SYMBOL INDEX (150 symbols across 18 files)

FILE: dataset/data_item.py
  class DataItem (line 8) | class DataItem:
    method __init__ (line 10) | def __init__(self,
    method load_audio (line 49) | def load_audio(self, audio_path: str):
    method truncate (line 55) | def truncate(self, audio_array: np.ndarray, sr: int,
    method offset_id (line 65) | def offset_id(self, offset: int):
    method scale_and_offset (line 70) | def scale_and_offset(self,
    method to_dict (line 76) | def to_dict(self, ) -> Any:
    method get_dict (line 91) | def get_dict(self, ):

FILE: dataset/dataset.py
  class AudioFaceDataset (line 13) | class AudioFaceDataset(data.Dataset):
    method __init__ (line 15) | def __init__(self, data_label_path: str, args: dict = None) -> None:
    method __len__ (line 44) | def __len__(self, ):
    method __getitem__ (line 47) | def __getitem__(self, index: Any) -> Any:
    method get_identity_num (line 51) | def get_identity_num(self, ):
  class MixAudioFaceDataset (line 55) | class MixAudioFaceDataset(AudioFaceDataset):
    method __init__ (line 57) | def __init__(self,
  function get_dataset_list (line 80) | def get_dataset_list(args):
  function get_single_dataset (line 104) | def get_single_dataset(args, json_path: str = ''):
  function get_dataloaders (line 123) | def get_dataloaders(args):

FILE: loss/loss.py
  class FlameParams (line 11) | class FlameParams:
  class FlameLayer (line 18) | class FlameLayer(nn.Module):
    method __init__ (line 20) | def __init__(self, model_path: str) -> None:
    method flame_params_from_3dmm (line 76) | def flame_params_from_3dmm(self,
    method forward (line 97) | def forward(self, tensor_3dmm: torch.Tensor):
  class FlameParamLossForDADHead (line 126) | class FlameParamLossForDADHead(nn.Module):
    method __init__ (line 128) | def __init__(self, mouth_indices_path: str, loss_mask_path: str,
    method forward (line 138) | def forward(self, x: torch.Tensor, target: torch.Tensor):
    method get_vertices (line 147) | def get_vertices(
    method mouth_metric (line 154) | def mouth_metric(self, x: torch.Tensor, target: torch.Tensor):
  class VerticesLoss (line 165) | class VerticesLoss(nn.Module):
    method __init__ (line 167) | def __init__(self, mouth_indices_path: str) -> None:
    method forward (line 173) | def forward(self, x: torch.Tensor, target: torch.Tensor):
    method get_vertices (line 176) | def get_vertices(
    method mouth_metric (line 182) | def mouth_metric(self, x: torch.Tensor, target: torch.Tensor):
  class BlendShapeLoss (line 193) | class BlendShapeLoss(nn.Module):
    method __init__ (line 195) | def __init__(self,
    method forward (line 215) | def forward(self, x: torch.Tensor, target: torch.Tensor):
    method bs2vertices (line 219) | def bs2vertices(self, x: torch.Tensor):
    method get_vertices (line 224) | def get_vertices(
    method mouth_metric (line 231) | def mouth_metric(self, x: torch.Tensor, target: torch.Tensor):
  class ParamLoss (line 244) | class ParamLoss(nn.Module):
    method __init__ (line 246) | def __init__(self, weight: float):
    method forward (line 252) | def forward(self, x: torch.Tensor, target: torch.Tensor):
    method mouth_metric (line 255) | def mouth_metric(self, x: torch.Tensor, target: torch.Tensor):
    method get_vertices (line 258) | def get_vertices(
  class UniTalkerLoss (line 265) | class UniTalkerLoss(nn.Module):
    method __init__ (line 267) | def __init__(self, args) -> None:
    method forward (line 344) | def forward(
    method pca_loss (line 352) | def pca_loss(self, x: torch.Tensor, target: torch.Tensor):
    method mouth_metric (line 355) | def mouth_metric(self, x: torch.Tensor, target: torch.Tensor,
    method get_vertices (line 359) | def get_vertices(self, x: torch.Tensor, annot_type: str):

