SYMBOL INDEX (374 symbols across 28 files)

FILE: boson_multimodal/audio_processing/descriptaudiocodec/dac/model/base.py
  class DACFile (line 16) | class DACFile:
    method save (line 28) | def save(self, path):
    method load (line 47) | def load(cls, path):
  class CodecMixin (line 55) | class CodecMixin:
    method padding (line 57) | def padding(self):
    method padding (line 63) | def padding(self, value):
    method get_delay (line 78) | def get_delay(self):
    method get_output_length (line 104) | def get_output_length(self, input_length):
    method compress (line 122) | def compress(
    method decompress (line 230) | def decompress(

FILE: boson_multimodal/audio_processing/descriptaudiocodec/dac/model/dac.py
  function init_weights (line 18) | def init_weights(m):
  class ResidualUnit (line 24) | class ResidualUnit(nn.Module):
    method __init__ (line 25) | def __init__(self, dim: int = 16, dilation: int = 1):
    method forward (line 35) | def forward(self, x):
  class EncoderBlock (line 43) | class EncoderBlock(nn.Module):
    method __init__ (line 44) | def __init__(self, dim: int = 16, stride: int = 1):
    method forward (line 60) | def forward(self, x):
  class Encoder (line 64) | class Encoder(nn.Module):
    method __init__ (line 65) | def __init__(
    method forward (line 90) | def forward(self, x):
  class DecoderBlock (line 94) | class DecoderBlock(nn.Module):
    method __init__ (line 95) | def __init__(self, input_dim: int = 16, output_dim: int = 8, stride: i...
    method forward (line 112) | def forward(self, x):
  class Decoder (line 116) | class Decoder(nn.Module):
    method __init__ (line 117) | def __init__(
    method forward (line 148) | def forward(self, x):
  class DAC (line 152) | class DAC(BaseModel, CodecMixin):
    method __init__ (line 153) | def __init__(
    method preprocess (line 203) | def preprocess(self, audio_data, sample_rate):
    method encode (line 214) | def encode(
    method decode (line 252) | def decode(self, z: torch.Tensor):
    method forward (line 271) | def forward(

FILE: boson_multimodal/audio_processing/descriptaudiocodec/dac/nn/layers.py
  function WNConv1d (line 9) | def WNConv1d(*args, **kwargs):
  function WNConvTranspose1d (line 13) | def WNConvTranspose1d(*args, **kwargs):
  function snake (line 19) | def snake(x, alpha):
  class Snake1d (line 27) | class Snake1d(nn.Module):
    method __init__ (line 28) | def __init__(self, channels):
    method forward (line 32) | def forward(self, x):

FILE: boson_multimodal/audio_processing/descriptaudiocodec/dac/nn/quantize.py
  class VectorQuantize (line 13) | class VectorQuantize(nn.Module):
    method __init__ (line 25) | def __init__(self, input_dim: int, codebook_size: int, codebook_dim: i...
    method forward (line 34) | def forward(self, z):
    method embed_code (line 70) | def embed_code(self, embed_id):
    method decode_code (line 73) | def decode_code(self, embed_id):
    method decode_latents (line 76) | def decode_latents(self, latents):
  class ResidualVectorQuantize (line 95) | class ResidualVectorQuantize(nn.Module):
    method __init__ (line 101) | def __init__(
    method forward (line 122) | def forward(self, z, n_quantizers: int = None):
    method from_codes (line 191) | def from_codes(self, codes: torch.Tensor):
    method from_latents (line 213) | def from_latents(self, latents: torch.Tensor):

FILE: boson_multimodal/audio_processing/higgs_audio_tokenizer.py
  class EncodedResult (line 24) | class EncodedResult:
    method __init__ (line 25) | def __init__(self, audio_codes):
  class HiggsAudioFeatureExtractor (line 29) | class HiggsAudioFeatureExtractor(nn.Module):
    method __init__ (line 30) | def __init__(self, sampling_rate=16000):
    method forward (line 34) | def forward(self, raw_audio, sampling_rate=16000, return_tensors="pt"):
  class HiggsAudioTokenizer (line 43) | class HiggsAudioTokenizer(nn.Module):
    method __init__ (line 44) | def __init__(
    method tps (line 138) | def tps(self):
    method sampling_rate (line 142) | def sampling_rate(self):
    method num_codebooks (line 146) | def num_codebooks(self):
    method codebook_size (line 150) | def codebook_size(self):
    method get_last_layer (line 153) | def get_last_layer(self):
    method calculate_rec_loss (line 156) | def calculate_rec_loss(self, rec, target):
    method get_regress_target (line 164) | def get_regress_target(self, x):
    method forward (line 209) | def forward(self, x: torch.Tensor, bw: int):
    method encode (line 237) | def encode(self, audio_path_or_wv, sr=None, loudness_normalize=False, ...
    method _xcodec_encode (line 263) | def _xcodec_encode(self, x: torch.Tensor, target_bw: Optional[int] = N...
    method decode (line 296) | def decode(self, vq_code: torch.Tensor) -> torch.Tensor:
  function load_higgs_audio_tokenizer (line 312) | def load_higgs_audio_tokenizer(tokenizer_name_or_path, device="cuda"):

