SYMBOL INDEX (450 symbols across 33 files)

FILE: attribute_level/attribute.py
  class AttributeClassifier (line 66) | class AttributeClassifier:  # Neural network method
    method __init__ (line 67) | def __init__(self):
    method train_from_data (line 72) | def train_from_data(self, train_raw_data, test_raw_data, W, word2index...
    method load_model (line 141) | def load_model(self, check_point):
  function split_dev (line 145) | def split_dev(train_texts, train_labels, folds=5):
  function main (line 158) | def main():
  function kfold_split (line 195) | def kfold_split(length, k=5):
  function ensemble (line 208) | def ensemble():
  function test (line 249) | def test():
  function dev (line 276) | def dev():
  function load_elmo (line 300) | def load_elmo(test_texts):
  function get_oof (line 315) | def get_oof(clfs, raw_texts, raw_labels, test_data, word2index, attr_dict):
  function load_oof (line 363) | def load_oof(dir):
  function stacking (line 371) | def stacking():

FILE: attribute_level/networks2.py
  class WordRep (line 6) | class WordRep(nn.Module):
    method __init__ (line 7) | def __init__(self, vocab_size, word_embed_dim, char_size, args):
    method forward (line 23) | def forward(self, input_tensors):
  class LSTM (line 74) | class LSTM(nn.Module):
    method __init__ (line 75) | def __init__(self, word_embed_dim, output_size, vocab_size, args=None):
    method forward (line 96) | def forward(self, input_tensors):
  class CNN (line 109) | class CNN(nn.Module):
    method __init__ (line 110) | def __init__(self, word_embed_dim, output_size, vocab_size, args=None,...
    method forward (line 146) | def forward(self, input_tensors):
    method optimize_step (line 166) | def optimize_step(self, input_tensors, category_tensor, optimizer):
  class AttA3 (line 183) | class AttA3(nn.Module):
    method __init__ (line 184) | def __init__(self, word_embed_dim, output_size, vocab_size, args=None):
    method forward (line 226) | def forward(self, input_tensors):
    method optimize_step (line 271) | def optimize_step(self, input_tensors, category_tensor, optimizer):

FILE: bert/convert_tf_checkpoint_to_pytorch.py
  function convert (line 51) | def convert():

FILE: bert/convert_tf_checkpoint_to_pytorch_raw.py
  function convert (line 51) | def convert():

FILE: bert/download_MSRP.py
  function download_and_extract (line 26) | def download_and_extract(task, data_dir):
  function format_mrpc (line 35) | def format_mrpc(data_dir, path_to_data):
  function download_diagnostic (line 79) | def download_diagnostic(data_dir):
  function get_tasks (line 88) | def get_tasks(task_names):
  function main (line 99) | def main(arguments):

FILE: bert/extract_features.py
  class InputExample (line 41) | class InputExample(object):
    method __init__ (line 43) | def __init__(self, unique_id, text_a, text_b):
  class InputFeatures (line 49) | class InputFeatures(object):
    method __init__ (line 52) | def __init__(self, unique_id, tokens, input_ids, input_mask, input_typ...
  function convert_examples_to_features (line 60) | def convert_examples_to_features(examples, seq_length, tokenizer):
  function _truncate_seq_pair (line 151) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function read_examples (line 168) | def read_examples(input_file):
  function main (line 192) | def main():

FILE: bert/glue_data/generate_npy.py
  function categories_from_output (line 7) | def categories_from_output(output, t = 0.45):
  function kfold_split (line 24) | def kfold_split(length, k=5):
  function merge_oof (line 37) | def merge_oof(dir):

FILE: bert/glue_data/generate_npy_for_polarity.py
  function categories_from_output (line 7) | def categories_from_output(output, t = 0.45):
  function kfold_split (line 24) | def kfold_split(length, k=5):
  function merge_oof (line 37) | def merge_oof(dir):

