SYMBOL INDEX (440 symbols across 45 files)

FILE: example_for_mac.py
  function patched_torch_load (line 10) | def patched_torch_load(*args, **kwargs):

FILE: gradio_tts_app.py
  function set_seed (line 11) | def set_seed(seed: int):
  function load_model (line 19) | def load_model():
  function generate (line 24) | def generate(model, text, audio_prompt_path, exaggeration, temperature, ...

FILE: gradio_tts_turbo_app.py
  function set_seed (line 69) | def set_seed(seed: int):
  function load_model (line 77) | def load_model():
  function generate (line 83) | def generate(

FILE: gradio_vc_app.py
  function generate (line 10) | def generate(audio, target_voice_path):

FILE: multilingual_app.py
  function default_audio_for_ui (line 109) | def default_audio_for_ui(lang: str) -> str | None:
  function default_text_for_ui (line 113) | def default_text_for_ui(lang: str) -> str:
  function get_supported_languages_display (line 117) | def get_supported_languages_display() -> str:
  function get_or_load_model (line 136) | def get_or_load_model():
  function set_seed (line 158) | def set_seed(seed: int):
  function resolve_audio_prompt (line 167) | def resolve_audio_prompt(language_id: str, provided_path: str | None) ->...
  function generate_tts_audio (line 178) | def generate_tts_audio(
  function on_language_change (line 293) | def on_language_change(lang, current_ref, current_text):

FILE: src/chatterbox/models/s3gen/decoder.py
  function mask_to_bias (line 26) | def mask_to_bias(mask: torch.Tensor, dtype: torch.dtype) -> torch.Tensor:
  class Transpose (line 38) | class Transpose(torch.nn.Module):
    method __init__ (line 39) | def __init__(self, dim0: int, dim1: int):
    method forward (line 44) | def forward(self, x: torch.Tensor):
  class CausalBlock1D (line 49) | class CausalBlock1D(Block1D):
    method __init__ (line 50) | def __init__(self, dim: int, dim_out: int):
    method forward (line 60) | def forward(self, x: torch.Tensor, mask: torch.Tensor):
  class CausalResnetBlock1D (line 65) | class CausalResnetBlock1D(ResnetBlock1D):
    method __init__ (line 66) | def __init__(self, dim: int, dim_out: int, time_emb_dim: int, groups: ...
  class CausalConv1d (line 72) | class CausalConv1d(torch.nn.Conv1d):
    method __init__ (line 73) | def __init__(
    method forward (line 95) | def forward(self, x: torch.Tensor):
  class ConditionalDecoder (line 99) | class ConditionalDecoder(nn.Module):
    method __init__ (line 100) | def __init__(
    method dtype (line 226) | def dtype(self):
    method initialize_weights (line 229) | def initialize_weights(self):
    method forward (line 243) | def forward(self, x, mask, mu, t, spks=None, cond=None, r=None):

FILE: src/chatterbox/models/s3gen/f0_predictor.py
  class ConvRNNF0Predictor (line 19) | class ConvRNNF0Predictor(nn.Module):
    method __init__ (line 20) | def __init__(self,
    method forward (line 52) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: src/chatterbox/models/s3gen/flow.py
  function _repeat_batch_dim (line 30) | def _repeat_batch_dim(tnsr, B, ndim):
  class CausalMaskedDiffWithXvec (line 43) | class CausalMaskedDiffWithXvec(torch.nn.Module):
    method __init__ (line 44) | def __init__(self,
    method compute_loss (line 86) | def compute_loss(
    method inference (line 132) | def inference(self,

FILE: src/chatterbox/models/s3gen/flow_matching.py
  function cast_all (line 22) | def cast_all(*args, dtype):
  class ConditionalCFM (line 26) | class ConditionalCFM(BASECFM):
    method __init__ (line 27) | def __init__(self, in_channels, cfm_params, n_spks=1, spk_emb_dim=64, ...
    method forward (line 42) | def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, c...
    method solve_euler (line 78) | def solve_euler(self, x, t_span, mu, mask, spks, cond, meanflow=False):
    method compute_loss (line 147) | def compute_loss(self, x1, mask, mu, spks=None, cond=None):
  class CausalConditionalCFM (line 189) | class CausalConditionalCFM(ConditionalCFM):
    method __init__ (line 190) | def __init__(self, in_channels=240, cfm_params=CFM_PARAMS, n_spks=1, s...
    method forward (line 196) | def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, c...
    method basic_euler (line 235) | def basic_euler(self, x, t_span, mu, mask, spks, cond):