FILE: boson_multimodal/audio_processing/quantization/ac.py
  function build_stable_quantized_cdf (line 18) | def build_stable_quantized_cdf(
  class ArithmeticCoder (line 56) | class ArithmeticCoder:
    method __init__ (line 96) | def __init__(self, fo: tp.IO[bytes], total_range_bits: int = 24):
    method delta (line 107) | def delta(self) -> int:
    method _flush_common_prefix (line 111) | def _flush_common_prefix(self):
    method push (line 130) | def push(self, symbol: int, quantized_cdf: torch.Tensor):
    method flush (line 160) | def flush(self):
  class ArithmeticDecoder (line 169) | class ArithmeticDecoder:
    method __init__ (line 185) | def __init__(self, fo: tp.IO[bytes], total_range_bits: int = 24):
    method delta (line 198) | def delta(self) -> int:
    method _flush_common_prefix (line 201) | def _flush_common_prefix(self):
    method pull (line 217) | def pull(self, quantized_cdf: torch.Tensor) -> tp.Optional[int]:
  function test (line 263) | def test():

FILE: boson_multimodal/audio_processing/quantization/core_vq.py
  function default (line 44) | def default(val: tp.Any, d: tp.Any) -> tp.Any:
  function ema_inplace (line 48) | def ema_inplace(moving_avg, new, decay: float):
  function laplace_smoothing (line 52) | def laplace_smoothing(x, n_categories: int, epsilon: float = 1e-5):
  function uniform_init (line 56) | def uniform_init(*shape: int):
  function sample_vectors (line 62) | def sample_vectors(samples, num: int):
  function kmeans (line 73) | def kmeans(samples, num_clusters: int, num_iters: int = 10):
  class EuclideanCodebook (line 96) | class EuclideanCodebook(nn.Module):
    method __init__ (line 112) | def __init__(
    method init_embed_ (line 139) | def init_embed_(self, data):
    method replace_ (line 151) | def replace_(self, samples, mask):
    method expire_codes_ (line 155) | def expire_codes_(self, batch_samples):
    method preprocess (line 167) | def preprocess(self, x):
    method quantize (line 171) | def quantize(self, x):
    method postprocess_emb (line 177) | def postprocess_emb(self, embed_ind, shape):
    method dequantize (line 180) | def dequantize(self, embed_ind):
    method encode (line 184) | def encode(self, x):
    method decode (line 194) | def decode(self, embed_ind):
    method forward (line 198) | def forward(self, x):
  class VectorQuantization (line 225) | class VectorQuantization(nn.Module):
    method __init__ (line 242) | def __init__(
    method codebook (line 276) | def codebook(self):
    method encode (line 279) | def encode(self, x):
    method decode (line 285) | def decode(self, embed_ind):
    method forward (line 291) | def forward(self, x):
  class ResidualVectorQuantization (line 313) | class ResidualVectorQuantization(nn.Module):
    method __init__ (line 318) | def __init__(self, *, num_quantizers, **kwargs):
    method forward (line 322) | def forward(self, x, n_q: tp.Optional[int] = None):
    method encode (line 342) | def encode(self, x: torch.Tensor, n_q: tp.Optional[int] = None) -> tor...
    method decode (line 354) | def decode(self, q_indices: torch.Tensor) -> torch.Tensor:

