SYMBOL INDEX (115 symbols across 9 files)

FILE: api.py
  class Language (line 18) | class Language(str, Enum):
  function root (line 38) | async def root():
  function turn_audio_to_text (line 54) | async def turn_audio_to_text(

FILE: export_meta.py
  function export_rebuild_model (line 11) | def export_rebuild_model(model, **kwargs):
  function export_forward (line 22) | def export_forward(
  function export_dummy_inputs (line 53) | def export_dummy_inputs(self):
  function export_input_names (line 60) | def export_input_names(self):
  function export_output_names (line 63) | def export_output_names(self):
  function export_dynamic_axes (line 66) | def export_dynamic_axes(self):
  function export_name (line 76) | def export_name(self):

FILE: model.py
  class SinusoidalPositionEncoder (line 18) | class SinusoidalPositionEncoder(torch.nn.Module):
    method __int__ (line 21) | def __int__(self, d_model=80, dropout_rate=0.1):
    method encode (line 24) | def encode(
    method forward (line 43) | def forward(self, x):
  class PositionwiseFeedForward (line 51) | class PositionwiseFeedForward(torch.nn.Module):
    method __init__ (line 61) | def __init__(self, idim, hidden_units, dropout_rate, activation=torch....
    method forward (line 69) | def forward(self, x):
  class MultiHeadedAttentionSANM (line 74) | class MultiHeadedAttentionSANM(nn.Module):
    method __init__ (line 84) | def __init__(
    method forward_fsmn (line 122) | def forward_fsmn(self, inputs, mask, mask_shfit_chunk=None):
    method forward_qkv (line 140) | def forward_qkv(self, x):
    method forward_attention (line 169) | def forward_attention(self, value, scores, mask, mask_att_chunk_encode...
    method forward (line 207) | def forward(self, x, mask, mask_shfit_chunk=None, mask_att_chunk_encod...
    method forward_chunk (line 228) | def forward_chunk(self, x, cache=None, chunk_size=None, look_back=0):
  class LayerNorm (line 268) | class LayerNorm(nn.LayerNorm):
    method __init__ (line 269) | def __init__(self, *args, **kwargs):
    method forward (line 272) | def forward(self, input):
  function sequence_mask (line 283) | def sequence_mask(lengths, maxlen=None, dtype=torch.float32, device=None):
  class EncoderLayerSANM (line 294) | class EncoderLayerSANM(nn.Module):
    method __init__ (line 295) | def __init__(
    method forward (line 322) | def forward(self, x, mask, cache=None, mask_shfit_chunk=None, mask_att...
    method forward_chunk (line 400) | def forward_chunk(self, x, cache=None, chunk_size=None, look_back=0):
  class SenseVoiceEncoderSmall (line 438) | class SenseVoiceEncoderSmall(nn.Module):
    method __init__ (line 445) | def __init__(
    method output_size (line 543) | def output_size(self) -> int:
    method forward (line 546) | def forward(
  class SenseVoiceSmall (line 581) | class SenseVoiceSmall(nn.Module):
    method __init__ (line 584) | def __init__(
    method from_pretrained (line 649) | def from_pretrained(model:str=None, **kwargs):
    method forward (line 655) | def forward(
    method encode (line 707) | def encode(
    method _calc_ctc_loss (line 747) | def _calc_ctc_loss(
    method _calc_rich_ce_loss (line 764) | def _calc_rich_ce_loss(
    method inference (line 781) | def inference(
    method export (line 924) | def export(self, **kwargs):

FILE: utils/ctc_alignment.py
  function ctc_forced_align (line 3) | def ctc_forced_align(

FILE: utils/export_utils.py
  function export (line 5) | def export(
  function _onnx (line 29) | def _onnx(