FILE: src/chatterbox/models/s3gen/hifigan.py
  class Snake (line 34) | class Snake(nn.Module):
    method __init__ (line 50) | def __init__(self, in_features, alpha=1.0, alpha_trainable=True, alpha...
    method forward (line 73) | def forward(self, x):
  function get_padding (line 88) | def get_padding(kernel_size, dilation=1):
  function init_weights (line 91) | def init_weights(m, mean=0.0, std=0.01):
  class ResBlock (line 106) | class ResBlock(torch.nn.Module):
    method __init__ (line 108) | def __init__(
    method forward (line 154) | def forward(self, x: torch.Tensor) -> torch.Tensor:
    method remove_weight_norm (line 163) | def remove_weight_norm(self):
  class SineGen (line 169) | class SineGen(torch.nn.Module):
    method __init__ (line 185) | def __init__(self, samp_rate, harmonic_num=0,
    method _f02uv (line 195) | def _f02uv(self, f0):
    method forward (line 201) | def forward(self, f0):
  class SourceModuleHnNSF (line 234) | class SourceModuleHnNSF(torch.nn.Module):
    method __init__ (line 252) | def __init__(self, sampling_rate, upsample_scale, harmonic_num=0, sine...
    method forward (line 267) | def forward(self, x):
  class HiFTGenerator (line 286) | class HiFTGenerator(nn.Module):
    method __init__ (line 291) | def __init__(
    method remove_weight_norm (line 382) | def remove_weight_norm(self):
    method _stft (line 396) | def _stft(self, x):
    method _istft (line 404) | def _istft(self, magnitude, phase):
    method decode (line 412) | def decode(self, x: torch.Tensor, s: torch.Tensor = torch.zeros(1, 1, ...
    method forward (line 446) | def forward(
    method inference (line 463) | def inference(self, speech_feat: torch.Tensor, cache_source: torch.Ten...

FILE: src/chatterbox/models/s3gen/matcha/decoder.py
  class SinusoidalPosEmb (line 14) | class SinusoidalPosEmb(torch.nn.Module):
    method __init__ (line 15) | def __init__(self, dim):
    method forward (line 20) | def forward(self, x, scale=1000):
  class Block1D (line 32) | class Block1D(torch.nn.Module):
    method __init__ (line 33) | def __init__(self, dim, dim_out, groups=8):
    method forward (line 41) | def forward(self, x, mask):
  class ResnetBlock1D (line 46) | class ResnetBlock1D(torch.nn.Module):
    method __init__ (line 47) | def __init__(self, dim, dim_out, time_emb_dim, groups=8):
    method forward (line 56) | def forward(self, x, mask, time_emb):
  class Downsample1D (line 64) | class Downsample1D(nn.Module):
    method __init__ (line 65) | def __init__(self, dim):
    method forward (line 69) | def forward(self, x):
  class TimestepEmbedding (line 73) | class TimestepEmbedding(nn.Module):
    method __init__ (line 74) | def __init__(
    method forward (line 105) | def forward(self, sample, condition=None):
  class Upsample1D (line 120) | class Upsample1D(nn.Module):
    method __init__ (line 134) | def __init__(self, channels, use_conv=False, use_conv_transpose=True, ...
    method forward (line 148) | def forward(self, inputs):
  class ConformerWrapper (line 161) | class ConformerWrapper(ConformerBlock):
    method __init__ (line 162) | def __init__(  # pylint: disable=useless-super-delegation
    method forward (line 189) | def forward(
  class Decoder (line 200) | class Decoder(nn.Module):
    method __init__ (line 201) | def __init__(
    method get_block (line 319) | def get_block(block_type, dim, attention_head_dim, num_heads, dropout,...
    method initialize_weights (line 345) | def initialize_weights(self):
    method forward (line 363) | def forward(self, x, mask, mu, t, spks=None, cond=None):

FILE: src/chatterbox/models/s3gen/matcha/flow_matching.py
  class BASECFM (line 9) | class BASECFM(torch.nn.Module, ABC):
    method __init__ (line 10) | def __init__(
    method forward (line 30) | def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, c...
    method solve_euler (line 52) | def solve_euler(self, x, t_span, mu, mask, spks, cond):
    method compute_loss (line 84) | def compute_loss(self, x1, mask, mu, spks=None, cond=None):
  class CFM (line 118) | class CFM(BASECFM):
    method __init__ (line 119) | def __init__(self, in_channels, out_channel, cfm_params, decoder_param...