FILE: boson_multimodal/audio_processing/quantization/core_vq_lsx_version.py
  function default (line 54) | def default(val: tp.Any, d: tp.Any) -> tp.Any:
  function ema_inplace (line 58) | def ema_inplace(moving_avg, new, decay: float):
  function laplace_smoothing (line 62) | def laplace_smoothing(x, n_categories: int, epsilon: float = 1e-5):
  function uniform_init (line 66) | def uniform_init(*shape: int):
  function sample_vectors (line 72) | def sample_vectors(samples, num: int):
  function kmeans (line 83) | def kmeans(samples, num_clusters: int, num_iters: int = 10, frames_to_us...
  class EuclideanCodebook (line 132) | class EuclideanCodebook(nn.Module):
    method __init__ (line 148) | def __init__(
    method init_embed_ (line 179) | def init_embed_(self, data):
    method replace_ (line 200) | def replace_(self, samples, mask):
    method expire_codes_ (line 204) | def expire_codes_(self, batch_samples):
    method preprocess (line 221) | def preprocess(self, x):
    method quantize (line 225) | def quantize(self, x):
    method postprocess_emb (line 231) | def postprocess_emb(self, embed_ind, shape):
    method dequantize (line 234) | def dequantize(self, embed_ind):
    method encode (line 238) | def encode(self, x):
    method decode (line 248) | def decode(self, embed_ind):
    method forward (line 252) | def forward(self, x):
  class VectorQuantization (line 290) | class VectorQuantization(nn.Module):
    method __init__ (line 307) | def __init__(
    method codebook (line 341) | def codebook(self):
    method encode (line 344) | def encode(self, x):
    method decode (line 350) | def decode(self, embed_ind):
    method forward (line 356) | def forward(self, x):
  class ResidualVectorQuantization (line 378) | class ResidualVectorQuantization(nn.Module):
    method __init__ (line 383) | def __init__(self, *, num_quantizers, **kwargs):
    method forward (line 387) | def forward(self, x, n_q: tp.Optional[int] = None):
    method encode (line 407) | def encode(self, x: torch.Tensor, n_q: tp.Optional[int] = None) -> tor...
    method decode (line 419) | def decode(self, q_indices: torch.Tensor) -> torch.Tensor:

FILE: boson_multimodal/audio_processing/quantization/ddp_utils.py
  function set_random_seed (line 17) | def set_random_seed(seed):
  function is_logging_process (line 24) | def is_logging_process():
  function get_logger (line 28) | def get_logger(cfg, name=None):
  class SyncFunction (line 36) | class SyncFunction(torch.autograd.Function):
    method forward (line 39) | def forward(ctx, tensor):
    method backward (line 50) | def backward(ctx, grad_output):
  function get_timestamp (line 59) | def get_timestamp():
  function get_commit_hash (line 63) | def get_commit_hash():
  class DDP (line 68) | class DDP(DistributedDataParallel):
    method forward (line 73) | def forward(self, *inputs, **kwargs):  # pragma: no cover

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

FILE: boson_multimodal/audio_processing/quantization/vq.py
  class QuantizedResult (line 21) | class QuantizedResult:
  class ResidualVectorQuantizer (line 29) | class ResidualVectorQuantizer(nn.Module):
    method __init__ (line 43) | def __init__(
    method forward (line 74) | def forward(self, x: torch.Tensor, sample_rate: int, bandwidth: tp.Opt...
    method get_num_quantizers_for_bandwidth (line 92) | def get_num_quantizers_for_bandwidth(self, sample_rate: int, bandwidth...
    method get_bandwidth_per_quantizer (line 100) | def get_bandwidth_per_quantizer(self, sample_rate: int):
    method encode (line 104) | def encode(self, x: torch.Tensor, sample_rate: int, bandwidth: tp.Opti...
    method decode (line 113) | def decode(self, codes: torch.Tensor) -> torch.Tensor:

FILE: boson_multimodal/audio_processing/semantic_module.py
  class Conv1d1x1 (line 9) | class Conv1d1x1(nn.Conv1d):
    method __init__ (line 12) | def __init__(self, in_channels, out_channels, bias=True):
  class Conv1d (line 16) | class Conv1d(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 46) | def forward(self, x):
  class ResidualUnit (line 57) | class ResidualUnit(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 80) | def forward(self, x):
  class ConvTranspose1d (line 86) | class ConvTranspose1d(nn.Module):
    method __init__ (line 87) | def __init__(
    method forward (line 114) | def forward(self, x):
  class EncoderBlock (line 125) | class EncoderBlock(nn.Module):
    method __init__ (line 126) | def __init__(
    method forward (line 143) | def forward(self, x):
  class Encoder (line 150) | class Encoder(nn.Module):
    method __init__ (line 151) | def __init__(
    method forward (line 186) | def forward(self, x):
  class DecoderBlock (line 193) | class DecoderBlock(nn.Module):
    method __init__ (line 196) | def __init__(
    method forward (line 225) | def forward(self, x):
  class Decoder (line 232) | class Decoder(nn.Module):
    method __init__ (line 233) | def __init__(
    method forward (line 277) | def forward(self, z):