FILE: main/demo.py
  function get_all_audios (line 14) | def get_all_audios(audio_root:str):
  function split_long_audio (line 26) | def split_long_audio(
  function merge_out_list (line 47) | def merge_out_list(out_list: list, fps:int):
  function main (line 69) | def main():

FILE: main/render.py
  function render_meshes (line 23) | def render_meshes(mesh_vertices: torch.Tensor,
  function read_obj (line 131) | def read_obj(in_path):
  function pad_for_libx264 (line 161) | def pad_for_libx264(image_array):
  function array_to_video (line 209) | def array_to_video(
  function get_obj_faces (line 287) | def get_obj_faces(annot_type: str):
  function vis_model_out_proxy (line 303) | def vis_model_out_proxy():

FILE: main/train.py
  function main (line 21) | def main():

FILE: main/train_eval_loop.py
  function train_epoch (line 8) | def train_epoch(data_loader, model, loss_module, optimizer, epoch, args):
  function validate_epoch (line 53) | def validate_epoch(data_loader, model, loss_module, epoch, phase, args):

FILE: main/train_pca.py
  function main (line 8) | def main():
  function main_worker (line 15) | def main_worker(cfg):

FILE: models/base_model.py
  class BaseModel (line 5) | class BaseModel(nn.Module):
    method __init__ (line 8) | def __init__(self):
    method forward (line 12) | def forward(self, *x):
    method freeze_model (line 19) | def freeze_model(self, do_freeze: bool = True):
    method summary (line 23) | def summary(self, logger, writer=None):

FILE: models/hubert.py
  function _compute_mask_indices (line 12) | def _compute_mask_indices(
  class HubertModel (line 61) | class HubertModel(HubertModel):
    method __init__ (line 63) | def __init__(self, config):
    method _freeze_parameters (line 66) | def _freeze_parameters(self, do_freeze: bool = True):
    method forward (line 70) | def forward(

FILE: models/model_utils.py
  function linear_interpolation (line 9) | def linear_interpolation(features, output_len: int):
  function init_biased_mask (line 17) | def init_biased_mask(n_head, max_seq_len, period):
  function enc_dec_mask (line 53) | def enc_dec_mask(device, T, S):
  class PeriodicPositionalEncoding (line 61) | class PeriodicPositionalEncoding(nn.Module):
    method __init__ (line 63) | def __init__(self, d_model, dropout=0.1, period=25, max_seq_len=3000):
    method forward (line 78) | def forward(self, x):
  class TCN (line 83) | class TCN(nn.Module):
    method __init__ (line 85) | def __init__(self, in_dim, out_dim):
    method forward (line 91) | def forward(self, spectrogram, style_embed, time_steps=None):
  class SeqTranslator1D (line 106) | class SeqTranslator1D(nn.Module):
    method __init__ (line 109) | def __init__(self,
    method forward (line 144) | def forward(self, x):
  class ConvNormRelu (line 148) | class ConvNormRelu(nn.Module):
    method __init__ (line 155) | def __init__(self,
    method forward (line 264) | def forward(self, x, **kwargs):

FILE: models/pca.py
  class PCALayer (line 6) | class PCALayer(nn.Module):
    method __init__ (line 8) | def __init__(self, pca_info_path: str):
    method encode (line 23) | def encode(
    method decode (line 32) | def decode(self, feat: torch.Tensor, pca_dim: int = None):
  class PCA (line 38) | class PCA:
    method __init__ (line 40) | def __init__(self, trunc_dim: int = None):
    method buld_pca_for_dataset (line 43) | def buld_pca_for_dataset(self, dataset, trunc_dim: int = 1024):
    method load_dataset (line 47) | def load_dataset(self, dataset):
    method build_incremental_PCA (line 56) | def build_incremental_PCA(
    method build_pca (line 94) | def build_pca(