FILE: bert/modeling.py
  function gelu (line 29) | def gelu(x):
  class BertConfig (line 37) | class BertConfig(object):
    method __init__ (line 40) | def __init__(self,
    method from_dict (line 89) | def from_dict(cls, json_object):
    method from_json_file (line 97) | def from_json_file(cls, json_file):
    method to_dict (line 103) | def to_dict(self):
    method to_json_string (line 108) | def to_json_string(self):
  class BERTLayerNorm (line 113) | class BERTLayerNorm(nn.Module):
    method __init__ (line 114) | def __init__(self, config, variance_epsilon=1e-12):
    method forward (line 122) | def forward(self, x):
  class BERTEmbeddings (line 128) | class BERTEmbeddings(nn.Module):
    method __init__ (line 129) | def __init__(self, config):
    method forward (line 142) | def forward(self, input_ids, token_type_ids=None):
  class BERTSelfAttention (line 159) | class BERTSelfAttention(nn.Module):
    method __init__ (line 160) | def __init__(self, config):
    method transpose_for_scores (line 176) | def transpose_for_scores(self, x):
    method forward (line 181) | def forward(self, hidden_states, attention_mask):
  class BERTSelfOutput (line 210) | class BERTSelfOutput(nn.Module):
    method __init__ (line 211) | def __init__(self, config):
    method forward (line 217) | def forward(self, hidden_states, input_tensor):
  class BERTAttention (line 224) | class BERTAttention(nn.Module):
    method __init__ (line 225) | def __init__(self, config):
    method forward (line 230) | def forward(self, input_tensor, attention_mask):
  class BERTIntermediate (line 236) | class BERTIntermediate(nn.Module):
    method __init__ (line 237) | def __init__(self, config):
    method forward (line 242) | def forward(self, hidden_states):
  class BERTOutput (line 248) | class BERTOutput(nn.Module):
    method __init__ (line 249) | def __init__(self, config):
    method forward (line 255) | def forward(self, hidden_states, input_tensor):
  class BERTLayer (line 262) | class BERTLayer(nn.Module):
    method __init__ (line 263) | def __init__(self, config):
    method forward (line 269) | def forward(self, hidden_states, attention_mask):
  class BERTEncoder (line 276) | class BERTEncoder(nn.Module):
    method __init__ (line 277) | def __init__(self, config):
    method forward (line 282) | def forward(self, hidden_states, attention_mask):
  class BERTPooler (line 290) | class BERTPooler(nn.Module):
    method __init__ (line 291) | def __init__(self, config):
    method forward (line 296) | def forward(self, hidden_states):
  class BertModel (line 305) | class BertModel(nn.Module):
    method __init__ (line 322) | def __init__(self, config: BertConfig):
    method forward (line 333) | def forward(self, input_ids, token_type_ids=None, attention_mask=None):
  class BertForSequenceClassification (line 360) | class BertForSequenceClassification(nn.Module):
    method __init__ (line 381) | def __init__(self, config, num_labels):
    method forward (line 399) | def forward(self, input_ids, token_type_ids, attention_mask, labels=No...
  class BertForSequenceClassificationLSTM (line 412) | class BertForSequenceClassificationLSTM(nn.Module):
    method __init__ (line 433) | def __init__(self, config, num_labels):
    method forward (line 452) | def forward(self, input_ids, token_type_ids, attention_mask, labels=No...
  class BertForMultiLabelClassification (line 473) | class BertForMultiLabelClassification(nn.Module):
    method __init__ (line 494) | def __init__(self, config, num_labels):
    method forward (line 512) | def forward(self, input_ids, token_type_ids, attention_mask, labels=No...
  class BertForQuestionAnswering (line 525) | class BertForQuestionAnswering(nn.Module):
    method __init__ (line 544) | def __init__(self, config):
    method forward (line 563) | def forward(self, input_ids, token_type_ids, attention_mask, start_pos...

