SYMBOL INDEX (113 symbols across 5 files)

FILE: inference.py
  class InputExample (line 7) | class InputExample():
    method __init__ (line 8) | def __init__(self, words, labels):
  function template_entity (line 12) | def template_entity(words, input_TXT, start):
  function prediction (line 58) | def prediction(input_TXT):
  function cal_time (line 94) | def cal_time(since):

FILE: modeling_bart.py
  function invert_mask (line 133) | def invert_mask(attention_mask):
  function _prepare_bart_decoder_inputs (line 139) | def _prepare_bart_decoder_inputs(
  class PretrainedBartModel (line 163) | class PretrainedBartModel(PreTrainedModel):
    method _init_weights (line 167) | def _init_weights(self, module):
    method dummy_inputs (line 181) | def dummy_inputs(self):
  function _make_linear_from_emb (line 191) | def _make_linear_from_emb(emb):
  function _check_shapes (line 199) | def _check_shapes(shape_1, shape2):
  function shift_tokens_right (line 204) | def shift_tokens_right(input_ids, pad_token_id):
  function make_padding_mask (line 213) | def make_padding_mask(input_ids, padding_idx=1):
  class Adapter (line 222) | class Adapter(nn.Module):
    method __init__ (line 223) | def __init__(self, config):
    method forward (line 231) | def forward(self, hidden_states):
    method init_weights (line 237) | def init_weights(self, config):
  class EncoderLayer (line 248) | class EncoderLayer(nn.Module):
    method __init__ (line 249) | def __init__(self, config: BartConfig):
    method forward (line 267) | def forward(self, x, encoder_padding_mask, output_attentions=False):
  class BartEncoder (line 307) | class BartEncoder(nn.Module):
    method __init__ (line 316) | def __init__(self, config: BartConfig, embed_tokens):
    method forward (line 344) | def forward(
  class DecoderLayer (line 405) | class DecoderLayer(nn.Module):
    method __init__ (line 406) | def __init__(self, config: BartConfig):
    method forward (line 436) | def forward(
  class BartDecoder (line 504) | class BartDecoder(nn.Module):
    method __init__ (line 513) | def __init__(self, config: BartConfig, embed_tokens: nn.Embedding):
    method forward (line 538) | def forward(
  function _reorder_buffer (line 652) | def _reorder_buffer(attn_cache, new_order):
  class Attention (line 659) | class Attention(nn.Module):
    method __init__ (line 662) | def __init__(
    method _shape (line 685) | def _shape(self, tensor, seq_len, bsz):
    method forward (line 688) | def forward(
    method _use_saved_state (line 779) | def _use_saved_state(self, k, v, saved_state, key_padding_mask, static...
  class BartClassificationHead (line 811) | class BartClassificationHead(nn.Module):
    method __init__ (line 816) | def __init__(
    method forward (line 828) | def forward(self, x):
  class LearnedPositionalEmbedding (line 837) | class LearnedPositionalEmbedding(nn.Embedding):
    method __init__ (line 845) | def __init__(self, num_embeddings: int, embedding_dim: int, padding_id...
    method forward (line 853) | def forward(self, input_ids, use_cache=False):
  function LayerNorm (line 864) | def LayerNorm(normalized_shape, eps=1e-5, elementwise_affine=True):
  function fill_with_neg_inf (line 875) | def fill_with_neg_inf(t):
  function _get_shape (line 881) | def _get_shape(t):
  class BartModel (line 889) | class BartModel(PretrainedBartModel):
    method __init__ (line 890) | def __init__(self, config: BartConfig):
    method forward (line 915) | def forward(
    method get_input_embeddings (line 1003) | def get_input_embeddings(self):
    method set_input_embeddings (line 1006) | def set_input_embeddings(self, value):
    method get_output_embeddings (line 1011) | def get_output_embeddings(self):
  class BartAdapterForConditionalGeneration (line 1018) | class BartAdapterForConditionalGeneration(PretrainedBartModel):
    method __init__ (line 1022) | def __init__(self, config: BartConfig):
    method resize_token_embeddings (line 1028) | def resize_token_embeddings(self, new_num_tokens: int) -> nn.Embedding:
    method _resize_final_logits_bias (line 1035) | def _resize_final_logits_bias(self, new_num_tokens: int, old_num_token...
    method forward (line 1046) | def forward(
    method prepare_inputs_for_generation (line 1148) | def prepare_inputs_for_generation(
    method adjust_logits_during_generation (line 1160) | def adjust_logits_during_generation(self, logits, cur_len, max_length):
    method _force_token_ids_generation (line 1167) | def _force_token_ids_generation(self, scores, token_id) -> None:
    method _reorder_cache (line 1172) | def _reorder_cache(past, beam_idx):
    method get_encoder (line 1182) | def get_encoder(self):
    method get_output_embeddings (line 1185) | def get_output_embeddings(self):
  class BartForSequenceClassification (line 1193) | class BartForSequenceClassification(PretrainedBartModel):
    method __init__ (line 1194) | def __init__(self, config: BartConfig, **kwargs):
    method forward (line 1213) | def forward(
  class BartForQuestionAnswering (line 1280) | class BartForQuestionAnswering(PretrainedBartModel):
    method __init__ (line 1281) | def __init__(self, config):
    method forward (line 1299) | def forward(
  class SinusoidalPositionalEmbedding (line 1383) | class SinusoidalPositionalEmbedding(nn.Embedding):
    method __init__ (line 1386) | def __init__(self, num_positions, embedding_dim, padding_idx=None):
    method _init_weight (line 1393) | def _init_weight(out: nn.Parameter):
    method forward (line 1408) | def forward(self, input_ids, use_cache=False):

