteps=20, seq_cfg_w=[1.0, 1.0], **kwargs)
tts/modules/llm_dit/dit.py:127
↓ 1 callersFunctionis_sil_phoneme
(p)
tts/utils/text_utils/text_encoder.py:279
↓ 1 callersMethodlogits
(self, tokens, audio_features, kv_cache=None)
tts/modules/aligner/whisper_small.py:264
↓ 1 callersFunctionmake_dur_prompt
(self, mel2ph_ref, ph_ref, tone_ref)
tts/frontend_function.py:77
↓ 1 callersFunctionmake_pad_mask
Make mask tensor containing indices of padded part. Args: lengths (LongTensor or List): Batch of lengths (B,). xs (Tensor, optiona
tts/modules/ar_dur/commons/seq_utils.py:112
↓ 1 callersFunctionmel2token_to_dur
(mel2token, T_txt=None, max_dur=None)
tts/utils/audio_utils/align.py:17
↓ 1 callersFunctionprecompute_freqs_cis
(dim: int, end: int, theta: float = 10000.0)
tts/modules/llm_dit/transformer.py:23
↓ 1 callersFunctionprepare_inputs_for_dit
(self, mel2ph_ref, mel2ph_pred, ph_ref, tone_ref, ph_pred, tone_pred, vae_latent)
tts/frontend_function.py:154
↓ 1 callersMethodqkv_attention
( self, q: Tensor, k: Tensor, v: Tensor, mask: Optional[Tensor] = None, casual: Optional[bool] = None
tts/modules/aligner/whisper_small.py:118
↓ 1 callersFunctionremove_meta_key
(d)
tts/utils/commons/hparams.py:66
↓ 1 callersMethodreset_parameters
(self)
tts/modules/ar_dur/commons/transformer.py:201
↓ 1 callersFunctionreshape_for_broadcast
(freqs_cis: torch.Tensor, x: torch.Tensor)
tts/modules/llm_dit/transformer.py:31
↓ 1 callersMethodsample
(self, size, device)
tts/modules/llm_dit/cfm.py:42
↓ 1 callersMethodsample_location_and_conditional_flow
Compute the sample xt (drawn from N(t * x1 + (1 - t) * x0, sigma)) and the conditional vector field ut(x1|x0) = x1 - x0, see Eq.(15)
tts/modules/llm_dit/cfm.py:189
↓ 1 callersMethodsample_noise_like
(self, x)
tts/modules/llm_dit/cfm.py:186
↓ 1 callersMethodsample_xt
Draw a sample from the probability path N(t * x1 + (1 - t) * x0, sigma), see (Eq.14) [1]. Parameters ---------- x0 :
tts/modules/llm_dit/cfm.py:134
↓ 1 callersFunctionsanitize_filename_component
(text, max_length=20)
tts/infer_cli.py:43
↓ 1 callersFunctionsave_wav
(wav_bytes, path)
tts/utils/audio_utils/io.py:39
↓ 1 callersFunctionsequence_mask
(length, max_length=None)
tts/modules/ar_dur/commons/rel_transformer.py:34
↓ 1 callersMethodset_buffer
(self, name, tensor, incremental_state)
tts/modules/ar_dur/commons/rot_transformer.py:608
↓ 1 callersMethodset_buffer
(self, name, tensor, incremental_state)
tts/modules/ar_dur/commons/transformer.py:635
↓ 1 callersFunctionsinusoids
Returns sinusoids for positional embedding
tts/modules/aligner/whisper_small.py:65
↓ 1 callersFunctionsplit_ph
Input: ph_timestamp, shape [T]
tts/utils/text_utils/ph_tone_convert.py:72
↓ 1 callersFunctionsplit_ph_timestamp
Input: ph_timestamp, shape [T]
tts/utils/text_utils/ph_tone_convert.py:39
↓ 1 callersFunctionstrip_ids
Strip ids_to_strip from the end ids.