FILE: boson_multimodal/data_collator/higgs_audio_collator.py
  function _ceil_to_nearest (line 15) | def _ceil_to_nearest(n, round_to):
  function _ceil_to_next_power_of_two (line 19) | def _ceil_to_next_power_of_two(self, x):
  class HiggsAudioBatchInput (line 24) | class HiggsAudioBatchInput:
  class HiggsAudioSampleCollator (line 47) | class HiggsAudioSampleCollator:
    method __init__ (line 68) | def __init__(
    method _process_and_duplicate_audio_tokens (line 109) | def _process_and_duplicate_audio_tokens(
    method __call__ (line 151) | def __call__(self, batch: List[ChatMLDatasetSample]):

FILE: boson_multimodal/data_types.py
  class AudioContent (line 8) | class AudioContent:
  class TextContent (line 19) | class TextContent:
  class Message (line 25) | class Message:
  class ChatMLSample (line 32) | class ChatMLSample:

FILE: boson_multimodal/dataset/chatml_dataset.py
  class ChatMLDatasetSample (line 24) | class ChatMLDatasetSample:
    method num_audios (line 48) | def num_audios(self):
    method get_audio_codes (line 51) | def get_audio_codes(self, idx):
    method get_audio_codes_labels (line 60) | def get_audio_codes_labels(self, idx):
    method get_wv (line 71) | def get_wv(self, idx):
    method cal_num_tokens (line 80) | def cal_num_tokens(
    method merge (line 129) | def merge(
  class RankedChatMLDatasetSampleTuple (line 277) | class RankedChatMLDatasetSampleTuple:
    method max_score_sample (line 281) | def max_score_sample(self) -> ChatMLDatasetSample:
    method min_score_sample (line 286) | def min_score_sample(self) -> ChatMLDatasetSample:
  class ChatMLDatasetStorageSample (line 293) | class ChatMLDatasetStorageSample:
  function prepare_chatml_sample (line 307) | def prepare_chatml_sample(sample: Union[ChatMLSample, Dict], tokenizer):
  function extract_generation_prompt_from_input_tokens (line 455) | def extract_generation_prompt_from_input_tokens(input_tokens, tokenizer):
  function prepare_chatml_dataframe_single_process (line 493) | def prepare_chatml_dataframe_single_process(df, tokenizer):
  function prepare_chatml_dataframe (line 502) | def prepare_chatml_dataframe(df, tokenizer, num_process=16):
  class DatasetInterface (line 515) | class DatasetInterface(ABC):
    method __getitem__ (line 517) | def __getitem__(self, idx) -> Union["ChatMLDatasetSample", "RankedChat...
  class IterableDatasetInterface (line 522) | class IterableDatasetInterface(ABC):
    method __iter__ (line 524) | def __iter__(self) -> Union["ChatMLDatasetSample", "RankedChatMLDatase...
  class DatasetInfo (line 530) | class DatasetInfo:

FILE: boson_multimodal/model/higgs_audio/audio_head.py
  class HiggsAudioDecoderLayerOutput (line 14) | class HiggsAudioDecoderLayerOutput:
  class HiggsAudioDecoderProjector (line 21) | class HiggsAudioDecoderProjector(HiggsAudioPreTrainedModel):
    method __init__ (line 29) | def __init__(self, config: HiggsAudioConfig, layer_idx: Optional[int] ...
    method forward (line 39) | def forward(

FILE: boson_multimodal/model/higgs_audio/common.py
  class HiggsAudioPreTrainedModel (line 8) | class HiggsAudioPreTrainedModel(PreTrainedModel):
    method _init_weights (line 17) | def _init_weights(self, module):

FILE: boson_multimodal/model/higgs_audio/configuration_higgs_audio.py
  class HiggsAudioEncoderConfig (line 5) | class HiggsAudioEncoderConfig(PretrainedConfig):
    method __init__ (line 10) | def __init__(
  class HiggsAudioConfig (line 47) | class HiggsAudioConfig(PretrainedConfig):
    method __init__ (line 118) | def __init__(