FILE: src/chatterbox/models/s3gen/matcha/text_encoder.py
  function sequence_mask (line 10) | def sequence_mask(length, max_length=None):
  class LayerNorm (line 18) | class LayerNorm(nn.Module):
    method __init__ (line 19) | def __init__(self, channels, eps=1e-4):
    method forward (line 27) | def forward(self, x):
  class ConvReluNorm (line 39) | class ConvReluNorm(nn.Module):
    method __init__ (line 40) | def __init__(self, in_channels, hidden_channels, out_channels, kernel_...
    method forward (line 63) | def forward(self, x, x_mask):
  class DurationPredictor (line 73) | class DurationPredictor(nn.Module):
    method __init__ (line 74) | def __init__(self, in_channels, filter_channels, kernel_size, p_dropout):
    method forward (line 87) | def forward(self, x, x_mask):
  class RotaryPositionalEmbeddings (line 100) | class RotaryPositionalEmbeddings(nn.Module):
    method __init__ (line 110) | def __init__(self, d: int, base: int = 10_000):
    method _build_cache (line 122) | def _build_cache(self, x: torch.Tensor):
    method _neg_half (line 150) | def _neg_half(self, x: torch.Tensor):
    method forward (line 157) | def forward(self, x: torch.Tensor):
  class MultiHeadAttention (line 178) | class MultiHeadAttention(nn.Module):
    method __init__ (line 179) | def __init__(
    method forward (line 219) | def forward(self, x, c, attn_mask=None):
    method attention (line 229) | def attention(self, query, key, value, mask=None):
    method _attention_bias_proximal (line 252) | def _attention_bias_proximal(length):
  class FFN (line 258) | class FFN(nn.Module):
    method __init__ (line 259) | def __init__(self, in_channels, out_channels, filter_channels, kernel_...
    method forward (line 271) | def forward(self, x, x_mask):
  class Encoder (line 279) | class Encoder(nn.Module):
    method __init__ (line 280) | def __init__(
    method forward (line 317) | def forward(self, x, x_mask):
  class TextEncoder (line 331) | class TextEncoder(nn.Module):
    method __init__ (line 332) | def __init__(
    method forward (line 381) | def forward(self, x, x_lengths, spks=None):

FILE: src/chatterbox/models/s3gen/matcha/transformer.py
  class SnakeBeta (line 17) | class SnakeBeta(nn.Module):
    method __init__ (line 35) | def __init__(self, in_features, out_features, alpha=1.0, alpha_trainab...
    method forward (line 64) | def forward(self, x):
  class FeedForward (line 83) | class FeedForward(nn.Module):
    method __init__ (line 96) | def __init__(
    method forward (line 131) | def forward(self, hidden_states):
  class BasicTransformerBlock (line 138) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 159) | def __init__(
    method set_chunk_feed_forward (line 238) | def set_chunk_feed_forward(self, chunk_size: Optional[int], dim: int):
    method forward (line 243) | def forward(

FILE: src/chatterbox/models/s3gen/s3gen.py
  function drop_invalid_tokens (line 36) | def drop_invalid_tokens(x):
  function get_resampler (line 43) | def get_resampler(src_sr, dst_sr, device):
  class S3Token2Mel (line 47) | class S3Token2Mel(torch.nn.Module):
    method __init__ (line 53) | def __init__(self, meanflow=False):
    method device (line 109) | def device(self):
    method dtype (line 114) | def dtype(self):
    method embed_ref (line 118) | def embed_ref(
    method forward (line 173) | def forward(
  class S3Token2Wav (line 232) | class S3Token2Wav(S3Token2Mel):
    method __init__ (line 241) | def __init__(self, meanflow=False):
    method forward (line 261) | def forward(
    method flow_inference (line 301) | def flow_inference(
    method hift_inference (line 324) | def hift_inference(self, speech_feat, cache_source: torch.Tensor = None):
    method inference (line 330) | def inference(

FILE: src/chatterbox/models/s3gen/transformer/activation.py
  class Swish (line 24) | class Swish(torch.nn.Module):
    method forward (line 27) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Snake (line 34) | class Snake(nn.Module):
    method __init__ (line 50) | def __init__(self, in_features, alpha=1.0, alpha_trainable=True, alpha...
    method forward (line 73) | def forward(self, x):

