SYMBOL INDEX (271 symbols across 22 files)

FILE: bert/create_pretraining_data.py
  class TrainingInstance (line 64) | class TrainingInstance(object):
    method __init__ (line 67) | def __init__(self, tokens, segment_ids, masked_lm_positions, masked_lm...
    method __str__ (line 75) | def __str__(self):
    method __repr__ (line 88) | def __repr__(self):
  function write_instance_to_example_files (line 92) | def write_instance_to_example_files(instances, tokenizer, max_seq_length,
  function create_int_feature (line 165) | def create_int_feature(values):
  function create_float_feature (line 170) | def create_float_feature(values):
  function create_training_instances (line 175) | def create_training_instances(input_files, tokenizer, max_seq_length,
  function create_instances_from_document (line 219) | def create_instances_from_document(
  function create_masked_lm_predictions (line 338) | def create_masked_lm_predictions(tokens, masked_lm_prob,
  function truncate_seq_pair (line 391) | def truncate_seq_pair(tokens_a, tokens_b, max_num_tokens, rng):
  function main (line 409) | def main(_):

FILE: bert/extract_features.py
  class InputExample (line 81) | class InputExample(object):
    method __init__ (line 83) | def __init__(self, unique_id, text_a, text_b):
  class InputFeatures (line 89) | class InputFeatures(object):
    method __init__ (line 92) | def __init__(self, unique_id, tokens, input_ids, input_mask, input_typ...
  function input_fn_builder (line 100) | def input_fn_builder(features, seq_length):
  function model_fn_builder (line 148) | def model_fn_builder(bert_config, init_checkpoint, layer_indexes, use_tpu,
  function convert_examples_to_features (line 210) | def convert_examples_to_features(examples, seq_length, tokenizer):
  function _truncate_seq_pair (line 302) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function read_examples (line 319) | def read_examples(input_file):
  function main (line 343) | def main(_):

FILE: bert/modeling.py
  class BertConfig (line 31) | class BertConfig(object):
    method __init__ (line 34) | def __init__(self,
    method from_dict (line 83) | def from_dict(cls, json_object):
    method from_json_file (line 91) | def from_json_file(cls, json_file):
    method to_dict (line 97) | def to_dict(self):
    method to_json_string (line 102) | def to_json_string(self):
  class BertModel (line 107) | class BertModel(object):
    method __init__ (line 131) | def __init__(self,
    method get_pooled_output (line 234) | def get_pooled_output(self):
    method get_sequence_output (line 237) | def get_sequence_output(self):
    method get_all_encoder_layers (line 246) | def get_all_encoder_layers(self):
    method get_embedding_output (line 249) | def get_embedding_output(self):
    method get_embedding_table (line 260) | def get_embedding_table(self):
  function gelu (line 264) | def gelu(x):
  function get_activation (line 280) | def get_activation(activation_string):
  function get_assignment_map_from_checkpoint (line 317) | def get_assignment_map_from_checkpoint(tvars, init_checkpoint):
  function dropout (line 344) | def dropout(input_tensor, dropout_prob):
  function layer_norm (line 362) | def layer_norm(input_tensor, name=None):
  function layer_norm_and_dropout (line 368) | def layer_norm_and_dropout(input_tensor, dropout_prob, name=None):
  function create_initializer (line 375) | def create_initializer(initializer_range=0.02):
  function embedding_lookup (line 380) | def embedding_lookup(input_ids,
  function embedding_postprocessor (line 428) | def embedding_postprocessor(input_tensor,
  function create_attention_mask_from_input_mask (line 524) | def create_attention_mask_from_input_mask(from_tensor, to_mask):
  function attention_layer (line 558) | def attention_layer(from_tensor,
  function transformer_model (line 754) | def transformer_model(input_tensor,
  function get_shape_list (line 895) | def get_shape_list(tensor, expected_rank=None, name=None):
  function reshape_to_matrix (line 932) | def reshape_to_matrix(input_tensor):
  function reshape_from_matrix (line 946) | def reshape_from_matrix(output_tensor, orig_shape_list):
  function assert_rank (line 959) | def assert_rank(tensor, expected_rank, name=None):