FILE: bert/optimization.py
  function warmup_cosine (line 22) | def warmup_cosine(x, warmup=0.002):
  function warmup_constant (line 27) | def warmup_constant(x, warmup=0.002):
  function warmup_linear (line 32) | def warmup_linear(x, warmup=0.002):
  class BERTAdam (line 44) | class BERTAdam(Optimizer):
    method __init__ (line 58) | def __init__(self, params, lr, warmup=-1, t_total=-1, schedule='warmup...
    method get_lr (line 78) | def get_lr(self):
    method to (line 93) | def to(self, device):
    method initialize_step (line 99) | def initialize_step(self, initial_step):
    method step (line 114) | def step(self, closure=None):

FILE: bert/run_classifier.py
  class InputExample (line 43) | class InputExample(object):
    method __init__ (line 46) | def __init__(self, guid, text_a, text_b=None, label=None):
  class InputFeatures (line 64) | class InputFeatures(object):
    method __init__ (line 67) | def __init__(self, input_ids, input_mask, segment_ids, label_id):
  class DataProcessor (line 74) | class DataProcessor(object):
    method get_train_examples (line 77) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 81) | def get_dev_examples(self, data_dir):
    method get_labels (line 85) | def get_labels(self):
    method _read_tsv (line 90) | def _read_tsv(cls, input_file, quotechar=None):
  class MrpcProcessor (line 100) | class MrpcProcessor(DataProcessor):
    method get_train_examples (line 103) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 109) | def get_dev_examples(self, data_dir):
    method get_labels (line 114) | def get_labels(self):
    method _create_examples (line 118) | def _create_examples(self, lines, set_type):
  class MnliProcessor (line 133) | class MnliProcessor(DataProcessor):
    method get_train_examples (line 136) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 141) | def get_dev_examples(self, data_dir):
    method get_labels (line 147) | def get_labels(self):
    method _create_examples (line 151) | def _create_examples(self, lines, set_type):
  class ColaProcessor (line 166) | class ColaProcessor(DataProcessor):
    method get_train_examples (line 169) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 174) | def get_dev_examples(self, data_dir):
    method get_labels (line 179) | def get_labels(self):
    method _create_examples (line 183) | def _create_examples(self, lines, set_type):
  function convert_examples_to_features (line 195) | def convert_examples_to_features(examples, label_list, max_seq_length, t...
  function _truncate_seq_pair (line 292) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function accuracy (line 308) | def accuracy(out, labels):
  function main (line 312) | def main():

FILE: bert/run_classifier_2.py
  class InputExample (line 45) | class InputExample(object):
    method __init__ (line 48) | def __init__(self, guid, text_a, text_b=None, label=None):
  class InputFeatures (line 66) | class InputFeatures(object):
    method __init__ (line 69) | def __init__(self, input_ids, input_mask, segment_ids, label_id):
  class DataProcessor (line 76) | class DataProcessor(object):
    method get_train_examples (line 79) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 83) | def get_dev_examples(self, data_dir):
    method get_labels (line 87) | def get_labels(self):
    method _read_tsv (line 92) | def _read_tsv(cls, input_file, quotechar=None):
  class MrpcProcessor (line 102) | class MrpcProcessor(DataProcessor):
    method get_train_examples (line 105) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 111) | def get_dev_examples(self, data_dir):
    method get_labels (line 116) | def get_labels(self):
    method _create_examples (line 120) | def _create_examples(self, lines, set_type):
  class SstProcessor (line 135) | class SstProcessor(DataProcessor):
    method get_train_examples (line 138) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 144) | def get_dev_examples(self, data_dir):
    method get_labels (line 149) | def get_labels(self):
    method _create_examples (line 153) | def _create_examples(self, lines, set_type):
  class AspectProcessor (line 167) | class AspectProcessor(DataProcessor):
    method get_train_examples (line 170) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 176) | def get_dev_examples(self, data_dir):
    method get_labels (line 181) | def get_labels(self):
    method _create_examples (line 185) | def _create_examples(self, lines, set_type):
  class MnliProcessor (line 202) | class MnliProcessor(DataProcessor):
    method get_train_examples (line 205) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 210) | def get_dev_examples(self, data_dir):
    method get_labels (line 216) | def get_labels(self):
    method _create_examples (line 220) | def _create_examples(self, lines, set_type):
  class ColaProcessor (line 235) | class ColaProcessor(DataProcessor):
    method get_train_examples (line 238) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 243) | def get_dev_examples(self, data_dir):
    method get_labels (line 248) | def get_labels(self):
    method _create_examples (line 252) | def _create_examples(self, lines, set_type):
  function convert_examples_to_features (line 264) | def convert_examples_to_features(examples, label_list, max_seq_length, t...
  function _truncate_seq_pair (line 369) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function accuracy (line 388) | def accuracy(out, labels):
  function accuracy1 (line 397) | def accuracy1(out, labels):
  function accuracy2 (line 405) | def accuracy2(out, labels):
  function accuracy3 (line 416) | def accuracy3(out, labels):
  function accuracy3_2 (line 427) | def accuracy3_2(out, labels):
  function accuracy4 (line 438) | def accuracy4(out, labels):
  function accuracy5 (line 450) | def accuracy5(out, labels):
  function accuracy7 (line 463) | def accuracy7(out, labels):
  function score_list (line 475) | def score_list(predicted, golden):
  function categories_from_output (line 497) | def categories_from_output(output, t = 0.45):
  function main (line 520) | def main():

