SYMBOL INDEX (440 symbols across 22 files)

FILE: bert_utils.py
  function get_shape_list (line 13) | def get_shape_list(tensor, expected_rank=None, name=None):
  function reshape_to_matrix (line 49) | def reshape_to_matrix(input_tensor):
  function reshape_from_matrix (line 62) | def reshape_from_matrix(output_tensor, orig_shape_list):
  function assert_rank (line 74) | def assert_rank(tensor, expected_rank, name=None):
  function gather_indexes (line 103) | def gather_indexes(sequence_tensor, positions):
  function generate_seq2seq_mask (line 122) | def generate_seq2seq_mask(attention_mask, mask_sequence, seq_type, **kar...

FILE: classifier_utils.py
  function convert_to_unicode (line 36) | def convert_to_unicode(text):
  class InputExample (line 56) | class InputExample(object):
    method __init__ (line 59) | def __init__(self, guid, text_a, text_b=None, label=None):
  class PaddingInputExample (line 76) | class PaddingInputExample(object):
  class DataProcessor (line 87) | class DataProcessor(object):
    method get_train_examples (line 90) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 94) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 98) | def get_test_examples(self, data_dir):
    method get_labels (line 102) | def get_labels(self):
    method _read_tsv (line 107) | def _read_tsv(cls, input_file, delimiter="\t", quotechar=None):
    method _read_txt (line 117) | def _read_txt(cls, input_file):
    method _read_json (line 127) | def _read_json(cls, input_file):
  class XnliProcessor (line 137) | class XnliProcessor(DataProcessor):
    method get_train_examples (line 140) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 145) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 150) | def get_test_examples(self, data_dir):
    method _create_examples (line 155) | def _create_examples(self, lines, set_type):
    method get_labels (line 167) | def get_labels(self):
  class TnewsProcessor (line 214) | class TnewsProcessor(DataProcessor):
    method get_train_examples (line 217) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 222) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 227) | def get_test_examples(self, data_dir):
    method get_labels (line 232) | def get_labels(self):
    method _create_examples (line 241) | def _create_examples(self, lines, set_type):
  class iFLYTEKDataProcessor (line 294) | class iFLYTEKDataProcessor(DataProcessor):
    method get_train_examples (line 297) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 302) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 307) | def get_test_examples(self, data_dir):
    method get_labels (line 312) | def get_labels(self):
    method _create_examples (line 319) | def _create_examples(self, lines, set_type):
  class AFQMCProcessor (line 332) | class AFQMCProcessor(DataProcessor):
    method get_train_examples (line 335) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 340) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 345) | def get_test_examples(self, data_dir):
    method get_labels (line 350) | def get_labels(self):
    method _create_examples (line 354) | def _create_examples(self, lines, set_type):
  class CMNLIProcessor (line 367) | class CMNLIProcessor(DataProcessor):
    method get_train_examples (line 370) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 374) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 378) | def get_test_examples(self, data_dir):
    method get_labels (line 382) | def get_labels(self):
    method _create_examples_json (line 386) | def _create_examples_json(self, file_name, set_type):
  class CslProcessor (line 405) | class CslProcessor(DataProcessor):
    method get_train_examples (line 408) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 413) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 418) | def get_test_examples(self, data_dir):
    method get_labels (line 423) | def get_labels(self):
    method _create_examples (line 427) | def _create_examples(self, lines, set_type):
  class WSCProcessor (line 779) | class WSCProcessor(DataProcessor):
    method get_train_examples (line 782) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 787) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 792) | def get_test_examples(self, data_dir):
    method get_labels (line 797) | def get_labels(self):
    method _create_examples (line 801) | def _create_examples(self, lines, set_type):
  class COPAProcessor (line 841) | class COPAProcessor(DataProcessor):
    method __init__ (line 844) | def __init__(self):
    method get_train_examples (line 847) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 853) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 858) | def get_test_examples(self, data_dir):
    method get_labels (line 863) | def get_labels(self):
    method _create_examples_one (line 868) | def _create_examples_one(self, lines, set_type):
    method _create_examples (line 887) | def _create_examples(self, lines, set_type):