FILE: bert/modeling_test.py
  class BertModelTest (line 29) | class BertModelTest(tf.test.TestCase):
    class BertModelTester (line 31) | class BertModelTester(object):
      method __init__ (line 33) | def __init__(self,
      method create_model (line 71) | def create_model(self):
      method check_output (line 114) | def check_output(self, result):
    method test_default (line 126) | def test_default(self):
    method test_config_to_json_string (line 129) | def test_config_to_json_string(self):
    method run_tester (line 135) | def run_tester(self, tester):
    method ids_tensor (line 147) | def ids_tensor(cls, shape, vocab_size, rng=None, name=None):
    method assert_all_tensors_reachable (line 162) | def assert_all_tensors_reachable(self, sess, outputs):
    method get_unreachable_ops (line 194) | def get_unreachable_ops(cls, graph, outputs):
    method flatten_recursive (line 257) | def flatten_recursive(cls, item):

FILE: bert/optimization.py
  function create_optimizer (line 25) | def create_optimizer(loss, init_lr, num_train_steps, num_warmup_steps, u...
  class AdamWeightDecayOptimizer (line 87) | class AdamWeightDecayOptimizer(tf.train.Optimizer):
    method __init__ (line 90) | def __init__(self,
    method apply_gradients (line 108) | def apply_gradients(self, grads_and_vars, global_step=None, name=None):
    method _do_use_weight_decay (line 159) | def _do_use_weight_decay(self, param_name):
    method _get_variable_name (line 169) | def _get_variable_name(self, param_name):

FILE: bert/optimization_test.py
  class OptimizationTest (line 23) | class OptimizationTest(tf.test.TestCase):
    method test_adam (line 25) | def test_adam(self):

FILE: bert/run_classifier.py
  class InputExample (line 127) | class InputExample(object):
    method __init__ (line 130) | def __init__(self, guid, text_a, text_b=None, label=None):
  class PaddingInputExample (line 148) | class PaddingInputExample(object):
  class InputFeatures (line 161) | class InputFeatures(object):
    method __init__ (line 164) | def __init__(self,
  class DataProcessor (line 177) | class DataProcessor(object):
    method get_train_examples (line 180) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 184) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 188) | def get_test_examples(self, data_dir):
    method get_labels (line 192) | def get_labels(self):
    method _read_tsv (line 197) | def _read_tsv(cls, input_file, quotechar=None):
  class XnliProcessor (line 207) | class XnliProcessor(DataProcessor):
    method __init__ (line 210) | def __init__(self):
    method get_train_examples (line 213) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 232) | def get_dev_examples(self, data_dir):
    method get_labels (line 250) | def get_labels(self):
  class MnliProcessor (line 255) | class MnliProcessor(DataProcessor):
    method get_train_examples (line 258) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 263) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 269) | def get_test_examples(self, data_dir):
    method get_labels (line 274) | def get_labels(self):
    method _create_examples (line 278) | def _create_examples(self, lines, set_type):
  class MrpcProcessor (line 296) | class MrpcProcessor(DataProcessor):
    method get_train_examples (line 299) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 304) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 309) | def get_test_examples(self, data_dir):
    method get_labels (line 314) | def get_labels(self):
    method _create_examples (line 318) | def _create_examples(self, lines, set_type):
  class ColaProcessor (line 336) | class ColaProcessor(DataProcessor):
    method get_train_examples (line 339) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 344) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 349) | def get_test_examples(self, data_dir):
    method get_labels (line 354) | def get_labels(self):
    method _create_examples (line 358) | def _create_examples(self, lines, set_type):
  function convert_single_example (line 377) | def convert_single_example(ex_index, example, label_list, max_seq_length,
  function file_based_convert_examples_to_features (line 479) | def file_based_convert_examples_to_features(
  function file_based_input_fn_builder (line 509) | def file_based_input_fn_builder(input_file, seq_length, is_training,
  function _truncate_seq_pair (line 557) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function create_model (line 574) | def create_model(bert_config, is_training, input_ids, input_mask, segmen...
  function model_fn_builder (line 619) | def model_fn_builder(bert_config, num_labels, init_checkpoint, learning_...
  function input_fn_builder (line 713) | def input_fn_builder(features, seq_length, is_training, drop_remainder):
  function convert_examples_to_features (line 767) | def convert_examples_to_features(examples, label_list, max_seq_length,
  function main (line 783) | def main(_):