FILE: src/chatterbox/models/s3gen/transformer/attention.py
  class MultiHeadedAttention (line 26) | class MultiHeadedAttention(nn.Module):
    method __init__ (line 36) | def __init__(self,
    method forward_qkv (line 53) | def forward_qkv(
    method forward_attention (line 82) | def forward_attention(
    method forward (line 129) | def forward(
  class RelPositionMultiHeadedAttention (line 200) | class RelPositionMultiHeadedAttention(MultiHeadedAttention):
    method __init__ (line 209) | def __init__(self,
    method rel_shift (line 225) | def rel_shift(self, x: torch.Tensor) -> torch.Tensor:
    method forward (line 249) | def forward(

FILE: src/chatterbox/models/s3gen/transformer/convolution.py
  class ConvolutionModule (line 24) | class ConvolutionModule(nn.Module):
    method __init__ (line 27) | def __init__(self,
    method forward (line 90) | def forward(

FILE: src/chatterbox/models/s3gen/transformer/embedding.py
  class PositionalEncoding (line 26) | class PositionalEncoding(torch.nn.Module):
    method __init__ (line 37) | def __init__(self,
    method forward (line 59) | def forward(self,
    method position_encoding (line 79) | def position_encoding(self,
  class RelPositionalEncoding (line 120) | class RelPositionalEncoding(PositionalEncoding):
    method __init__ (line 129) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 5...
    method forward (line 133) | def forward(self,
  class WhisperPositionalEncoding (line 150) | class WhisperPositionalEncoding(PositionalEncoding):
    method __init__ (line 154) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 1...
  class LearnablePositionalEncoding (line 167) | class LearnablePositionalEncoding(PositionalEncoding):
    method __init__ (line 171) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 4...
  class NoPositionalEncoding (line 178) | class NoPositionalEncoding(torch.nn.Module):
    method __init__ (line 182) | def __init__(self, d_model: int, dropout_rate: float):
    method forward (line 187) | def forward(self,
    method position_encoding (line 196) | def position_encoding(self, offset: Union[int, torch.Tensor],
  class EspnetRelPositionalEncoding (line 201) | class EspnetRelPositionalEncoding(torch.nn.Module):
    method __init__ (line 215) | def __init__(self, d_model: int, dropout_rate: float, max_len: int = 5...
    method extend_pe (line 224) | def extend_pe(self, x: torch.Tensor):
    method forward (line 256) | def forward(self, x: torch.Tensor, offset: Union[int, torch.Tensor] = ...
    method position_encoding (line 272) | def position_encoding(self,

FILE: src/chatterbox/models/s3gen/transformer/encoder_layer.py
  class TransformerEncoderLayer (line 24) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 40) | def __init__(
    method forward (line 58) | def forward(
  class ConformerEncoderLayer (line 109) | class ConformerEncoderLayer(nn.Module):
    method __init__ (line 129) | def __init__(
    method forward (line 160) | def forward(

FILE: src/chatterbox/models/s3gen/transformer/positionwise_feed_forward.py
  class PositionwiseFeedForward (line 20) | class PositionwiseFeedForward(torch.nn.Module):
    method __init__ (line 33) | def __init__(
    method forward (line 47) | def forward(self, xs: torch.Tensor) -> torch.Tensor:
  class MoEFFNLayer (line 58) | class MoEFFNLayer(torch.nn.Module):
    method __init__ (line 75) | def __init__(
    method forward (line 91) | def forward(self, xs: torch.Tensor) -> torch.Tensor:

FILE: src/chatterbox/models/s3gen/transformer/subsampling.py
  class BaseSubsampling (line 23) | class BaseSubsampling(torch.nn.Module):
    method __init__ (line 25) | def __init__(self):
    method position_encoding (line 30) | def position_encoding(self, offset: Union[int, torch.Tensor],
  class EmbedinigNoSubsampling (line 35) | class EmbedinigNoSubsampling(BaseSubsampling):
    method __init__ (line 39) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 45) | def forward(
  class LinearNoSubsampling (line 69) | class LinearNoSubsampling(BaseSubsampling):
    method __init__ (line 79) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 92) | def forward(
  class Conv1dSubsampling2 (line 116) | class Conv1dSubsampling2(BaseSubsampling):
    method __init__ (line 128) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 145) | def forward(
  class Conv2dSubsampling4 (line 173) | class Conv2dSubsampling4(BaseSubsampling):
    method __init__ (line 183) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 202) | def forward(
  class Conv2dSubsampling6 (line 230) | class Conv2dSubsampling6(BaseSubsampling):
    method __init__ (line 239) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 256) | def forward(
  class Conv2dSubsampling8 (line 282) | class Conv2dSubsampling8(BaseSubsampling):
    method __init__ (line 292) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 311) | def forward(
  class LegacyLinearNoSubsampling (line 338) | class LegacyLinearNoSubsampling(BaseSubsampling):
    method __init__ (line 348) | def __init__(self, idim: int, odim: int, dropout_rate: float,
    method forward (line 362) | def forward(

