SYMBOL INDEX (88 symbols across 17 files)

FILE: common/instance.py
  class Instance (line 8) | class Instance:
    method __init__ (line 13) | def __init__(self, input: Sentence, output: List[str] = None, embeddin...
    method __len__ (line 32) | def __len__(self):

FILE: common/sentence.py
  class Sentence (line 8) | class Sentence:
    method __init__ (line 13) | def __init__(self, words: List[str], pos_tags:List[str] = None):
    method __len__ (line 22) | def __len__(self):

FILE: config/config.py
  class ContextEmb (line 21) | class ContextEmb(Enum):
  class Config (line 28) | class Config:
    method __init__ (line 29) | def __init__(self, args) -> None:
    method read_pretrain_embedding (line 104) | def read_pretrain_embedding(self) -> Tuple[Union[Dict[str, np.array], ...
    method build_word_idx (line 139) | def build_word_idx(self, train_insts: List[Instance], dev_insts: List[...
    method add_word_idx (line 180) | def add_word_idx(self, match_insts):
    method build_emb_table (line 187) | def build_emb_table(self) -> None:
    method build_label_idx (line 210) | def build_label_idx(self, insts: List[Instance]) -> None:
    method use_iobes (line 238) | def use_iobes(self, insts: List[Instance]) -> None:
    method map_insts_ids (line 262) | def map_insts_ids(self, insts: List[Instance]):

FILE: config/eval.py
  class Span (line 12) | class Span:
    method __init__ (line 17) | def __init__(self, left: int, right: int, type: str):
    method __eq__ (line 28) | def __eq__(self, other):
    method __hash__ (line 31) | def __hash__(self):
  function evaluate_batch_insts (line 35) | def evaluate_batch_insts(batch_insts: List[Instance],

FILE: config/reader.py
  class Reader (line 14) | class Reader:
    method __init__ (line 16) | def __init__(self, digit2zero:bool=True):
    method read_txt (line 24) | def read_txt(self, file: str, number: int = -1) -> List[Instance]:
    method read_trigger_txt (line 48) | def read_trigger_txt(self, file: str, percentage, number: int = -1) ->...
    method merge_labels (line 113) | def merge_labels(self, dataset):
    method trigger_percentage (line 142) | def trigger_percentage(self, dataset, percentage):

FILE: config/utils.py
  function log_sum_exp_pytorch (line 16) | def log_sum_exp_pytorch(vec: torch.Tensor) -> torch.Tensor:
  function batching_list_instances (line 28) | def batching_list_instances(config: Config, insts: List[Instance], is_so...
  function simple_batching (line 39) | def simple_batching(config, insts: List[Instance], is_soft=False, is_nai...
  function lr_decay (line 110) | def lr_decay(config, optimizer: optim.Optimizer, epoch: int) -> optim.Op...
  function load_bert_vec (line 125) | def load_bert_vec(file: str, insts: List[Instance]):
  function get_bert_embedding (line 158) | def get_bert_embedding(batch):
  function get_optimizer (line 189) | def get_optimizer(config: Config, model: nn.Module, name=None):
  function write_results (line 210) | def write_results(filename: str, insts):

FILE: model/charbilstm.py
  class CharBiLSTM (line 10) | class CharBiLSTM(nn.Module):
    method __init__ (line 12) | def __init__(self, config, print_info: bool = True):
    method forward (line 27) | def forward(self, char_seq_tensor: torch.Tensor, char_seq_len: torch.T...

FILE: model/linear_crf_inferencer.py
  class LinearCRF (line 11) | class LinearCRF(nn.Module):
    method __init__ (line 13) | def __init__(self, config, print_info: bool = True):
    method forward (line 37) | def forward(self, lstm_scores, word_seq_lens, tags, mask):
    method forward_unlabeled (line 51) | def forward_unlabeled(self, all_scores: torch.Tensor, word_seq_lens: t...
    method forward_labeled (line 76) | def forward_labeled(self, all_scores: torch.Tensor, word_seq_lens: tor...
    method calculate_all_scores (line 99) | def calculate_all_scores(self, lstm_scores: torch.Tensor) -> torch.Ten...
    method decode (line 113) | def decode(self, features, wordSeqLengths, annotation_mask = None) -> ...
    method constrainted_viterbi_decode (line 123) | def constrainted_viterbi_decode(self, all_scores: torch.Tensor, word_s...