FILE: bert/run_classifier_with_tfhub.py
  function create_model (line 37) | def create_model(is_training, input_ids, input_mask, segment_ids, labels,
  function model_fn_builder (line 87) | def model_fn_builder(num_labels, learning_rate, num_train_steps,
  function create_tokenizer_from_hub_module (line 146) | def create_tokenizer_from_hub_module(bert_hub_module_handle):
  function main (line 158) | def main(_):

FILE: bert/run_pretraining.py
  function model_fn_builder (line 109) | def model_fn_builder(bert_config, init_checkpoint, learning_rate,
  function get_masked_lm_output (line 240) | def get_masked_lm_output(bert_config, input_tensor, output_weights, posi...
  function get_next_sentence_output (line 285) | def get_next_sentence_output(bert_config, input_tensor, labels):
  function gather_indexes (line 308) | def gather_indexes(sequence_tensor, positions):
  function input_fn_builder (line 324) | def input_fn_builder(input_files,
  function _decode_record (line 391) | def _decode_record(record, name_to_features):
  function main (line 406) | def main(_):

FILE: bert/run_squad.py
  class SquadExample (line 157) | class SquadExample(object):
    method __init__ (line 163) | def __init__(self,
    method __str__ (line 179) | def __str__(self):
    method __repr__ (line 182) | def __repr__(self):
  class InputFeatures (line 197) | class InputFeatures(object):
    method __init__ (line 200) | def __init__(self,
  function read_squad_examples (line 227) | def read_squad_examples(input_file, is_training):
  function convert_examples_to_features (line 309) | def convert_examples_to_features(examples, tokenizer, max_seq_length,
  function _improve_answer_span (line 476) | def _improve_answer_span(doc_tokens, input_start, input_end, tokenizer,
  function _check_is_max_context (line 513) | def _check_is_max_context(doc_spans, cur_span_index, position):
  function create_model (line 550) | def create_model(bert_config, is_training, input_ids, input_mask, segmen...
  function model_fn_builder (line 590) | def model_fn_builder(bert_config, init_checkpoint, learning_rate,
  function input_fn_builder (line 687) | def input_fn_builder(input_file, seq_length, is_training, drop_remainder):
  function write_predictions (line 741) | def write_predictions(all_examples, all_features, all_results, n_best_size,
  function get_final_text (line 927) | def get_final_text(pred_text, orig_text, do_lower_case):
  function _get_best_indexes (line 1023) | def _get_best_indexes(logits, n_best_size):
  function _compute_softmax (line 1035) | def _compute_softmax(scores):
  class FeatureWriter (line 1058) | class FeatureWriter(object):
    method __init__ (line 1061) | def __init__(self, filename, is_training):
    method process_feature (line 1067) | def process_feature(self, feature):
    method close (line 1093) | def close(self):
  function validate_flags_or_throw (line 1097) | def validate_flags_or_throw(bert_config):
  function main (line 1126) | def main(_):

FILE: bert/tokenization.py
  function validate_case_matches_checkpoint (line 28) | def validate_case_matches_checkpoint(do_lower_case, init_checkpoint):
  function convert_to_unicode (line 78) | def convert_to_unicode(text):
  function printable_text (line 98) | def printable_text(text):
  function load_vocab (line 121) | def load_vocab(vocab_file):
  function convert_by_vocab (line 136) | def convert_by_vocab(vocab, items):
  function convert_tokens_to_ids (line 144) | def convert_tokens_to_ids(vocab, tokens):
  function convert_ids_to_tokens (line 148) | def convert_ids_to_tokens(inv_vocab, ids):
  function whitespace_tokenize (line 152) | def whitespace_tokenize(text):
  class FullTokenizer (line 161) | class FullTokenizer(object):
    method __init__ (line 164) | def __init__(self, vocab_file, do_lower_case=True):
    method tokenize (line 170) | def tokenize(self, text):
    method convert_tokens_to_ids (line 178) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 181) | def convert_ids_to_tokens(self, ids):
  class BasicTokenizer (line 185) | class BasicTokenizer(object):
    method __init__ (line 188) | def __init__(self, do_lower_case=True):
    method tokenize (line 196) | def tokenize(self, text):
    method _run_strip_accents (line 220) | def _run_strip_accents(self, text):
    method _run_split_on_punc (line 231) | def _run_split_on_punc(self, text):
    method _tokenize_chinese_chars (line 251) | def _tokenize_chinese_chars(self, text):
    method _is_chinese_char (line 264) | def _is_chinese_char(self, cp):
    method _clean_text (line 286) | def _clean_text(self, text):
  class WordpieceTokenizer (line 300) | class WordpieceTokenizer(object):
    method __init__ (line 303) | def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=...
    method tokenize (line 308) | def tokenize(self, text):
  function _is_whitespace (line 362) | def _is_whitespace(char):
  function _is_control (line 374) | def _is_control(char):
  function _is_punctuation (line 386) | def _is_punctuation(char):