FILE: utils/frontend.py
  class WavFrontend (line 14) | class WavFrontend:
    method __init__ (line 17) | def __init__(
    method fbank (line 53) | def fbank(self, waveform: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
    method fbank_online (line 65) | def fbank_online(self, waveform: np.ndarray) -> Tuple[np.ndarray, np.n...
    method reset_status (line 78) | def reset_status(self):
    method lfr_cmvn (line 82) | def lfr_cmvn(self, feat: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
    method apply_lfr (line 93) | def apply_lfr(inputs: np.ndarray, lfr_m: int, lfr_n: int) -> np.ndarray:
    method apply_cmvn (line 115) | def apply_cmvn(self, inputs: np.ndarray) -> np.ndarray:
    method load_cmvn (line 125) | def load_cmvn(
  class WavFrontendOnline (line 154) | class WavFrontendOnline(WavFrontend):
    method __init__ (line 155) | def __init__(self, **kwargs):
    method apply_lfr (line 172) | def apply_lfr(
    method compute_frame_num (line 205) | def compute_frame_num(
    method fbank (line 211) | def fbank(
    method get_fbank (line 262) | def get_fbank(self) -> Tuple[np.ndarray, np.ndarray]:
    method lfr_cmvn (line 265) | def lfr_cmvn(
    method extract_fbank (line 291) | def extract_fbank(
    method get_waveforms (line 362) | def get_waveforms(self):
    method cache_reset (line 365) | def cache_reset(self):
  function load_bytes (line 372) | def load_bytes(input):
  class SinusoidalPositionEncoderOnline (line 388) | class SinusoidalPositionEncoderOnline:
    method encode (line 391) | def encode(self, positions: np.ndarray = None, depth: int = None, dtyp...
    method forward (line 401) | def forward(self, x, start_idx=0):
  function test (line 409) | def test():

FILE: utils/infer_utils.py
  function pad_list (line 30) | def pad_list(xs, pad_value, max_len=None):
  class TokenIDConverter (line 79) | class TokenIDConverter:
    method __init__ (line 80) | def __init__(
    method get_num_vocabulary_size (line 90) | def get_num_vocabulary_size(self) -> int:
    method ids2tokens (line 93) | def ids2tokens(self, integers: Union[np.ndarray, Iterable[int]]) -> Li...
    method tokens2ids (line 98) | def tokens2ids(self, tokens: Iterable[str]) -> List[int]:
  class CharTokenizer (line 103) | class CharTokenizer:
    method __init__ (line 104) | def __init__(
    method load_symbols (line 116) | def load_symbols(value: Union[Path, str, Iterable[str]] = None) -> Set:
    method text2tokens (line 131) | def text2tokens(self, line: Union[str, list]) -> List[str]:
    method tokens2text (line 148) | def tokens2text(self, tokens: Iterable[str]) -> str:
    method __repr__ (line 152) | def __repr__(self):
  class Hypothesis (line 161) | class Hypothesis(NamedTuple):
    method asdict (line 169) | def asdict(self) -> dict:
  class TokenIDConverterError (line 178) | class TokenIDConverterError(Exception):
  class ONNXRuntimeError (line 182) | class ONNXRuntimeError(Exception):
  class OrtInferSession (line 186) | class OrtInferSession:
    method __init__ (line 187) | def __init__(self, model_file, device_id=-1, intra_op_num_threads=4):
    method __call__ (line 224) | def __call__(self, input_content: List[Union[np.ndarray, np.ndarray]])...
    method get_input_names (line 231) | def get_input_names(
    method get_output_names (line 236) | def get_output_names(
    method get_character_list (line 241) | def get_character_list(self, key: str = "character"):
    method have_key (line 244) | def have_key(self, key: str = "character") -> bool:
    method _verify_model (line 251) | def _verify_model(model_path):
  function split_to_mini_sentence (line 259) | def split_to_mini_sentence(words: list, word_limit: int = 20):
  function code_mix_split_words (line 273) | def code_mix_split_words(text: str):
  function isEnglish (line 294) | def isEnglish(text: str):
  function join_chinese_and_english (line 301) | def join_chinese_and_english(input_list):
  function code_mix_split_words_jieba (line 313) | def code_mix_split_words_jieba(seg_dict_file: str):
  function read_yaml (line 356) | def read_yaml(yaml_path: Union[str, Path]) -> Dict:
  function get_logger (line 366) | def get_logger(name="funasr_onnx"):

FILE: utils/model_bin.py
  class SenseVoiceSmallONNX (line 28) | class SenseVoiceSmallONNX:
    method __init__ (line 35) | def __init__(
    method __call__ (line 68) | def __call__(self,
    method load_data (line 101) | def load_data(self, wav_content: Union[str, np.ndarray, List[str]], fs...
    method extract_feat (line 117) | def extract_feat(self, waveform_list: List[np.ndarray]) -> Tuple[np.nd...
    method pad_feats (line 130) | def pad_feats(feats: List[np.ndarray], max_feat_len: int) -> np.ndarray:
    method infer (line 139) | def infer(self,

FILE: webui.py
  function format_str (line 91) | def format_str(s):
  function format_str_v2 (line 97) | def format_str_v2(s):
  function format_str_v3 (line 116) | def format_str_v3(s):
  function model_inference (line 141) | def model_inference(input_wav, language, fs=16000):
  function launch (line 220) | def launch():