FILE: bert/run_classifier_ensemble.py
  class InputExample (line 45) | class InputExample(object):
    method __init__ (line 48) | def __init__(self, guid, text_a, text_b=None, label=None):
  class InputFeatures (line 66) | class InputFeatures(object):
    method __init__ (line 69) | def __init__(self, input_ids, input_mask, segment_ids, label_id):
  class DataProcessor (line 76) | class DataProcessor(object):
    method get_train_examples (line 79) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 83) | def get_dev_examples(self, data_dir):
    method get_labels (line 87) | def get_labels(self):
    method _read_tsv (line 92) | def _read_tsv(cls, input_file, quotechar=None):
  class MrpcProcessor (line 102) | class MrpcProcessor(DataProcessor):
    method get_train_examples (line 105) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 111) | def get_dev_examples(self, data_dir):
    method get_labels (line 116) | def get_labels(self):
    method _create_examples (line 120) | def _create_examples(self, lines, set_type):
  class SstProcessor (line 135) | class SstProcessor(DataProcessor):
    method get_train_examples (line 138) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 144) | def get_dev_examples(self, data_dir):
    method get_labels (line 149) | def get_labels(self):
    method _create_examples (line 153) | def _create_examples(self, lines, set_type):
  class AspectProcessor (line 167) | class AspectProcessor(DataProcessor):
    method get_train_examples (line 170) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 176) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 181) | def get_test_examples(self, data_dir):
    method get_labels (line 186) | def get_labels(self):
    method _create_examples (line 190) | def _create_examples(self, lines, set_type):
  class MnliProcessor (line 210) | class MnliProcessor(DataProcessor):
    method get_train_examples (line 213) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 218) | def get_dev_examples(self, data_dir):
    method get_labels (line 224) | def get_labels(self):
    method _create_examples (line 228) | def _create_examples(self, lines, set_type):
  class ColaProcessor (line 243) | class ColaProcessor(DataProcessor):
    method get_train_examples (line 246) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 251) | def get_dev_examples(self, data_dir):
    method get_labels (line 256) | def get_labels(self):
    method _create_examples (line 260) | def _create_examples(self, lines, set_type):
  function convert_examples_to_features (line 272) | def convert_examples_to_features(examples, label_list, max_seq_length, t...
  function _truncate_seq_pair (line 380) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function accuracy (line 399) | def accuracy(out, labels):
  function accuracy1 (line 408) | def accuracy1(out, labels):
  function accuracy2 (line 416) | def accuracy2(out, labels):
  function accuracy3 (line 427) | def accuracy3(out, labels):
  function accuracy3_2 (line 438) | def accuracy3_2(out, labels):
  function accuracy4 (line 449) | def accuracy4(out, labels):
  function accuracy5 (line 461) | def accuracy5(out, labels):
  function accuracy7 (line 474) | def accuracy7(out, labels):
  function score_list (line 487) | def score_list(predicted, golden):
  function categories_from_output (line 509) | def categories_from_output(output, t = 0.45):
  function main (line 532) | def main():
  function train (line 639) | def train(args):