FILE: bert/tokenization_test.py
  class TokenizationTest (line 26) | class TokenizationTest(tf.test.TestCase):
    method test_full_tokenizer (line 28) | def test_full_tokenizer(self):
    method test_chinese (line 51) | def test_chinese(self):
    method test_basic_tokenizer_lower (line 58) | def test_basic_tokenizer_lower(self):
    method test_basic_tokenizer_no_lower (line 66) | def test_basic_tokenizer_no_lower(self):
    method test_wordpiece_tokenizer (line 73) | def test_wordpiece_tokenizer(self):
    method test_convert_tokens_to_ids (line 93) | def test_convert_tokens_to_ids(self):
    method test_is_whitespace (line 107) | def test_is_whitespace(self):
    method test_is_control (line 117) | def test_is_control(self):
    method test_is_punctuation (line 126) | def test_is_punctuation(self):

FILE: createPretrainData.py
  class TrainingInstance (line 78) | class TrainingInstance(object):
    method __init__ (line 81) | def __init__(self, tokens, segment_ids, masked_lm_positions, masked_lm...
    method __str__ (line 89) | def __str__(self):
    method __repr__ (line 102) | def __repr__(self):
  function write_instance_to_example_files (line 106) | def write_instance_to_example_files(instances, tokenizer, max_seq_length,
  function create_int_feature (line 179) | def create_int_feature(values):
  function create_float_feature (line 184) | def create_float_feature(values):
  function create_training_instances (line 189) | def create_training_instances(input_files, tokenizer, max_seq_length,
  function create_instances_from_document (line 233) | def create_instances_from_document(
  function create_masked_lm_predictions (line 352) | def create_masked_lm_predictions(tokens, masked_lm_prob,
  function truncate_seq_pair (line 405) | def truncate_seq_pair(tokens_a, tokens_b, max_num_tokens, rng):
  function main (line 423) | def main(_):

FILE: evaluation.py
  function readThreshold (line 14) | def readThreshold(fname):
  function add_ (line 20) | def add_(arr1, arr2):
  function re_match (line 26) | def re_match(text, feature):
  function getMatch (line 34) | def getMatch(feature, sentences, model):
  function load_file (line 42) | def load_file(filename):

FILE: genPretrainData.py
  function getSentences (line 3) | def getSentences(filename):
  function work (line 15) | def work(task):

FILE: run_pretrain.py
  function model_fn_builder (line 119) | def model_fn_builder(bert_config, init_checkpoint, learning_rate,
  function get_masked_lm_output (line 250) | def get_masked_lm_output(bert_config, input_tensor, output_weights, posi...
  function get_next_sentence_output (line 295) | def get_next_sentence_output(bert_config, input_tensor, labels):
  function gather_indexes (line 318) | def gather_indexes(sequence_tensor, positions):
  function input_fn_builder (line 334) | def input_fn_builder(input_files,
  function _decode_record (line 401) | def _decode_record(record, name_to_features):
  function main (line 416) | def main(_):

FILE: search_threshold.py
  function getLab (line 14) | def getLab(probs, id2label, threshold):
  function getPreLab (line 21) | def getPreLab(array, id2label, threshold):
  function load_file (line 27) | def load_file(filename):
  function searchThreshold (line 39) | def searchThreshold(domain, model_pb, threshold_dir,

