SYMBOL INDEX (157 symbols across 26 files)

FILE: alm/callback/progress.py
  class ProgressLogger (line 10) | class ProgressLogger(Callback):
    method __init__ (line 12) | def __init__(self, metric_monitor: dict, precision: int = 3):
    method on_train_start (line 17) | def on_train_start(self, trainer: Trainer, pl_module: LightningModule,
    method on_train_end (line 21) | def on_train_end(self, trainer: Trainer, pl_module: LightningModule,
    method on_validation_epoch_end (line 25) | def on_validation_epoch_end(self, trainer: Trainer,
    method on_train_epoch_end (line 30) | def on_train_epoch_end(self,

FILE: alm/config.py
  function get_module_config (line 7) | def get_module_config(cfg_model, path="modules"):
  function get_obj_from_str (line 16) | def get_obj_from_str(string, reload=False):
  function instantiate_from_config (line 24) | def instantiate_from_config(config):
  function parse_args (line 34) | def parse_args(phase="train"):

FILE: alm/data/BIWI/dataset.py
  class BIWIDataset (line 13) | class BIWIDataset(data.Dataset):
    method __init__ (line 15) | def __init__(self,
    method __len__ (line 29) | def __len__(self):
    method __getitem__ (line 32) | def __getitem__(self, index):

FILE: alm/data/base.py
  class BASEDataModule (line 7) | class BASEDataModule(pl.LightningDataModule):
    method __init__ (line 9) | def __init__(self, collate_fn, batch_size: int, num_workers: int):
    method __getattr__ (line 32) | def __getattr__(self, item):
    method setup (line 53) | def setup(self, stage=None):
    method train_dataloader (line 62) | def train_dataloader(self):
    method predict_dataloader (line 70) | def predict_dataloader(self):
    method val_dataloader (line 82) | def val_dataloader(self):
    method test_dataloader (line 94) | def test_dataloader(self):

FILE: alm/data/biwi.py
  function load_data (line 15) | def load_data(args):
  class BIWIDataModule (line 36) | class BIWIDataModule(BASEDataModule):
    method __init__ (line 37) | def __init__(self,
    method __getattr__ (line 175) | def __getattr__(self, item):

FILE: alm/data/get_data.py
  function collate_tensors (line 4) | def collate_tensors(batch):
  function vocaset_collate_fn (line 16) | def vocaset_collate_fn(batch):
  function voxcelebinsta_collate_fn (line 31) | def voxcelebinsta_collate_fn(batch):
  function voxcelebinstacoeflmdb_collate_fn (line 60) | def voxcelebinstacoeflmdb_collate_fn(batch):
  function get_datasets (line 94) | def get_datasets(cfg, logger, phase='train'):

FILE: alm/data/voca/dataset.py
  class VOCASETDataset (line 13) | class VOCASETDataset(data.Dataset):
    method __init__ (line 15) | def __init__(self,
    method __getitem__ (line 27) | def __getitem__(self, index):
    method __len__ (line 57) | def __len__(self):

FILE: alm/data/vocaset.py
  function load_data (line 15) | def load_data(args):
  class VOCASETDataModule (line 36) | class VOCASETDataModule(BASEDataModule):
    method __init__ (line 37) | def __init__(self,
    method __getattr__ (line 155) | def __getattr__(self, item):

FILE: alm/models/architectures/adpt_bias_denoiser.py
  class Adpt_Bias_Denoiser (line 13) | class Adpt_Bias_Denoiser(nn.Module):
    method __init__ (line 15) | def __init__(self,
    method forward (line 104) | def forward(self,

FILE: alm/models/architectures/tools/embeddings.py
  function get_activation (line 8) | def get_activation(activation_type):
  class MaskedNorm (line 37) | class MaskedNorm(nn.Module):
    method __init__ (line 43) | def __init__(self, norm_type, num_groups, num_features):
    method forward (line 57) | def forward(self, x: Tensor, mask: Tensor):
  class Embeddings (line 76) | class Embeddings(nn.Module):
    method __init__ (line 83) | def __init__(
    method forward (line 133) | def forward(self, x: Tensor, mask: Tensor = None) -> Tensor:
    method __repr__ (line 155) | def __repr__(self):
  class SpatialEmbeddings (line 163) | class SpatialEmbeddings(nn.Module):
    method __init__ (line 171) | def __init__(
    method forward (line 218) | def forward(self, x: Tensor, mask: Tensor) -> Tensor:
    method __repr__ (line 238) | def __repr__(self):
  function get_timestep_embedding (line 245) | def get_timestep_embedding(
  class TimestepEmbedding (line 288) | class TimestepEmbedding(nn.Module):
    method __init__ (line 289) | def __init__(self, channel: int, time_embed_dim: int, act_fn: str = "s...
    method forward (line 298) | def forward(self, sample):
  class Timesteps (line 308) | class Timesteps(nn.Module):
    method __init__ (line 309) | def __init__(self, num_channels: int, flip_sin_to_cos: bool, downscale...
    method forward (line 315) | def forward(self, timesteps):