FILE: create_pretraining_data.py
  class TrainingInstance (line 71) | class TrainingInstance(object):
    method __init__ (line 74) | def __init__(self, tokens, segment_ids, masked_lm_positions, masked_lm...
    method __str__ (line 82) | def __str__(self):
    method __repr__ (line 95) | def __repr__(self):
  function write_instance_to_example_files (line 99) | def write_instance_to_example_files(instances, tokenizer, max_seq_length,
  function create_int_feature (line 172) | def create_int_feature(values):
  function create_float_feature (line 177) | def create_float_feature(values):
  function create_training_instances (line 182) | def create_training_instances(input_files, tokenizer, max_seq_length,
  function get_new_segment (line 227) | def get_new_segment(segment):  # 新增的方法 ####
  function create_instances_from_document_albert (line 260) | def create_instances_from_document_albert(
  function create_instances_from_document_original (line 372) | def create_instances_from_document_original( # THIS IS ORIGINAL BERT STY...
  function create_masked_lm_predictions (line 498) | def create_masked_lm_predictions(tokens, masked_lm_prob,
  function create_masked_lm_predictions_original (line 581) | def create_masked_lm_predictions_original(tokens, masked_lm_prob,
  function truncate_seq_pair (line 657) | def truncate_seq_pair(tokens_a, tokens_b, max_num_tokens, rng):
  function main (line 675) | def main(_):

FILE: create_pretraining_data_google.py
  class TrainingInstance (line 97) | class TrainingInstance(object):
    method __init__ (line 100) | def __init__(self, tokens, segment_ids, masked_lm_positions, masked_lm...
    method __str__ (line 109) | def __str__(self):
    method __repr__ (line 124) | def __repr__(self):
  function write_instance_to_example_files (line 128) | def write_instance_to_example_files(instances, tokenizer, max_seq_length,
  function create_int_feature (line 209) | def create_int_feature(values):
  function create_float_feature (line 214) | def create_float_feature(values):
  function create_training_instances (line 219) | def create_training_instances(input_files, tokenizer, max_seq_length,
  function create_instances_from_document (line 268) | def create_instances_from_document(
  function _is_start_piece_sp (line 395) | def _is_start_piece_sp(piece):
  function _is_start_piece_bert (line 412) | def _is_start_piece_bert(piece):
  function is_start_piece (line 421) | def is_start_piece(piece):
  function create_masked_lm_predictions (line 428) | def create_masked_lm_predictions(tokens, masked_lm_prob,
  function truncate_seq_pair (line 603) | def truncate_seq_pair(tokens_a, tokens_b, max_num_tokens, rng):
  function main (line 621) | def main(_):

FILE: lamb_optimizer_google.py
  class LAMBOptimizer (line 34) | class LAMBOptimizer(tf.train.Optimizer):
    method __init__ (line 42) | def __init__(self,
    method apply_gradients (line 68) | def apply_gradients(self, grads_and_vars, global_step=None, name=None):
    method _do_use_weight_decay (line 126) | def _do_use_weight_decay(self, param_name):
    method _do_layer_adaptation (line 136) | def _do_layer_adaptation(self, param_name):
    method _get_variable_name (line 144) | def _get_variable_name(self, param_name):

FILE: 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 254) | def get_pooled_output(self):
    method get_sequence_output (line 257) | def get_sequence_output(self):
    method get_all_encoder_layers (line 266) | def get_all_encoder_layers(self):
    method get_embedding_output (line 269) | def get_embedding_output(self):
    method get_embedding_table (line 280) | def get_embedding_table(self):
    method get_embedding_table_2 (line 283) | def get_embedding_table_2(self):
  function gelu (line 286) | def gelu(x):
  function get_activation (line 302) | def get_activation(activation_string):
  function get_assignment_map_from_checkpoint (line 339) | def get_assignment_map_from_checkpoint(tvars, init_checkpoint):
  function dropout (line 366) | def dropout(input_tensor, dropout_prob):
  function layer_norm (line 384) | def layer_norm(input_tensor, name=None):
  function layer_norm_and_dropout (line 390) | def layer_norm_and_dropout(input_tensor, dropout_prob, name=None):
  function create_initializer (line 397) | def create_initializer(initializer_range=0.02):
  function embedding_lookup (line 402) | def embedding_lookup(input_ids,
  function embedding_lookup_factorized (line 448) | def embedding_lookup_factorized(input_ids, # Factorized embedding parame...
  function embedding_postprocessor (line 507) | def embedding_postprocessor(input_tensor,
  function create_attention_mask_from_input_mask (line 603) | def create_attention_mask_from_input_mask(from_tensor, to_mask):
  function attention_layer (line 637) | def attention_layer(from_tensor,
  function transformer_model (line 833) | def transformer_model(input_tensor,
  function get_shape_list (line 981) | def get_shape_list(tensor, expected_rank=None, name=None):
  function reshape_to_matrix (line 1018) | def reshape_to_matrix(input_tensor):
  function reshape_from_matrix (line 1032) | def reshape_from_matrix(output_tensor, orig_shape_list):
  function assert_rank (line 1045) | def assert_rank(tensor, expected_rank, name=None):
  function prelln_transformer_model (line 1074) | def prelln_transformer_model(input_tensor,

