SYMBOL INDEX (36 symbols across 6 files)

FILE: classifier.py
  class Classifier (line 21) | class Classifier(pl.LightningModule):
    class DataModule (line 28) | class DataModule(pl.LightningDataModule):
      method __init__ (line 29) | def __init__(self, classifier_instance):
      method read_csv (line 40) | def read_csv(self, path: str) -> list:
      method train_dataloader (line 53) | def train_dataloader(self) -> DataLoader:
      method val_dataloader (line 64) | def val_dataloader(self) -> DataLoader:
      method test_dataloader (line 74) | def test_dataloader(self) -> DataLoader:
    method __init__ (line 84) | def __init__(self, hparams: Namespace) -> None:
    method __build_model (line 104) | def __build_model(self) -> None:
    method __build_loss (line 125) | def __build_loss(self):
    method unfreeze_encoder (line 129) | def unfreeze_encoder(self) -> None:
    method freeze_encoder (line 137) | def freeze_encoder(self) -> None:
    method predict (line 143) | def predict(self, sample: dict) -> dict:
    method forward (line 165) | def forward(self, tokens, lengths):
    method loss (line 192) | def loss(self, predictions: dict, targets: dict) -> torch.tensor:
    method prepare_sample (line 204) | def prepare_sample(self, sample: list, prepare_target: bool = True) ->...
    method training_step (line 228) | def training_step(self, batch: tuple, batch_nb: int, *args, **kwargs) ...
    method validation_step (line 251) | def validation_step(self, batch: tuple, batch_nb: int, *args, **kwargs...
    method validation_end (line 287) | def validation_end(self, outputs: list) -> dict:
    method configure_optimizers (line 321) | def configure_optimizers(self):
    method on_epoch_end (line 333) | def on_epoch_end(self):
    method add_model_specific_args (line 339) | def add_model_specific_args(cls, parser: ArgumentParser) -> ArgumentPa...

FILE: interact.py
  function load_model_from_experiment (line 12) | def load_model_from_experiment(experiment_folder: str):

FILE: test.py
  function load_model_from_experiment (line 16) | def load_model_from_experiment(experiment_folder: str):

FILE: tokenizer.py
  class Tokenizer (line 10) | class Tokenizer(TextEncoder):
    method __init__ (line 15) | def __init__(self, pretrained_model) -> None:
    method unk_index (line 21) | def unk_index(self) -> int:
    method bos_index (line 26) | def bos_index(self) -> int:
    method eos_index (line 31) | def eos_index(self) -> int:
    method padding_index (line 36) | def padding_index(self) -> int:
    method vocab (line 41) | def vocab(self) -> list:
    method vocab_size (line 49) | def vocab_size(self) -> int:
    method encode (line 56) | def encode(self, sequence: str) -> torch.Tensor:
    method batch_encode (line 65) | def batch_encode(self, sentences: list) -> (torch.Tensor, torch.Tensor):

FILE: training.py
  function main (line 15) | def main(hparams) -> None:

FILE: utils.py
  function mask_fill (line 7) | def mask_fill(