FILE: boson_multimodal/model/higgs_audio/cuda_graph_runner.py
  class CUDAGraphRunner (line 12) | class CUDAGraphRunner(nn.Module):
    method __init__ (line 13) | def __init__(self, model):
    method graph (line 23) | def graph(self):
    method capture (line 27) | def capture(
    method forward (line 106) | def forward(

FILE: boson_multimodal/model/higgs_audio/custom_modules.py
  class PartiallyFrozenEmbedding (line 5) | class PartiallyFrozenEmbedding(nn.Module):
    method __init__ (line 14) | def __init__(self, original_embedding: nn.Embedding, freeze_until_idx:...
    method forward (line 46) | def forward(self, input_ids: torch.Tensor) -> torch.Tensor:
    method to_unsplit (line 81) | def to_unsplit(self) -> nn.Embedding:
  class PartiallyFrozenLinear (line 96) | class PartiallyFrozenLinear(nn.Module):
    method __init__ (line 99) | def __init__(self, original_linear: nn.Linear, freeze_until_idx: int):
    method forward (line 135) | def forward(self, input_tensor):
    method to_unsplit (line 141) | def to_unsplit(self) -> nn.Linear:

FILE: boson_multimodal/model/higgs_audio/modeling_higgs_audio.py
  class GenerationMode (line 45) | class GenerationMode(Enum):
  function _whisper_encoder_zero_shape_forward (line 53) | def _whisper_encoder_zero_shape_forward(whisper_encoder, *args, **kwargs):
  function _prepare_4d_causal_attention_mask_with_cache_position (line 110) | def _prepare_4d_causal_attention_mask_with_cache_position(
  class HiggsAudioFeatureProjector (line 163) | class HiggsAudioFeatureProjector(nn.Module):
    method __init__ (line 166) | def __init__(self, config: HiggsAudioConfig):
    method forward (line 170) | def forward(self, audio_features):
  class HiggsAudioEncoder (line 177) | class HiggsAudioEncoder(HiggsAudioPreTrainedModel):
    method __init__ (line 191) | def __init__(self, config: HiggsAudioEncoderConfig):
    method _freeze_parameters (line 218) | def _freeze_parameters(self):
    method get_input_embeddings (line 223) | def get_input_embeddings(self) -> nn.Module:
    method set_input_embeddings (line 226) | def set_input_embeddings(self, value: nn.Module):
    method forward (line 229) | def forward(
    method _get_feat_extract_output_lengths (line 353) | def _get_feat_extract_output_lengths(self, input_lengths: torch.LongTe...
  class HiggsAudioDualFFNDecoderLayer (line 362) | class HiggsAudioDualFFNDecoderLayer(nn.Module):
    method __init__ (line 397) | def __init__(
    method forward (line 430) | def forward(
  class HiggsAudioModelOutputWithPast (line 732) | class HiggsAudioModelOutputWithPast(ModelOutput):
  class HiggsAudioGenerationOutput (line 752) | class HiggsAudioGenerationOutput(ModelOutput):
  class HiggsAudioModel (line 794) | class HiggsAudioModel(HiggsAudioPreTrainedModel, GenerationMixin):
    method __init__ (line 815) | def __init__(self, config: HiggsAudioConfig):
    method set_num_activation_checkpointing_layers (line 907) | def set_num_activation_checkpointing_layers(self, num_layers):
    method set_delay_pattern (line 910) | def set_delay_pattern(self):
    method set_audio_special_tokens (line 914) | def set_audio_special_tokens(self, tokenizer: AutoTokenizer):
    method _embed_audio_ids (line 918) | def _embed_audio_ids(self, audio_ids):
    method _apply_audio_tower (line 939) | def _apply_audio_tower(self, audio_features, audio_feature_attention_m...
    method _update_causal_mask (line 985) | def _update_causal_mask(
    method _prepare_all_static_kv_cache_masks (line 1051) | def _prepare_all_static_kv_cache_masks(self, hidden_states, attention_...
    method _forward_core (line 1078) | def _forward_core(
    method forward (line 1142) | def forward(
    method _update_model_kwargs_for_generation (line 1420) | def _update_model_kwargs_for_generation(
    method _copy_kv_cache (line 1454) | def _copy_kv_cache(self, from_cache: Cache, to_cache: Cache):
    method _prepare_kv_cache (line 1467) | def _prepare_kv_cache(
    method _sample_audio_tokens (line 1490) | def _sample_audio_tokens(
    method _sample_text_tokens (line 1577) | def _sample_text_tokens(
    method _sample (line 1624) | def _sample(
    method generate (line 1933) | def generate(
    method parameter_count_per_component (line 2025) | def parameter_count_per_component(self):
    method set_skip_audio_tower (line 2126) | def set_skip_audio_tower(self):
    method set_encode_audio_in_tokens (line 2130) | def set_encode_audio_in_tokens(self):
    method freeze_audio_tower (line 2133) | def freeze_audio_tower(self):
    method freeze_audio_encoder_proj (line 2138) | def freeze_audio_encoder_proj(self):
    method freeze_llm (line 2143) | def freeze_llm(self, freeze_embed=True, freeze_embed_until_idx: Option...
    method freeze_text_head (line 2173) | def freeze_text_head(self, freeze_text_head_until_idx: Optional[int] =...
    method merge_weights_from_checkpoint (line 2186) | def merge_weights_from_checkpoint(cls, checkpoint_dir: str, merged_out...
    method capture_model (line 2242) | def capture_model(self, past_key_values: list[Union[Cache, List[torch....