FILE: bert/run_classifier_ensemble_polarity.py
  class InputExample (line 45) | class InputExample(object):
    method __init__ (line 48) | def __init__(self, guid, text_a, text_b=None, label=None):
  class InputFeatures (line 66) | class InputFeatures(object):
    method __init__ (line 69) | def __init__(self, input_ids, input_mask, segment_ids, label_id):
  class DataProcessor (line 76) | class DataProcessor(object):
    method get_train_examples (line 79) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 83) | def get_dev_examples(self, data_dir):
    method get_labels (line 87) | def get_labels(self):
    method _read_tsv (line 92) | def _read_tsv(cls, input_file, quotechar=None):
  class MrpcProcessor (line 102) | class MrpcProcessor(DataProcessor):
    method get_train_examples (line 105) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 111) | def get_dev_examples(self, data_dir):
    method get_labels (line 116) | def get_labels(self):
    method _create_examples (line 120) | def _create_examples(self, lines, set_type):
  class PolarityProcessor (line 135) | class PolarityProcessor(DataProcessor):
    method get_train_examples (line 138) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 144) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 149) | def get_test_examples(self, data_dir):
    method get_labels (line 154) | def get_labels(self):
    method _create_examples (line 158) | def _create_examples(self, lines, set_type):
  class SstProcessor (line 173) | class SstProcessor(DataProcessor):
    method get_train_examples (line 176) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 182) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 187) | def get_test_examples(self, data_dir):
    method get_labels (line 192) | def get_labels(self):
    method _create_examples (line 196) | def _create_examples(self, lines, set_type):
  class AspectProcessor (line 210) | class AspectProcessor(DataProcessor):
    method get_train_examples (line 213) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 219) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 224) | def get_test_examples(self, data_dir):
    method get_labels (line 229) | def get_labels(self):
    method _create_examples (line 233) | def _create_examples(self, lines, set_type):
  class MnliProcessor (line 253) | class MnliProcessor(DataProcessor):
    method get_train_examples (line 256) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 261) | def get_dev_examples(self, data_dir):
    method get_labels (line 267) | def get_labels(self):
    method _create_examples (line 271) | def _create_examples(self, lines, set_type):
  class ColaProcessor (line 286) | class ColaProcessor(DataProcessor):
    method get_train_examples (line 289) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 294) | def get_dev_examples(self, data_dir):
    method get_labels (line 299) | def get_labels(self):
    method _create_examples (line 303) | def _create_examples(self, lines, set_type):
  function convert_examples_to_features (line 315) | def convert_examples_to_features(examples, label_list, max_seq_length, t...
  function _truncate_seq_pair (line 414) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function accuracy (line 434) | def accuracy(out, labels):
  function score2 (line 439) | def score2(predicted, golden):
  function main (line 455) | def main():
  function do_eval (line 572) | def do_eval(model, device, eval_features, args):
  function train (line 628) | def train(args):

FILE: bert/run_squad.py
  class SquadExample (line 46) | class SquadExample(object):
    method __init__ (line 49) | def __init__(self,
    method __str__ (line 63) | def __str__(self):
    method __repr__ (line 66) | def __repr__(self):
  class InputFeatures (line 79) | class InputFeatures(object):
    method __init__ (line 82) | def __init__(self,
  function read_squad_examples (line 107) | def read_squad_examples(input_file, is_training):
  function convert_examples_to_features (line 176) | def convert_examples_to_features(examples, tokenizer, max_seq_length,
  function _improve_answer_span (line 329) | def _improve_answer_span(doc_tokens, input_start, input_end, tokenizer,
  function _check_is_max_context (line 366) | def _check_is_max_context(doc_spans, cur_span_index, position):
  function write_predictions (line 408) | def write_predictions(all_examples, all_features, all_results, n_best_size,
  function get_final_text (line 542) | def get_final_text(pred_text, orig_text, do_lower_case, verbose_logging=...
  function _get_best_indexes (line 638) | def _get_best_indexes(logits, n_best_size):
  function _compute_softmax (line 650) | def _compute_softmax(scores):
  function main (line 673) | def main():