FILE: src/chatterbox/models/s3gen/transformer/upsample_encoder.py
  class Upsample1D (line 37) | class Upsample1D(nn.Module):
    method __init__ (line 51) | def __init__(self, channels: int, out_channels: int, stride: int = 2):
    method forward (line 59) | def forward(self, inputs: torch.Tensor, input_lengths: torch.Tensor):
  class PreLookaheadLayer (line 66) | class PreLookaheadLayer(nn.Module):
    method __init__ (line 67) | def __init__(self, channels: int, pre_lookahead_len: int = 1):
    method forward (line 81) | def forward(self, inputs: torch.Tensor) -> torch.Tensor:
  class UpsampleConformerEncoder (line 99) | class UpsampleConformerEncoder(torch.nn.Module):
    method __init__ (line 101) | def __init__(
    method output_size (line 234) | def output_size(self) -> int:
    method forward (line 237) | def forward(
    method forward_layers (line 306) | def forward_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,
    method forward_up_layers (line 313) | def forward_up_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,

FILE: src/chatterbox/models/s3gen/utils/intmeanflow.py
  function get_intmeanflow_time_mixer (line 5) | def get_intmeanflow_time_mixer(dims):

FILE: src/chatterbox/models/s3gen/utils/mask.py
  function subsequent_chunk_mask (line 54) | def subsequent_chunk_mask(
  function add_optional_chunk_mask (line 89) | def add_optional_chunk_mask(xs: torch.Tensor,
  function make_pad_mask (line 167) | def make_pad_mask(lengths: torch.Tensor, max_len: int = 0) -> torch.Tensor:

FILE: src/chatterbox/models/s3gen/utils/mel.py
  function dynamic_range_compression_torch (line 15) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
  function spectral_normalize_torch (line 19) | def spectral_normalize_torch(magnitudes):
  function mel_spectrogram (line 36) | def mel_spectrogram(y, n_fft=1920, num_mels=80, sampling_rate=24000, hop...

FILE: src/chatterbox/models/s3gen/xvector.py
  function pad_list (line 15) | def pad_list(xs, pad_value):
  function extract_feature (line 45) | def extract_feature(audio):
  class BasicResBlock (line 61) | class BasicResBlock(torch.nn.Module):
    method __init__ (line 64) | def __init__(self, in_planes, planes, stride=1):
    method forward (line 86) | def forward(self, x):
  class FCM (line 94) | class FCM(torch.nn.Module):
    method __init__ (line 95) | def __init__(self, block=BasicResBlock, num_blocks=[2, 2], m_channels=...
    method _make_layer (line 110) | def _make_layer(self, block, planes, num_blocks, stride):
    method forward (line 118) | def forward(self, x):
  function get_nonlinear (line 130) | def get_nonlinear(config_str, channels):
  function statistics_pooling (line 146) | def statistics_pooling(x, dim=-1, keepdim=False, unbiased=True, eps=1e-2):
  class StatsPool (line 155) | class StatsPool(torch.nn.Module):
    method forward (line 156) | def forward(self, x):
  class TDNNLayer (line 160) | class TDNNLayer(torch.nn.Module):
    method __init__ (line 161) | def __init__(
    method forward (line 189) | def forward(self, x):
  class CAMLayer (line 195) | class CAMLayer(torch.nn.Module):
    method __init__ (line 196) | def __init__(
    method forward (line 214) | def forward(self, x):
    method seg_pooling (line 221) | def seg_pooling(self, x, seg_len=100, stype="avg"):
  class CAMDenseTDNNLayer (line 234) | class CAMDenseTDNNLayer(torch.nn.Module):
    method __init__ (line 235) | def __init__(
    method bn_function (line 266) | def bn_function(self, x):
    method forward (line 269) | def forward(self, x):
  class CAMDenseTDNNBlock (line 278) | class CAMDenseTDNNBlock(torch.nn.ModuleList):
    method __init__ (line 279) | def __init__(
    method forward (line 307) | def forward(self, x):
  class TransitLayer (line 313) | class TransitLayer(torch.nn.Module):
    method __init__ (line 314) | def __init__(self, in_channels, out_channels, bias=True, config_str="b...
    method forward (line 319) | def forward(self, x):
  class DenseLayer (line 325) | class DenseLayer(torch.nn.Module):
    method __init__ (line 326) | def __init__(self, in_channels, out_channels, bias=False, config_str="...
    method forward (line 331) | def forward(self, x):
  class CAMPPlus (line 340) | class CAMPPlus(torch.nn.Module):
    method __init__ (line 341) | def __init__(
    method forward (line 417) | def forward(self, x):
    method inference (line 425) | def inference(self, audio_list):