FILE: alm/models/architectures/tools/transformer_adpt.py
  class Transformer_Adpt (line 13) | class Transformer_Adpt(nn.Module):
    method __init__ (line 15) | def __init__(self,
    method obj_vector (line 85) | def obj_vector(self, id):
    method _forward (line 91) | def _forward(self,
  class TransformerDecoder_w_Adapter (line 131) | class TransformerDecoder_w_Adapter(nn.TransformerDecoder):
    method __init__ (line 141) | def __init__(self, decoder_layer, num_layers, norm=None):
    method forward (line 147) | def forward(self,
  class TransformerDecoderLayer_w_Adapter (line 184) | class TransformerDecoderLayer_w_Adapter(nn.TransformerDecoderLayer):
    method __init__ (line 201) | def __init__(self,
    method forward (line 217) | def forward(self,
    method _sa_block (line 252) | def _sa_block(self, x: Tensor,
    method _mha_block (line 289) | def _mha_block(self, x: Tensor, mem: Tensor,
    method _concate_adapter (line 326) | def _concate_adapter(self, adapter: Tensor, x: Tensor, batch_first: bo...

FILE: alm/models/architectures/tools/utils.py
  class PeriodicPositionalEncoding (line 5) | class PeriodicPositionalEncoding(nn.Module):
    method __init__ (line 6) | def __init__(self, d_model, dropout=0.1, period=25, max_seq_len=600):
    method forward (line 19) | def forward(self, x):
  function init_biased_mask (line 95) | def init_biased_mask(n_head, max_seq_len, period):
  function init_bi_biased_mask (line 133) | def init_bi_biased_mask(max_seq_len, ):
  function init_mem_mask_faceformer (line 147) | def init_mem_mask_faceformer(max_seq_len):
  function init_bi_biased_mask_faceformer (line 153) | def init_bi_biased_mask_faceformer(n_head, max_seq_len, period):

FILE: alm/models/get_model.py
  function get_model (line 3) | def get_model(cfg, datamodule):
  function get_module (line 11) | def get_module(cfg, datamodule):

FILE: alm/models/losses/utils.py
  class MaskedConsistency (line 4) | class MaskedConsistency:
    method __init__ (line 5) | def __init__(self) -> None:
    method __call__ (line 8) | def __call__(self, pred, gt, mask):
    method __repr__ (line 11) | def __repr__(self):
  class MaskedVelocityConsistency (line 14) | class MaskedVelocityConsistency:
    method __init__ (line 15) | def __init__(self) -> None:
    method __call__ (line 18) | def __call__(self, pred, gt, mask):
    method velocity (line 23) | def velocity(self, term):
    method __repr__ (line 27) | def __repr__(self):
  function vocaset_upper_face_variance (line 164) | def vocaset_upper_face_variance(motion, ):
  function vocaset_mouth_distance (line 172) | def vocaset_mouth_distance(vertices_gt, vertices_pred):
  function biwi_upper_face_variance (line 179) | def biwi_upper_face_variance(motion, ):
  function biwi_mouth_distance (line 187) | def biwi_mouth_distance(vertices_gt, vertices_pred):

FILE: alm/models/losses/voca.py
  class VOCALosses (line 32) | class VOCALosses(Metric):
    method __init__ (line 37) | def __init__(self, cfg, split):
    method update (line 121) | def update(self, rs_set):
    method compute (line 151) | def compute(self, split):
    method _update_loss (line 156) | def _update_loss(self, loss: str, outputs, inputs, mask = None):
    method loss2logname (line 167) | def loss2logname(self, loss: str, split: str):
  class MaskedConsistency (line 175) | class MaskedConsistency:
    method __init__ (line 176) | def __init__(self) -> None:
    method __call__ (line 179) | def __call__(self, pred, gt, mask):
    method __repr__ (line 186) | def __repr__(self):
  class MaskedVelocityConsistency (line 189) | class MaskedVelocityConsistency:
    method __init__ (line 190) | def __init__(self) -> None:
    method __call__ (line 193) | def __call__(self, pred, gt, mask):
    method velocity (line 198) | def velocity(self, term):
    method __repr__ (line 202) | def __repr__(self):