FILE: boson_multimodal/model/higgs_audio/utils.py
  function _ceil_to_nearest (line 15) | def _ceil_to_nearest(n, round_to):
  function count_parameters (line 19) | def count_parameters(model, trainable_only=True):
  function build_delay_pattern_mask (line 26) | def build_delay_pattern_mask(
  function revert_delay_pattern (line 91) | def revert_delay_pattern(data):
  function merge_input_ids_with_audio_features (line 110) | def merge_input_ids_with_audio_features(
  function is_deepspeed_ulysses_enabled (line 436) | def is_deepspeed_ulysses_enabled():
  function support_deepspeed_ulysses (line 444) | def support_deepspeed_ulysses(module):
  function deepspeed_ulysses_attention (line 479) | def deepspeed_ulysses_attention(seq_dim=1, head_dim=2):
  function deepspeed_ulysses_rope (line 510) | def deepspeed_ulysses_rope(state_seq_dim=2, trig_seq_dim=1):
  function _gather_tensors (line 530) | def _gather_tensors(input_, group=None):
  function _scatter_tensors (line 548) | def _scatter_tensors(input_, group=None):
  class _GatherTensors (line 557) | class _GatherTensors(torch.autograd.Function):
    method symbolic (line 561) | def symbolic(graph, input_, group):
    method forward (line 565) | def forward(ctx, input_, group):
    method backward (line 570) | def backward(ctx, grad_output):
  function all_gather_tensors (line 574) | def all_gather_tensors(input_, size=None, dim=0, group=None):
  function get_sequence_data_parallel_world_size (line 591) | def get_sequence_data_parallel_world_size():
  function get_sequence_data_parallel_rank (line 595) | def get_sequence_data_parallel_rank():
  function get_sequence_data_parallel_group (line 599) | def get_sequence_data_parallel_group():
  function _gather_tokens (line 609) | def _gather_tokens(input_, dim=0, group=None):
  function _drop_tokens (line 632) | def _drop_tokens(input_, dim=0, group=None):
  class _DropTokens (line 646) | class _DropTokens(torch.autograd.Function):
    method symbolic (line 650) | def symbolic(graph, input_, dim, group, grad_scale):
    method forward (line 654) | def forward(ctx, input_, dim, group, grad_scale):
    method backward (line 661) | def backward(ctx, grad_output):
  class _GatherTokens (line 668) | class _GatherTokens(torch.autograd.Function):
    method symbolic (line 672) | def symbolic(graph, input_, dim, group, grad_scale):
    method forward (line 676) | def forward(ctx, input_, dim, group, grad_scale):
    method backward (line 683) | def backward(ctx, grad_output):
  function drop_tokens (line 690) | def drop_tokens(input_, dim=0, group=None, grad_scale=1):
  function gather_tokens (line 697) | def gather_tokens(input_, dim=0, group=None, grad_scale=1):
  function sequence_chunking_per_rank (line 704) | def sequence_chunking_per_rank(sp_size, sp_rank, *args, dim=1):
  function disable_deepspeed_ulysses (line 740) | def disable_deepspeed_ulysses():