FILE: src/chatterbox/models/s3tokenizer/__init__.py
  function drop_invalid_tokens (line 16) | def drop_invalid_tokens(x):

FILE: src/chatterbox/models/s3tokenizer/s3tokenizer.py
  class S3Tokenizer (line 22) | class S3Tokenizer(S3TokenizerV2):
    method __init__ (line 31) | def __init__(
    method pad (line 54) | def pad(self, wavs, sr) -> List[torch.Tensor]:
    method _prepare_audio (line 78) | def _prepare_audio(self, wavs):
    method forward (line 91) | def forward(
    method log_mel_spectrogram (line 128) | def log_mel_spectrogram(

FILE: src/chatterbox/models/t3/inference/alignment_stream_analyzer.py
  class AlignmentAnalysisResult (line 17) | class AlignmentAnalysisResult:
  class AlignmentStreamAnalyzer (line 32) | class AlignmentStreamAnalyzer:
    method __init__ (line 33) | def __init__(self, tfmr, queue, text_tokens_slice, alignment_layer_idx...
    method _add_attention_spy (line 67) | def _add_attention_spy(self, tfmr, buffer_idx, layer_idx, head_idx):
    method step (line 92) | def step(self, logits, next_token=None):

FILE: src/chatterbox/models/t3/inference/t3_hf_backend.py
  class T3HuggingfaceBackend (line 9) | class T3HuggingfaceBackend(LlamaPreTrainedModel, GenerationMixin):
    method __init__ (line 17) | def __init__(
    method prepare_inputs_for_generation (line 36) | def prepare_inputs_for_generation(
    method forward (line 73) | def forward(

FILE: src/chatterbox/models/t3/modules/cond_enc.py
  class T3Cond (line 12) | class T3Cond:
    method to (line 24) | def to(self, *, device=None, dtype=None):
    method save (line 32) | def save(self, fpath):
    method load (line 36) | def load(fpath, map_location="cpu"):
  class T3CondEnc (line 41) | class T3CondEnc(nn.Module):
    method __init__ (line 46) | def __init__(self, hp: T3Config):
    method forward (line 64) | def forward(self, cond: T3Cond):

FILE: src/chatterbox/models/t3/modules/learned_pos_emb.py
  class LearnedPositionEmbeddings (line 7) | class LearnedPositionEmbeddings(nn.Module):
    method __init__ (line 8) | def __init__(self, seq_len, model_dim, init=.02):
    method forward (line 14) | def forward(self, x):
    method get_fixed_embedding (line 21) | def get_fixed_embedding(self, idx: 'Union[int, Tensor]'):

FILE: src/chatterbox/models/t3/modules/perceiver.py
  class RelativePositionBias (line 12) | class RelativePositionBias(nn.Module):
    method __init__ (line 13) | def __init__(self, scale, causal=False, num_buckets=32, max_distance=1...
    method _relative_position_bucket (line 22) | def _relative_position_bucket(relative_position, causal=True, num_buck...
    method forward (line 43) | def forward(self, qk_dots):
  class AttentionQKV (line 55) | class AttentionQKV(nn.Module):
    method __init__ (line 56) | def __init__(self, n_heads, head_dim, dropout_rate=0.1, scale=None, fl...
    method setup_flash_config (line 66) | def setup_flash_config(self):
    method forward (line 75) | def forward(self, q, k, v, mask=None):
    method scaled_dot_product_attention (line 84) | def scaled_dot_product_attention(self, q, k, v, mask=None):
    method flash_attention (line 92) | def flash_attention(self, q, k, v, mask=None):
    method split_heads (line 102) | def split_heads(self, x):
    method combine_heads (line 107) | def combine_heads(self, x):
  class AttentionBlock2 (line 113) | class AttentionBlock2(nn.Module):
    method __init__ (line 119) | def __init__(
    method forward (line 156) | def forward(self, x1, x2, mask=None):
  class Perceiver (line 173) | class Perceiver(nn.Module):
    method __init__ (line 175) | def __init__(self, pre_attention_query_token=32, pre_attention_query_s...
    method forward (line 200) | def forward(self, h):