FILE: seq2seq_model.py
  class Seq2SeqModel (line 69) | class Seq2SeqModel:
    method __init__ (line 70) | def __init__(
    method train_model (line 216) | def train_model(
    method train (line 285) | def train(
    method eval_model (line 673) | def eval_model(self, eval_data, output_dir=None, verbose=True, silent=...
    method evaluate (line 713) | def evaluate(self, eval_dataset, output_dir, verbose=True, silent=Fals...
    method evaluate_decode (line 756) | def evaluate_decode(self, eval_dataset, output_dir, verbose=True, sile...
    method predict (line 800) | def predict(self, to_predict):
    method predict_sep (line 887) | def predict_sep(self, to_predict, decoder_input_token_id):
    method _decode (line 973) | def _decode(self, output_id):
    method compute_metrics (line 976) | def compute_metrics(self, labels, preds, **kwargs):
    method load_and_cache_examples (line 1012) | def load_and_cache_examples(self, data, evaluate=False, no_cache=False...
    method _create_training_progress_scores (line 1040) | def _create_training_progress_scores(self, **kwargs):
    method _get_last_metrics (line 1052) | def _get_last_metrics(self, metric_values):
    method _save_model (line 1055) | def _save_model(self, output_dir=None, optimizer=None, scheduler=None,...
    method _move_model_to_device (line 1104) | def _move_model_to_device(self):
    method _get_inputs_dict (line 1107) | def _get_inputs_dict(self, batch):
    method _save_model_args (line 1147) | def _save_model_args(self, output_dir):
    method _load_model_args (line 1151) | def _load_model_args(self, input_dir):
    method get_named_parameters (line 1156) | def get_named_parameters(self):

FILE: seq2seq_utils.py
  function preprocess_data (line 18) | def preprocess_data(data):
  class Seq2SeqDataset (line 31) | class Seq2SeqDataset(Dataset):
    method __init__ (line 32) | def __init__(self, encoder_tokenizer, decoder_tokenizer, args, data, m...
    method __len__ (line 68) | def __len__(self):
    method __getitem__ (line 71) | def __getitem__(self, index):
  function preprocess_data_bart (line 75) | def preprocess_data_bart(data):
  class SimpleSummarizationDataset (line 93) | class SimpleSummarizationDataset(Dataset):
    method __init__ (line 94) | def __init__(self, tokenizer, args, data, mode):
    method __len__ (line 127) | def __len__(self):
    method __getitem__ (line 130) | def __getitem__(self, index):

FILE: utils_metrics.py
  function get_entities (line 4) | def get_entities(seq):
  function end_of_chunk (line 38) | def end_of_chunk(prev_tag, tag, prev_type, type_):
  function start_of_chunk (line 68) | def start_of_chunk(prev_tag, tag, prev_type, type_):
  function get_entities_bios (line 98) | def get_entities_bios(seq):
  function get_entities_bio (line 143) | def get_entities_bio(seq):
  function get_entities_span (line 184) | def get_entities_span(starts, ends):
  function f1_score (line 202) | def f1_score(true_entities, pred_entities):
  function precision_score (line 215) | def precision_score(true_entities, pred_entities):
  function recall_score (line 225) | def recall_score(true_entities, pred_entities):
  function classification_report (line 235) | def classification_report(true_entities, pred_entities, digits=5):
  function convert_span_to_bio (line 294) | def convert_span_to_bio(starts, ends):