tts/utils/text_utils/text_encoder.py:44
↓ 1 callersFunctionto_mp3
(out_path)
tts/utils/audio_utils/io.py:46
↓ 1 callersFunctionto_wav_bytes
(wav, sr, norm=False)
tts/utils/audio_utils/io.py:25
↓ 1 callersFunctiontraverse_dict
(d, func, ctx)
tts/utils/commons/hparams.py:42
FunctionWNConvTranspose1d
(*args, **kwargs)
tts/modules/wavvae/decoder/hifigan_modules.py:95
Method__init__
( self, device=None, ckpt_root='./checkpoints', dit_exp_name=
tts/infer_cli.py:73
Method__init__
(self, n_state: int, n_head: int)
tts/modules/aligner/whisper_small.py:87
Method__init__
(self, n_state: int, n_head: int, cross_attention: bool = False)
tts/modules/aligner/whisper_small.py:135
Method__init__
( self, n_mels: int, n_ctx: int, n_state: int, n_head: int, n_layer: int )
tts/modules/aligner/whisper_small.py:169
Method__init__
( self, n_vocab: int, n_ctx: int, n_state: int, n_head: int, n_layer: int )
tts/modules/aligner/whisper_small.py:202
Method__init__
(self, T=1000.0, loc=0.0, scale=1.0)
tts/modules/llm_dit/cfm.py:37
Method__init__
r"""Initialize the ConditionalFlowMatcher class. It requires the hyper-parameter $\sigma$. Parameters ---------- sigma : Unio
tts/modules/llm_dit/cfm.py:82
Method__init__
(self, dim)
tts/modules/llm_dit/time_embedding.py:21
Method__init__
(self, dim)
tts/modules/llm_dit/transformer.py:67
Method__init__
(self, encoder_dim, encoder_n_heads, max_seq_len)
tts/modules/llm_dit/transformer.py:81
Method__init__
( self, dim: int, hidden_dim: int, multiple_of: int,
tts/modules/llm_dit/transformer.py:131
Method__init__
(self, encoder_dim, encoder_n_heads, max_seq_len)
tts/modules/llm_dit/transformer.py:155
Method__init__
(self, encoder_n_layers, encoder_dim, encoder_n_heads, max_seq_len)
tts/modules/llm_dit/transformer.py:208
Method__init__
(self)
tts/modules/llm_dit/dit.py:28
Method__init__
(self, hparams, hidden_size, dec_hidden_size, lm_num_layers, dict_size, code_size, use_rot_embed=True,
tts/modules/ar_dur/ar_dur_predictor.py:172
Method__init__
Construct an LayerNorm object.
tts/modules/ar_dur/commons/layers.py:25
Method__init__
(self, *args)
tts/modules/ar_dur/commons/layers.py:51
Method__init__
(self, embedding_dim, padding_idx, init_size=1024)
tts/modules/ar_dur/commons/rot_transformer.py:35
Method__init__
Rotary embeddings (Su et al., 2021) layer. The rotary embedding will be precomputed for up to 'seq _len' positions. The embedding will
tts/modules/ar_dur/commons/rot_transformer.py:96
Method__init__
(self, embed_dim, num_heads, kdim=None, vdim=None, dropout=0., bias=True, add_bias_kv=False,
tts/modules/ar_dur/commons/rot_transformer.py:207
Method__init__
(self, embed_dim, num_heads, kdim=None, vdim=None, dropout=0., bias=True, add_bias_kv=False,
tts/modules/ar_dur/commons/rot_transformer.py:405
Method__init__
(self, c, num_heads, dropout, attention_dropout=0.1, relu_dropout=0.1, kernel_size=9, ffn_hid
tts/modules/ar_dur/commons/rot_transformer.py:613
Method__init__
(self, hidden_size, dropout, kernel_size=9, num_heads=8, ffn_hidden_size=1024, post_ln=False,
tts/modules/ar_dur/commons/rot_transformer.py:623
Method__init__
(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., wind
tts/modules/ar_dur/commons/rel_transformer.py:42
Method__init__
(self, channels, out_channels, n_heads, window_size=None, heads_share=True, p_dropout=0., blo
tts/modules/ar_dur/commons/rel_transformer.py:101
Method__init__
(self, channels, eps=1e-4)
tts/modules/ar_dur/commons/rel_transformer.py:280
Method__init__
(self, in_channels, hidden_channels, out_channels, kernel_size, n_layers, p_dropout)
tts/modules/ar_dur/commons/rel_transformer.py:301
Method__init__
(self, n_vocab, out_channels, hidden_channels,
tts/modules/ar_dur/commons/rel_transformer.py:336
Method__init__
(self, pad_value=0.0)
tts/modules/ar_dur/commons/nar_tts_modules.py:24
Method__init__
(self, embedding_dim, padding_idx, init_size=1024)
tts/modules/ar_dur/commons/transformer.py:33
Method__init__
(self, hidden_size, filter_size, padding="SAME", kernel_size=1, dropout=0., act='gelu', bias=True)
tts/modules/ar_dur/commons/transformer.py:90
Method__init__