FILE: src/chatterbox/models/t3/modules/t3_config.py
  class T3Config (line 4) | class T3Config:
    method __init__ (line 5) | def __init__(self, text_tokens_dict_size=704):
    method n_channels (line 26) | def n_channels(self):
    method is_multilingual (line 30) | def is_multilingual(self):
    method english_only (line 34) | def english_only(cls):
    method multilingual (line 39) | def multilingual(cls):

FILE: src/chatterbox/models/t3/t3.py
  function _ensure_BOT_EOT (line 34) | def _ensure_BOT_EOT(text_tokens: Tensor, hp):
  class T3 (line 40) | class T3(nn.Module):
    method __init__ (line 50) | def __init__(self, hp=None):
    method device (line 90) | def device(self):
    method prepare_conditioning (line 93) | def prepare_conditioning(self, t3_cond: T3Cond):
    method prepare_input_embeds (line 103) | def prepare_input_embeds(
    method forward (line 133) | def forward(
    method loss (line 190) | def loss(
    method inference (line 227) | def inference(
    method inference_turbo (line 415) | def inference_turbo(self, t3_cond, text_tokens, temperature=0.8, top_k...

FILE: src/chatterbox/models/tokenizers/tokenizer.py
  class EnTokenizer (line 20) | class EnTokenizer:
    method __init__ (line 21) | def __init__(self, vocab_file_path):
    method check_vocabset_sot_eot (line 25) | def check_vocabset_sot_eot(self):
    method text_to_tokens (line 30) | def text_to_tokens(self, text: str):
    method encode (line 35) | def encode(self, txt: str):
    method decode (line 44) | def decode(self, seq):
  function is_kanji (line 65) | def is_kanji(c: str) -> bool:
  function is_katakana (line 70) | def is_katakana(c: str) -> bool:
  function hiragana_normalize (line 75) | def hiragana_normalize(text: str) -> str:
  function add_hebrew_diacritics (line 117) | def add_hebrew_diacritics(text: str) -> str:
  function korean_normalize (line 136) | def korean_normalize(text: str) -> str:
  class ChineseCangjieConverter (line 157) | class ChineseCangjieConverter:
    method __init__ (line 160) | def __init__(self, model_dir=None):
    method _load_cangjie_mapping (line 167) | def _load_cangjie_mapping(self, model_dir=None):
    method _init_segmenter (line 190) | def _init_segmenter(self):
    method _cangjie_encode (line 199) | def _cangjie_encode(self, glyph: str):
    method __call__ (line 211) | def __call__(self, text):
  function add_russian_stress (line 237) | def add_russian_stress(text: str) -> str:
  class MTLTokenizer (line 256) | class MTLTokenizer:
    method __init__ (line 257) | def __init__(self, vocab_file_path):
    method check_vocabset_sot_eot (line 263) | def check_vocabset_sot_eot(self):
    method preprocess_text (line 268) | def preprocess_text(self, raw_text: str, language_id: str = None, lowe...
    method text_to_tokens (line 280) | def text_to_tokens(self, text: str, language_id: str = None, lowercase...
    method encode (line 285) | def encode(self, txt: str, language_id: str = None, lowercase: bool = ...
    method decode (line 307) | def decode(self, seq):

FILE: src/chatterbox/models/utils.py
  class AttrDict (line 1) | class AttrDict(dict):
    method __init__ (line 2) | def __init__(self, *args, **kwargs):

FILE: src/chatterbox/models/voice_encoder/config.py
  class VoiceEncConfig (line 1) | class VoiceEncConfig:

FILE: src/chatterbox/models/voice_encoder/melspec.py
  function mel_basis (line 9) | def mel_basis(hp):
  function preemphasis (line 19) | def preemphasis(wav, hp):
  function melspectrogram (line 26) | def melspectrogram(wav, hp, pad=True):
  function _stft (line 54) | def _stft(y, hp, pad=True):
  function _amp_to_db (line 67) | def _amp_to_db(x, hp):
  function _db_to_amp (line 71) | def _db_to_amp(x):
  function _normalize (line 75) | def _normalize(s, hp, headroom_db=15):