FILE: bert/tests/modeling_test.py
  class BertModelTest (line 28) | class BertModelTest(unittest.TestCase):
    class BertModelTester (line 29) | class BertModelTester(object):
      method __init__ (line 31) | def __init__(self,
      method create_model (line 69) | def create_model(self):
      method check_output (line 104) | def check_output(self, result):
    method test_default (line 111) | def test_default(self):
    method test_config_to_json_string (line 114) | def test_config_to_json_string(self):
    method run_tester (line 120) | def run_tester(self, tester):
    method ids_tensor (line 125) | def ids_tensor(cls, shape, vocab_size, rng=None, name=None):

FILE: bert/tests/optimization_test.py
  class OptimizationTest (line 25) | class OptimizationTest(unittest.TestCase):
    method assertListAlmostEqual (line 27) | def assertListAlmostEqual(self, list1, list2, tol):
    method test_adam (line 32) | def test_adam(self):

FILE: bert/tests/tokenization_test.py
  class TokenizationTest (line 25) | class TokenizationTest(unittest.TestCase):
    method test_full_tokenizer (line 27) | def test_full_tokenizer(self):
    method test_basic_tokenizer_lower (line 46) | def test_basic_tokenizer_lower(self):
    method test_basic_tokenizer_no_lower (line 54) | def test_basic_tokenizer_no_lower(self):
    method test_wordpiece_tokenizer (line 61) | def test_wordpiece_tokenizer(self):
    method test_convert_tokens_to_ids (line 81) | def test_convert_tokens_to_ids(self):
    method test_is_whitespace (line 95) | def test_is_whitespace(self):
    method test_is_control (line 105) | def test_is_control(self):
    method test_is_punctuation (line 113) | def test_is_punctuation(self):

FILE: bert/tokenization.py
  function convert_to_unicode (line 27) | def convert_to_unicode(text):
  function printable_text (line 47) | def printable_text(text):
  function load_vocab (line 70) | def load_vocab(vocab_file):
  function convert_tokens_to_ids (line 85) | def convert_tokens_to_ids(vocab, tokens):
  function whitespace_tokenize (line 93) | def whitespace_tokenize(text):
  class FullTokenizer (line 102) | class FullTokenizer(object):
    method __init__ (line 105) | def __init__(self, vocab_file, do_lower_case=True):
    method tokenize (line 110) | def tokenize(self, text):
    method convert_tokens_to_ids (line 118) | def convert_tokens_to_ids(self, tokens):
  class BasicTokenizer (line 122) | class BasicTokenizer(object):
    method __init__ (line 125) | def __init__(self, do_lower_case=True):
    method tokenize (line 133) | def tokenize(self, text):
    method _run_strip_accents (line 157) | def _run_strip_accents(self, text):
    method _run_split_on_punc (line 168) | def _run_split_on_punc(self, text):
    method _tokenize_chinese_chars (line 188) | def _tokenize_chinese_chars(self, text):
    method _is_chinese_char (line 201) | def _is_chinese_char(self, cp):
    method _clean_text (line 223) | def _clean_text(self, text):
  class WordpieceTokenizer (line 237) | class WordpieceTokenizer(object):
    method __init__ (line 240) | def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=...
    method tokenize (line 245) | def tokenize(self, text):
  function _is_whitespace (line 299) | def _is_whitespace(char):
  function _is_control (line 311) | def _is_control(char):
  function _is_punctuation (line 323) | def _is_punctuation(char):

FILE: data/generate_dev.py
  function kfold_split (line 5) | def kfold_split(length, k=5):
  function load_attr_data (line 17) | def load_attr_data(filename):