FILE: alm/models/modeltype/base.py
  class BaseModel (line 8) | class BaseModel(LightningModule):
    method __init__ (line 10) | def __init__(self, *args, **kwargs):
    method __post_init__ (line 14) | def __post_init__(self):
    method training_step (line 25) | def training_step(self, batch, batch_idx):
    method validation_step (line 28) | def validation_step(self, batch, batch_idx):
    method test_step (line 31) | def test_step(self, batch, batch_idx):
    method predict_step (line 36) | def predict_step(self, batch, batch_idx):
    method allsplit_epoch_end (line 39) | def allsplit_epoch_end(self, split: str, outputs):
    method training_epoch_end (line 73) | def training_epoch_end(self, outputs):
    method validation_epoch_end (line 76) | def validation_epoch_end(self, outputs):
    method test_epoch_end (line 79) | def test_epoch_end(self, outputs):
    method configure_optimizers (line 115) | def configure_optimizers(self):

FILE: alm/models/modeltype/diffusion_bias.py
  class DIFFUSION_BIAS (line 26) | class DIFFUSION_BIAS(BaseModel):
    method __init__ (line 28) | def __init__(self, cfg, datamodule, **kwargs):
    method allsplit_step (line 95) | def allsplit_step(self, split: str, batch, batch_idx):
    method _memory_mask (line 273) | def _memory_mask(self, hidden_attention, ):
    method _tgt_mask (line 312) | def _tgt_mask(self, vertice_attention, ):
    method _mem_key_padding_mask (line 349) | def _mem_key_padding_mask(self, vertice_attention):
    method _tgt_key_padding_mask (line 364) | def _tgt_key_padding_mask(self, vertice_attention):
    method _audio_resize (line 379) | def _audio_resize(self, hidden_state: torch.Tensor, input_fps: Optiona...
    method _audio_2_hidden (line 399) | def _audio_2_hidden(self, audio, audio_attention, length = None):
    method _diffusion_forward (line 417) | def _diffusion_forward(self, batch, batch_idx, phase):
    method smooth (line 487) | def smooth(self, vertices):
    method predict (line 498) | def predict(self, batch, **kwargs):
    method _diffusion_process (line 546) | def _diffusion_process(
    method _diffusion_reverse (line 598) | def _diffusion_reverse(
    method _visualize (line 675) | def _visualize(self, batch, rs_set, parrallel = True):

FILE: alm/utils/demo_utils.py
  function load_example_input (line 25) | def load_example_input(audio_path, processor = None):
  function render_mesh_helper (line 132) | def render_mesh_helper(mesh, t_center, rot=np.zeros(3), tex_img=None, z_...
  function render_frame (line 218) | def render_frame(args):
  function animate (line 225) | def animate(vertices: np.array, wav_path: str, file_name: str, ply: str,...

FILE: alm/utils/logger.py
  function create_logger (line 9) | def create_logger(cfg, phase='train'):
  function config_logger (line 38) | def config_logger(final_output_dir, time_str, phase, head):
  function new_dir (line 56) | def new_dir(cfg, phase, time_str, final_output_dir):

FILE: alm/utils/temos_utils.py
  function lengths_to_mask (line 7) | def lengths_to_mask(lengths: Tensor, # [batch_size]
  function remove_padding (line 15) | def remove_padding(tensors, lengths):

FILE: demo_biwi.py
  function main (line 12) | def main():

FILE: demo_vocaset.py
  function main (line 36) | def main():

FILE: demo_vocaset_text.py
  function main (line 13) | def main():

FILE: eval_biwi.py
  function print_table (line 54) | def print_table(title, metrics):
  function get_metric_statistics (line 66) | def get_metric_statistics(values, replication_times):
  function main (line 72) | def main():

FILE: eval_vocaset.py
  function print_table (line 27) | def print_table(title, metrics):
  function get_metric_statistics (line 39) | def get_metric_statistics(values, replication_times):
  function main (line 45) | def main():

FILE: train.py
  function main (line 18) | def main():