FILE: src/chatterbox/models/voice_encoder/voice_encoder.py
  function pack (line 16) | def pack(arrays, seq_len: int=None, pad_value=0):
  function get_num_wins (line 54) | def get_num_wins(
  function get_frame_step (line 69) | def get_frame_step(
  function stride_as_partials (line 84) | def stride_as_partials(
  class VoiceEncoder (line 119) | class VoiceEncoder(nn.Module):
    method __init__ (line 120) | def __init__(self, hp=VoiceEncConfig()):
    method device (line 136) | def device(self):
    method forward (line 139) | def forward(self, mels: torch.FloatTensor):
    method inference (line 162) | def inference(self, mels: torch.Tensor, mel_lens, overlap=0.5, rate: f...
    method utt_to_spk_embed (line 202) | def utt_to_spk_embed(utt_embeds: np.ndarray):
    method voice_similarity (line 212) | def voice_similarity(embeds_x: np.ndarray, embeds_y: np.ndarray):
    method embeds_from_mels (line 220) | def embeds_from_mels(
    method embeds_from_wavs (line 246) | def embeds_from_wavs(

FILE: src/chatterbox/mtl_tts.py
  function punc_norm (line 51) | def punc_norm(text: str) -> str:
  class Conditionals (line 94) | class Conditionals:
    method to (line 113) | def to(self, device):
    method save (line 120) | def save(self, fpath: Path):
    method load (line 128) | def load(cls, fpath, map_location="cpu"):
  class ChatterboxMultilingualTTS (line 135) | class ChatterboxMultilingualTTS:
    method __init__ (line 139) | def __init__(
    method get_supported_languages (line 158) | def get_supported_languages(cls):
    method from_local (line 163) | def from_local(cls, ckpt_dir, device) -> 'ChatterboxMultilingualTTS':
    method from_pretrained (line 202) | def from_pretrained(cls, device: torch.device) -> 'ChatterboxMultiling...
    method prepare_conditionals (line 222) | def prepare_conditionals(self, wav_fpath, exaggeration=0.5):
    method generate (line 249) | def generate(

FILE: src/chatterbox/tts.py
  function punc_norm (line 22) | def punc_norm(text: str) -> str:
  class Conditionals (line 65) | class Conditionals:
    method to (line 84) | def to(self, device):
    method save (line 91) | def save(self, fpath: Path):
    method load (line 99) | def load(cls, fpath, map_location="cpu"):
  class ChatterboxTTS (line 106) | class ChatterboxTTS:
    method __init__ (line 110) | def __init__(
    method from_local (line 129) | def from_local(cls, ckpt_dir, device) -> 'ChatterboxTTS':
    method from_pretrained (line 168) | def from_pretrained(cls, device) -> 'ChatterboxTTS':
    method prepare_conditionals (line 182) | def prepare_conditionals(self, wav_fpath, exaggeration=0.5):
    method generate (line 208) | def generate(

FILE: src/chatterbox/tts_turbo.py
  function punc_norm (line 29) | def punc_norm(text: str) -> str:
  class Conditionals (line 69) | class Conditionals:
    method to (line 88) | def to(self, device):
    method save (line 95) | def save(self, fpath: Path):
    method load (line 103) | def load(cls, fpath, map_location="cpu"):
  class ChatterboxTurboTTS (line 110) | class ChatterboxTurboTTS:
    method __init__ (line 114) | def __init__(
    method from_local (line 133) | def from_local(cls, ckpt_dir, device) -> 'ChatterboxTurboTTS':
    method from_pretrained (line 186) | def from_pretrained(cls, device) -> 'ChatterboxTurboTTS':
    method norm_loudness (line 204) | def norm_loudness(self, wav, sr, target_lufs=-27):
    method prepare_conditionals (line 217) | def prepare_conditionals(self, wav_fpath, exaggeration=0.5, norm_loudn...
    method generate (line 248) | def generate(

FILE: src/chatterbox/vc.py
  class ChatterboxVC (line 16) | class ChatterboxVC:
    method __init__ (line 20) | def __init__(
    method from_local (line 39) | def from_local(cls, ckpt_dir, device) -> 'ChatterboxVC':
    method from_pretrained (line 62) | def from_pretrained(cls, device) -> 'ChatterboxVC':
    method set_target_voice (line 76) | def set_target_voice(self, wav_fpath):
    method generate (line 83) | def generate(