FILE: train.py
  function getNumClasses (line 171) | def getNumClasses():
  class InputExample (line 181) | class InputExample(object):
    method __init__ (line 184) | def __init__(self, guid, text_a, text_b=None, label=None):
  class PaddingInputExample (line 202) | class PaddingInputExample(object):
  class InputFeatures (line 215) | class InputFeatures(object):
    method __init__ (line 218) | def __init__(self,
  class DataProcessor (line 231) | class DataProcessor(object):
    method get_train_examples (line 234) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 238) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 242) | def get_test_examples(self, data_dir):
    method get_labels (line 246) | def get_labels(self):
    method _read_json (line 251) | def _read_json(cls, input_file):
  class MultilabelClassfier (line 265) | class MultilabelClassfier(DataProcessor):
    method get_train_examples (line 268) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 274) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 279) | def get_test_examples(self, data_dir):
    method get_labels (line 284) | def get_labels(self):
    method _create_examples (line 295) | def _create_examples(self, lines, set_type):
  function convert_single_example (line 311) | def convert_single_example(ex_index, example, label_list, max_seq_length,
  function file_based_convert_examples_to_features (line 420) | def file_based_convert_examples_to_features(
  function file_based_input_fn_builder (line 454) | def file_based_input_fn_builder(input_file, seq_length, is_training,
  function _truncate_seq_pair (line 502) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function create_model_original (line 519) | def create_model_original(bert_config, is_training, input_ids, input_mas...
  function focal_loss (line 563) | def focal_loss(prediction_tensor, target_tensor, alpha=FLAGS.alpha, gamm...
  function create_model (line 594) | def create_model(bert_config, is_training, input_ids, input_mask, segmen...
  function model_fn_builder (line 632) | def model_fn_builder(bert_config, num_labels, init_checkpoint, learning_...
  function input_fn_builder (line 738) | def input_fn_builder(features, seq_length, is_training, drop_remainder):
  function convert_examples_to_features (line 792) | def convert_examples_to_features(examples, label_list, max_seq_length,
  function main (line 808) | def main(_):

FILE: utils/ckpt2pb.py
  function create_model (line 13) | def create_model(bert_config, input_ids, input_mask, segment_ids,
  function convert (line 57) | def convert(task, tagDir, originDir, convertDir, model_type, bert_dir):

FILE: utils/evaluate.py
  class Judger (line 6) | class Judger:
    method __init__ (line 8) | def __init__(self, tag_path):
    method format_result (line 19) | def format_result(result):
    method gen_new_result (line 30) | def gen_new_result(self, result, truth, label):
    method get_value (line 59) | def get_value(res):
    method gen_score (line 77) | def gen_score(self, arr):
    method test (line 97) | def test(self, truth_label, pre_label):
  function evaluate (line 108) | def evaluate(predict_labels, target_labels, tag_dir):

FILE: utils/models.py
  class RCNN (line 3) | class RCNN():
    method __init__ (line 4) | def __init__(self, embedding, context_dim, hidden_dim, dropout_keep_pr...
    method getLogits (line 40) | def getLogits(self):
  class RCNNATT (line 43) | class RCNNATT():
    method __init__ (line 44) | def __init__(self, embedding, context_dim, hidden_dim, dropout_keep_pr...
    method getLogits (line 91) | def getLogits(self):

FILE: utils/predict.py
  class InputFeatures (line 14) | class InputFeatures(object):
    method __init__ (line 16) | def __init__(self,
  function convert_single_example (line 28) | def convert_single_example(sent, label_list, max_seq_length,
  class BERTModel (line 74) | class BERTModel:
    method __init__ (line 76) | def __init__(self, task, pb_model, tagDir, threshold, vocab_file):
    method convert (line 122) | def convert(self, line):
    method getAllResult (line 130) | def getAllResult(self, sentences):
    method rematch (line 142) | def rematch(self, arrays):
    method predict (line 153) | def predict(self, sentences):
    method getProb (line 189) | def getProb(self, sentences):
    method getProbs (line 208) | def getProbs(self, sentences):