(self, embed_dim, num_heads, kdim=None, vdim=None, dropout=0., bias=True, add_bias_kv=False,
tts/modules/ar_dur/commons/transformer.py:153
Method__init__
(self, c, num_heads, dropout, attention_dropout=0.1, relu_dropout=0.1, kernel_size=9, padding
tts/modules/ar_dur/commons/transformer.py:501
Method__init__
(self, c, num_heads, dropout, attention_dropout=0.1, relu_dropout=0.1, kernel_size=9, ffn_hid
tts/modules/ar_dur/commons/transformer.py:544
Method__init__
(self, hidden_size, dropout, kernel_size=9, num_heads=2, ffn_hidden_size=1024)
tts/modules/ar_dur/commons/transformer.py:640
Method__init__
(self, hidden_size, dropout, kernel_size=9, num_heads=2, ffn_hidden_size=1024, post_ln=False)
tts/modules/ar_dur/commons/transformer.py:655
Method__init__
(self, dict_size, hidden_size=256, num_layers=4, kernel_size=9, dropout=0.0, num_heads=2, ffn
tts/modules/ar_dur/commons/transformer.py:735
Method__init__
(self, dim: int, kernel_sizes: tp.List[int] = [3, 1], dilations: tp.List[int] = [1, 1], activ
tts/modules/wavvae/encoder/common_modules/seanet.py:42
Method__init__
(self, normalized_shape: tp.Union[int, tp.List[int], torch.Size], **kwargs)
tts/modules/wavvae/encoder/common_modules/conv.py:97
Method__init__
(self, *args, causal: bool = False, norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {
tts/modules/wavvae/encoder/common_modules/conv.py:108
Method__init__
(self, dimension: int, num_layers: int = 2, skip: bool = True)
tts/modules/wavvae/encoder/common_modules/lstm.py:39
Method__init__
(self, parameters: torch.Tensor, deterministic: bool = False)
tts/modules/wavvae/decoder/diag_gaussian.py:19
Method__init__
( self, dowmsamples: List[int] = [6, 5, 5, 4, 2], )
tts/modules/wavvae/decoder/seanet_encoder.py:22
Method__init__
(self, mult, r)
tts/modules/wavvae/decoder/hifigan_modules.py:60
Method__init__
( self, hop_length=300, sampling_rate=24000, n_mel_channels=80
tts/modules/wavvae/decoder/hifigan_modules.py:100
Method__init__
(self, dim, dilation=1, dim_in=None)
tts/modules/wavvae/decoder/hifigan_modules.py:150
Method__init__
(self, channels, kernel_size=3, dilation=(1, 3, 5))
tts/modules/wavvae/decoder/hifigan_modules.py:175
Method__init__
(self, channels, kernel_size=3)
tts/modules/wavvae/decoder/hifigan_modules.py:214
Method__init__
(self, input_size_, ngf, n_residual_layers, num_band, args, ratios=[5, 5, 4, 3], onnx_export=False,
tts/modules/wavvae/decoder/hifigan_modules.py:229
Method__init__
(self, hparams=None)
tts/modules/wavvae/decoder/wavvae_v3.py:26
Method__init__
Initialize from a file or list, one token per line. Handling of reserved tokens works as follows: - When initializing from a list, we
tts/utils/text_utils/text_encoder.py:124
Method__init__
(self, **kwargs)
tts/utils/commons/hparams.py:27
Method__len__
(self)
tts/utils/text_utils/text_encoder.py:191
Method_conv_forward
( self, x: Tensor, weight: Tensor, bias: Optional[Tensor] )
tts/modules/aligner/whisper_small.py:57
Functionalign_to_figure
(align, dur_info)
tts/utils/audio_utils/plot.py:73
Methodamo_sampling
(z_t, t, t_next, v)
tts/modules/llm_dit/dit.py:151
Functionbuild_token_encoder
(token_list_file)
tts/utils/text_utils/text_encoder.py:274
Methodclear_buffer
(self, *args)
tts/modules/ar_dur/commons/rot_transformer.py:645
Methodclear_buffer
(self, incremental_state)
tts/modules/ar_dur/commons/transformer.py:144
Methodclear_buffer
(self, incremental_state=None)
tts/modules/ar_dur/commons/transformer.py:490
Methodclear_buffer
(self, *args)
tts/modules/ar_dur/commons/transformer.py:669
Methodcompute_conditional_flow
r"""Compute the conditional vector field similar to [3]. ut(x1|x0) = pi/2 (cos(pi*t/2) x1 - sin(pi*t/2) x0), see Eq.(21) [3].
tts/modules/llm_dit/cfm.py:282
Methodcompute_lambda
Compute the lambda function, see Eq.(23) [3]. Parameters ---------- t : FloatTensor, shape (bs) Returns ----
tts/modules/llm_dit/cfm.py:233
Methodcompute_mu_t
r"""Compute the mean of the probability path (Eq.5) from [3]. Parameters ---------- x0 : Tensor, shape (bs, *dim)
tts/modules/llm_dit/cfm.py:260
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