FILE: data/generate_dev_polarity.py
  function kfold_split (line 6) | def kfold_split(length, k=5):
  function load_abp_raw (line 19) | def load_abp_raw(filename):  # aspect_based polarity
  function splits (line 24) | def splits(fo, train_index, dev_index):
  function count_instance (line 52) | def count_instance(fo):

FILE: data/generate_test.py
  function kfold_split (line 5) | def kfold_split(length, k=5):
  function load_attr_data (line 17) | def load_attr_data(filename):

FILE: polarity_level_aspect/ab_polarity.py
  class Classifier (line 65) | class Classifier:  # Neural network method
    method __init__ (line 66) | def __init__(self):
    method train_from_data (line 71) | def train_from_data(self, train_raw_data, test_raw_data, W, word2index...
    method split_dev (line 145) | def split_dev(self, train_texts, train_t, train_ow):
    method predict (line 175) | def predict(self, rnn, test_raw_data, word2index, args):
  function kfold_split (line 203) | def kfold_split(length, k=5):
  function splits (line 216) | def splits(fo, train_index, dev_index):
  function count_instance (line 244) | def count_instance(fo):
  function ensemble (line 258) | def ensemble():
  function main (line 299) | def main():
  function test (line 339) | def test():
  function load_elmo (line 388) | def load_elmo(test_texts):
  function get_oof (line 403) | def get_oof(clfs, fo, test_data, word2index, polarity_dict, attr_dict):
  function get_oof_test (line 454) | def get_oof_test(clfs, test_data):
  function load_oof_dir (line 476) | def load_oof_dir(dir):
  function load_oof_test (line 484) | def load_oof_test(dir):
  function load_oof (line 490) | def load_oof(clfs, fo, test_data, word2index, polarity_dict, attr_dict):
  function load_oof3 (line 503) | def load_oof3(clfs, fo, test_data, word2index, polarity_dict, attr_dict)...
  function softmax (line 516) | def softmax(x):
  function stacking (line 523) | def stacking():
  function blending (line 602) | def blending():

FILE: polarity_level_aspect/networks.py
  class WordRep (line 6) | class WordRep(nn.Module):
    method __init__ (line 7) | def __init__(self, vocab_size, word_embed_dim, char_size, args):
    method forward (line 23) | def forward(self, input_tensors):
  class AT_LSTM (line 74) | class AT_LSTM(nn.Module):
    method __init__ (line 75) | def __init__(self, word_embed_dim, output_size, vocab_size, aspect_siz...
    method forward (line 104) | def forward(self, input_tensors):
  class GCAE (line 155) | class GCAE(nn.Module):
    method __init__ (line 156) | def __init__(self, word_embed_dim, output_size, vocab_size, aspect_siz...
    method forward (line 180) | def forward(self, input_tensors):
  class HEAT (line 203) | class HEAT(nn.Module):
    method __init__ (line 204) | def __init__(self, word_embed_dim, output_size, vocab_size, aspect_siz...
    method forward (line 246) | def forward(self, input_tensors):

FILE: utils/Data.py
  class Data (line 5) | class Data:
    method __init__ (line 6) | def __init__(self, train_raw_data, word2index, attr_dict=None, args=No...
    method get (line 23) | def get(self, index, cuda_flag):
    method add_feature (line 42) | def add_feature(self, features):
    method get_input (line 45) | def get_input(self, index, cuda_flag):
    method to_tensor (line 48) | def to_tensor(self, text, word2id):
    method label2tensor (line 67) | def label2tensor(self, labels, attrDict):
    method generate_char_tensor (line 81) | def generate_char_tensor(self, text, char2id):
  class Data2 (line 102) | class Data2:  # data for polarity:
    method __init__ (line 103) | def __init__(self, train_raw_data, word2index, polarity_dict=None, arg...
    method get (line 123) | def get(self, index, cuda_flag):
    method to_tensor (line 142) | def to_tensor(self, text, word2id):
    method label2tensor (line 157) | def label2tensor(self, labels, attrDict):
  class Data3 (line 178) | class Data3:  # data for aspect_polarity:
    method __init__ (line 179) | def __init__(self, train_raw_data, word2index, polarity_dict=None, arg...
    method get (line 206) | def get(self, index, cuda_flag):
    method add_feature (line 231) | def add_feature(self, features):
    method to_tensor (line 234) | def to_tensor(self, text, word2id):
    method label2tensor (line 249) | def label2tensor(self, labels, attrDict):