FILE: model/soft_attention.py
  class SoftAttention (line 12) | class SoftAttention(nn.Module):
    method __init__ (line 13) | def __init__(self, config):
    method attention (line 24) | def attention(self, lstm_output, mask):
    method forward (line 49) | def forward(self, sentence_vec, sentence_mask, trigger_vec, trigger_ma...

FILE: model/soft_encoder.py
  class SoftEncoder (line 14) | class SoftEncoder(nn.Module):
    method __init__ (line 15) | def __init__(self, config, encoder = None):
    method forward (line 41) | def forward(self, word_seq_tensor: torch.Tensor,

FILE: model/soft_inferencer.py
  class SoftSequence (line 19) | class SoftSequence(nn.Module):
    method __init__ (line 20) | def __init__(self, config, softmatcher, encoder=None, print_info=True):
    method forward (line 45) | def forward(self, word_seq_tensor: torch.Tensor,
    method decode (line 100) | def decode(self, word_seq_tensor: torch.Tensor,
  class SoftSequenceTrainer (line 152) | class SoftSequenceTrainer(object):
    method __init__ (line 153) | def __init__(self, model, config, dev, test, triggers):
    method train_model (line 169) | def train_model(self, num_epochs, train_data, eval):
    method self_training (line 194) | def self_training(self, num_epochs, train_data, unlabeled_data):
    method evaluate_model (line 226) | def evaluate_model(self, batch_insts_ids, name: str, insts, triggers):
    method weakly_labeling (line 245) | def weakly_labeling(self, batch_insts_ids, insts, triggers):
    method weak_label_selftrain (line 281) | def weak_label_selftrain(self, unlabeled_data, triggers):

FILE: model/soft_inferencer_naive.py
  class SoftSequenceNaive (line 16) | class SoftSequenceNaive(nn.Module):
    method __init__ (line 17) | def __init__(self, config,  encoder=None, print_info=True):
    method forward (line 30) | def forward(self, word_seq_tensor: torch.Tensor,
    method decode (line 54) | def decode(self, word_seq_tensor: torch.Tensor,
  class SoftSequenceNaiveTrainer (line 68) | class SoftSequenceNaiveTrainer(object):
    method __init__ (line 69) | def __init__(self, model, config, dev, test):
    method train_model (line 83) | def train_model(self, num_epochs, train_data):
    method evaluate_model (line 108) | def evaluate_model(self, batch_insts_ids, name: str, insts):

FILE: model/soft_matcher.py
  class ContrastiveLoss (line 21) | class ContrastiveLoss(nn.Module):
    method __init__ (line 22) | def __init__(self, margin, device):
    method forward (line 28) | def forward(self, output1, output2, target, size_average=True):
  class SoftMatcher (line 36) | class SoftMatcher(nn.Module):
    method __init__ (line 37) | def __init__(self, config, num_classes):
    method forward (line 48) | def forward(self, word_seq_tensor: torch.Tensor,
  class SoftMatcherTrainer (line 62) | class SoftMatcherTrainer(object):
    method __init__ (line 63) | def __init__(self, model, config, dev, test):
    method train_model (line 78) | def train_model(self, num_epochs, train_data):
    method test_model (line 102) | def test_model(self, test_data):
    method get_triggervec (line 125) | def get_triggervec(self, data):

FILE: naive.py
  function parse_arguments (line 13) | def parse_arguments(parser):

FILE: semi_supervised.py
  function parse_arguments (line 21) | def parse_arguments(parser):
  function main (line 61) | def main():

FILE: supervised.py
  function parse_arguments (line 15) | def parse_arguments(parser):

FILE: util.py
  function remove_duplicates (line 20) | def remove_duplicates(features, labels, triggers, dataset):