FILE: boson_multimodal/serve/serve_engine.py
  class HiggsAudioStreamerDelta (line 27) | class HiggsAudioStreamerDelta:
  class AsyncHiggsAudioStreamer (line 36) | class AsyncHiggsAudioStreamer(BaseStreamer):
    method __init__ (line 76) | def __init__(
    method put (line 100) | def put(self, value: torch.Tensor):
    method end (line 128) | def end(self):
    method __aiter__ (line 134) | def __aiter__(self):
    method __anext__ (line 137) | async def __anext__(self):
  class AsyncStoppingCriteria (line 153) | class AsyncStoppingCriteria(StoppingCriteria):
    method __init__ (line 161) | def __init__(self, stop_signal: threading.Event):
    method __call__ (line 164) | def __call__(self, input_ids, scores, **kwargs) -> bool:
  class HiggsAudioResponse (line 172) | class HiggsAudioResponse:
  class HiggsAudioServeEngine (line 181) | class HiggsAudioServeEngine:
    method __init__ (line 182) | def __init__(
    method _prepare_inputs (line 280) | def _prepare_inputs(self, chat_ml_sample: ChatMLSample, force_audio_ge...
    method _prepare_kv_caches (line 337) | def _prepare_kv_caches(self):
    method generate (line 341) | def generate(
    method generate_delta_stream (line 428) | async def generate_delta_stream(

FILE: boson_multimodal/serve/utils.py
  function random_uuid (line 15) | def random_uuid() -> str:
  function async_generator_wrap (line 19) | async def async_generator_wrap(first_element, gen: AsyncGenerator):
  function encode_base64_content_from_file (line 27) | def encode_base64_content_from_file(file_path: str) -> str:
  function pcm16_to_target_format (line 35) | def pcm16_to_target_format(
  function contains_chinese (line 63) | def contains_chinese(text: str):
  function replace_blank (line 68) | def replace_blank(text: str):
  function replace_corner_mark (line 79) | def replace_corner_mark(text: str):
  function remove_bracket (line 86) | def remove_bracket(text: str):
  function split_paragraph (line 98) | def split_paragraph(text: str, tokenize, lang="zh", token_max_n=80, toke...
  function is_only_punctuation (line 153) | def is_only_punctuation(text: str):
  function spell_out_number (line 160) | def spell_out_number(text: str, inflect_parser):
  function remove_emoji (line 179) | def remove_emoji(text: str):
  function remove_repeated_punctuations (line 197) | def remove_repeated_punctuations(text, punctuations):
  function full_to_half_width (line 204) | def full_to_half_width(text: str) -> str:
  function split_interleaved_delayed_audios (line 212) | def split_interleaved_delayed_audios(

FILE: examples/generation.py
  function normalize_chinese_punctuation (line 44) | def normalize_chinese_punctuation(text):
  function prepare_chunk_text (line 83) | def prepare_chunk_text(
  function _build_system_message_with_audio_prompt (line 160) | def _build_system_message_with_audio_prompt(system_message):
  class HiggsAudioModelClient (line 178) | class HiggsAudioModelClient:
    method __init__ (line 179) | def __init__(
    method _init_static_kv_cache (line 242) | def _init_static_kv_cache(self):
    method _prepare_kv_caches (line 263) | def _prepare_kv_caches(self):
    method generate (line 268) | def generate(
  function prepare_generation_context (line 387) | def prepare_generation_context(scene_prompt, ref_audio, ref_audio_in_sys...
  function main (line 625) | def main(

FILE: examples/serve_engine/input_samples.py
  function encode_base64_content_from_file (line 6) | def encode_base64_content_from_file(file_path: str) -> str:
  function get_interleaved_dialogue_input_sample (line 14) | def get_interleaved_dialogue_input_sample():
  function get_zero_shot_input_sample (line 38) | def get_zero_shot_input_sample():
  function get_voice_clone_input_sample (line 59) | def get_voice_clone_input_sample():

FILE: examples/serve_engine/run_hf_example.py
  function main (line 18) | def main(example: str):

FILE: examples/vllm/run_chat_completion.py
  function encode_base64_content_from_file (line 26) | def encode_base64_content_from_file(file_path: str) -> str:
  function run_smart_voice (line 34) | def run_smart_voice() -> None:
  function run_voice_clone (line 63) | def run_voice_clone(stream: bool = False) -> None:
  function run_generate_multispeaker (line 131) | def run_generate_multispeaker(stream: bool = False) -> None:
  function main (line 184) | def main(args) -> None: