SYMBOL INDEX (50 symbols across 6 files)

FILE: AutomaticPipeline/AgePreTrainModel.py
  class ModelHead (line 10) | class ModelHead(nn.Module):
    method __init__ (line 13) | def __init__(self, config, num_labels):
    method forward (line 21) | def forward(self, features, **kwargs):
  class AgeGenderModel (line 32) | class AgeGenderModel(Wav2Vec2PreTrainedModel):
    method __init__ (line 35) | def __init__(self, config):
    method forward (line 44) | def forward(

FILE: AutomaticPipeline/AutoPipeline.py
  function to_device (line 30) | def to_device(tensors, device):
  class CustomDataset (line 39) | class CustomDataset(torch.utils.data.Dataset):
    method __init__ (line 40) | def __init__(
    method __preprocess__ (line 58) | def __preprocess__(self):
    method __len__ (line 70) | def __len__(self):
    method _cutorpad (line 76) | def _cutorpad(self, audio: np.ndarray) -> np.ndarray:
    method __getitem__ (line 94) | def __getitem__(self, index) -> torch.Tensor:
  class CollateFunc (line 117) | class CollateFunc:
    method __init__ (line 118) | def __init__(
    method __call__ (line 132) | def __call__(self, batch: List):
  function age_predict (line 157) | def age_predict(batch, model, device):
  function gender_predict (line 165) | def gender_predict(batch, model, device):
  function emotion_predict (line 176) | def emotion_predict(audiopaths, model):
  function pitch_energy_calculate (line 184) | def pitch_energy_calculate(input_values):
  function inference_on_device (line 195) | def inference_on_device(device, i, num_devices, language, basedir, scp_p...
  function main (line 289) | def main(args):

FILE: AutomaticPipeline/Clustering.py
  function assign_pitch_group (line 6) | def assign_pitch_group(row, language, male_percentiles, female_percentil...
  function replace_age_with_text (line 22) | def replace_age_with_text(row, language):
  function main (line 36) | def main(args):

FILE: AutomaticPipeline/PitchEnergy.py
  function extract_pitch (line 4) | def extract_pitch(wav, sr):
  function calculate_mean_pitch (line 8) | def calculate_mean_pitch(pitches):
  function process_audio (line 11) | def process_audio(audio, sr):

FILE: AutomaticPipeline/models/SECap/model2.py
  class KeywordsStoppingCriteria (line 20) | class KeywordsStoppingCriteria(StoppingCriteria):
    method __init__ (line 21) | def __init__(self, keywords_ids:list):
    method __call__ (line 24) | def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTen...
  class MotionAudio (line 29) | class MotionAudio(pl.LightningModule):
    method __init__ (line 30) | def __init__(
    method init_Qformer (line 76) | def init_Qformer(self,num_query_token, vision_width, cross_attention_f...
    method mean_pooling (line 94) | def mean_pooling(self,model_output, attention_mask):
    method forward (line 102) | def forward(self, audio, describtion):
    method training_step (line 170) | def training_step(self, batch, batch_idx):
    method validation_step (line 175) | def validation_step(self, batch, batch_idx):
    method configure_optimizers (line 180) | def configure_optimizers(self):
    method inference (line 183) | def inference(self, audio_feature):
    method post_processing (line 242) | def post_processing(self, sentences,device):
    method test_step (line 254) | def test_step(self, batch, batch_idx):
  function count_parameters (line 272) | def count_parameters(model):

FILE: llama-ft/llama_infer.py
  class Dataset (line 43) | class Dataset(torch.utils.data.Dataset):
    method __init__ (line 44) | def __init__(self, args):
    method __len__ (line 51) | def __len__(self):
    method __getitem__ (line 54) | def __getitem__(self, index):
  function extract (line 71) | def extract(input_text, language):
  function inference_on_device (line 87) | def inference_on_device(args, tokenizer, device, dataloader):
  function main (line 151) | def main(args):