FILE: utils/data_helper.py
  function load_w2v (line 42) | def load_w2v(filename):
  function load_attr_data (line 66) | def load_attr_data(filename):
  function load_abp_data (line 85) | def load_abp_data(filename, dev=False, folds=5):  # aspect_based polarity
  function load_abp_raw (line 121) | def load_abp_raw(filename):  # aspect_based polarity
  function load_test_data (line 127) | def load_test_data(filename):
  function load_ab_test (line 140) | def load_ab_test(f1, f2):
  function load_pos (line 166) | def load_pos(ds):
  function load_char2id (line 188) | def load_char2id(ds):
  function generate_sentence_label (line 203) | def generate_sentence_label(train_texts, train_ow):  # combine all ow la...
  function parse_json (line 226) | def parse_json(filename):

FILE: utils/evaluate.py
  function score_list (line 5) | def score_list(predicted, golden):
  function score (line 27) | def score(predicted, golden):
  function label_analysis (line 49) | def label_analysis(predicted, golden):
  function score2 (line 63) | def score2(predicted, golden):
  function label_analysis2 (line 82) | def label_analysis2(predicted, golden, label_num):
  function score_aspect (line 95) | def score_aspect(predict_list, true_list):

FILE: utils/prepare_w2v.py
  function prepare_w2v (line 13) | def prepare_w2v(ds=None):
  function load_vocab (line 77) | def load_vocab():
  function load_ft (line 112) | def load_ft():
  function test_miss (line 148) | def test_miss():
  function test (line 175) | def test():

FILE: utils/prepare_w2v_with_UNK.py
  function prepare_w2v (line 13) | def prepare_w2v(ds=None):
  function load_vocab (line 78) | def load_vocab():
  function load_ft (line 113) | def load_ft():
  function test_miss (line 149) | def test_miss():
  function test (line 176) | def test():

FILE: utils/train.py
  function train (line 15) | def train(rnn, train_data, dev_data, test_data, attr_dict, W, args):
  function optimize_step (line 117) | def optimize_step(rnn, input_tensors, category_tensor, optimizer):
  function customized_loss2 (line 133) | def customized_loss2(input, target):
  function category_from_output (line 162) | def category_from_output(output):
  function categories_from_output (line 170) | def categories_from_output(output, threshold=[0.45 for _ in range(10)]):
  function predict (line 196) | def predict(rnn, dev_data, args):
  function predict_with_logit (line 223) | def predict_with_logit(rnn, dev_data, args):

FILE: utils/train2.py
  function train (line 15) | def train(rnn, train_data, dev_data, test_data, attr_dict, W, args):
  function optimize_step (line 117) | def optimize_step(rnn, input_tensors, category_tensor, optimizer):
  function customized_loss2 (line 133) | def customized_loss2(input, target):
  function category_from_output (line 162) | def category_from_output(output):
  function categories_from_output (line 170) | def categories_from_output(output, threshold=[0.45 for _ in range(10)]):
  function predict (line 196) | def predict(rnn, dev_data, args):
  function predict_with_logit (line 223) | def predict_with_logit(rnn, dev_data, args):

FILE: utils/train_single.py
  function train (line 15) | def train(rnn, train_data, dev_data, test_data, attr_dict, W, args):
  function optimize_step (line 138) | def optimize_step(rnn, input_tensors, category_tensor, optimizer):
  function category_from_output (line 157) | def category_from_output(output):
  function categories_from_output (line 165) | def categories_from_output(output):
  function predict (line 183) | def predict(rnn, dev_data, args):
  function predict_with_logit (line 213) | def predict_with_logit(rnn, dev_data, args):

FILE: utils/utils.py
  function time_since (line 4) | def time_since(since):