FILE: models/unitalker.py
  class OutHead (line 9) | class OutHead(BaseModel):
    method __init__ (line 11) | def __init__(self, args, out_dim: int):
    method forward (line 22) | def forward(self, x):
  class UniTalker (line 26) | class UniTalker(BaseModel):
    method __init__ (line 28) | def __init__(self, args):
    method forward (line 87) | def forward(self,

FILE: models/unitalker_decoder.py
  class UniTalkerDecoderTCN (line 14) | class UniTalkerDecoderTCN(BaseModel):
    method __init__ (line 16) | def __init__(self, args) -> None:
    method forward (line 25) | def forward(self,
  class UniTalkerDecoderTransformer (line 43) | class UniTalkerDecoderTransformer(BaseModel):
    method __init__ (line 45) | def __init__(self, args) -> None:
    method forward (line 63) | def forward(self, hidden_states: torch.Tensor, style_idx: torch.Tensor,

FILE: models/wav2vec2.py
  function _compute_mask_indices (line 12) | def _compute_mask_indices(
  class Wav2Vec2Model (line 61) | class Wav2Vec2Model(Wav2Vec2Model):
    method __init__ (line 63) | def __init__(self, config):
    method _freeze_wav2vec2_parameters (line 66) | def _freeze_wav2vec2_parameters(self, do_freeze: bool = True):
    method forward (line 70) | def forward(

FILE: models/wavlm.py
  class WavLMModel (line 16) | class WavLMModel(WavLMModel):
    method __init__ (line 17) | def __init__(self, config):
    method _freeze_wav2vec2_parameters (line 20) | def _freeze_wav2vec2_parameters(self, do_freeze: bool = True):
    method forward (line 24) | def forward(

FILE: utils/config.py
  class CfgNode (line 10) | class CfgNode(dict):
    method __init__ (line 17) | def __init__(self, init_dict=None, key_list=None, new_allowed=False):
    method __getattr__ (line 27) | def __getattr__(self, name):
    method __setattr__ (line 33) | def __setattr__(self, name, value):
    method __str__ (line 36) | def __str__(self):
    method __repr__ (line 58) | def __repr__(self):
  function load_cfg_from_cfg_file (line 63) | def load_cfg_from_cfg_file(file):
  function merge_cfg_from_list (line 79) | def merge_cfg_from_list(cfg, cfg_list):
  function _decode_cfg_value (line 93) | def _decode_cfg_value(v):
  function _check_and_coerce_cfg_value_type (line 121) | def _check_and_coerce_cfg_value_type(replacement, original, key, full_key):

FILE: utils/utils.py
  function get_audio_encoder_dim (line 12) | def get_audio_encoder_dim(audio_encoder: str):
  function filer_list (line 20) | def filer_list(in_list: list, key: str):
  function count_checkpoint_params (line 28) | def count_checkpoint_params(ckpt: dict):
  function read_obj (line 39) | def read_obj(in_path):
  function get_logger (line 73) | def get_logger(log_file: str):
  function get_template_dict (line 86) | def get_template_dict(data_root, annot_type: str):
  function filter_unitalker_state_dict (line 97) | def filter_unitalker_state_dict(in_dict):
  function get_template_verts (line 104) | def get_template_verts(data_root, dataset_name: str, subject: int):
  function load_ckpt (line 110) | def load_ckpt(model, ckpt_path, re_init_decoder_and_head: bool = False):
  class AverageMeter (line 129) | class AverageMeter(object):
    method __init__ (line 132) | def __init__(self):
    method reset (line 135) | def reset(self):
    method update (line 141) | def update(self, val, n=1):
    method get_avg (line 147) | def get_avg(self, ):
  function get_average_meter_dict (line 151) | def get_average_meter_dict(args, phase):
  function log_datasetloss (line 170) | def log_datasetloss(
  function write_to_tensorboard (line 187) | def write_to_tensorboard(writer,
  function get_parser (line 201) | def get_parser():
  function seed_everything (line 226) | def seed_everything(seed: int = 42):