FILE: modeling_google.py
  class AlbertConfig (line 36) | class AlbertConfig(object):
    method __init__ (line 41) | def __init__(self,
    method from_dict (line 102) | def from_dict(cls, json_object):
    method from_json_file (line 110) | def from_json_file(cls, json_file):
    method to_dict (line 116) | def to_dict(self):
    method to_json_string (line 121) | def to_json_string(self):
  class AlbertModel (line 126) | class AlbertModel(object):
    method __init__ (line 145) | def __init__(self,
    method get_pooled_output (line 244) | def get_pooled_output(self):
    method get_sequence_output (line 247) | def get_sequence_output(self):
    method get_all_encoder_layers (line 255) | def get_all_encoder_layers(self):
    method get_word_embedding_output (line 258) | def get_word_embedding_output(self):
    method get_embedding_output (line 268) | def get_embedding_output(self):
    method get_embedding_table (line 278) | def get_embedding_table(self):
  function gelu (line 282) | def gelu(x):
  function get_activation (line 296) | def get_activation(activation_string):
  function get_assignment_map_from_checkpoint (line 330) | def get_assignment_map_from_checkpoint(tvars, init_checkpoint, num_of_gr...
  function dropout (line 389) | def dropout(input_tensor, dropout_prob):
  function layer_norm (line 405) | def layer_norm(input_tensor, name=None):
  function layer_norm_and_dropout (line 411) | def layer_norm_and_dropout(input_tensor, dropout_prob, name=None):
  function create_initializer (line 418) | def create_initializer(initializer_range=0.02):
  function get_timing_signal_1d_given_position (line 423) | def get_timing_signal_1d_given_position(channels,
  function embedding_lookup (line 453) | def embedding_lookup(input_ids,
  function embedding_postprocessor (line 499) | def embedding_postprocessor(input_tensor,
  function dense_layer_3d (line 592) | def dense_layer_3d(input_tensor,
  function dense_layer_3d_proj (line 632) | def dense_layer_3d_proj(input_tensor,
  function dense_layer_2d (line 669) | def dense_layer_2d(input_tensor,
  function dot_product_attention (line 704) | def dot_product_attention(q, k, v, bias, dropout_rate=0.0):
  function attention_layer (line 748) | def attention_layer(from_tensor,
  function attention_ffn_block (line 837) | def attention_ffn_block(layer_input,
  function transformer_model (line 913) | def transformer_model(input_tensor,
  function get_shape_list (line 997) | def get_shape_list(tensor, expected_rank=None, name=None):
  function reshape_to_matrix (line 1032) | def reshape_to_matrix(input_tensor):
  function reshape_from_matrix (line 1046) | def reshape_from_matrix(output_tensor, orig_shape_list):
  function assert_rank (line 1059) | def assert_rank(tensor, expected_rank, name=None):

FILE: modeling_google_fast.py
  class AlbertConfig (line 36) | class AlbertConfig(object):
    method __init__ (line 41) | def __init__(self,
    method from_dict (line 102) | def from_dict(cls, json_object):
    method from_json_file (line 110) | def from_json_file(cls, json_file):
    method to_dict (line 116) | def to_dict(self):
    method to_json_string (line 121) | def to_json_string(self):
  class AlbertModel (line 126) | class AlbertModel(object):
    method __init__ (line 145) | def __init__(self,
    method get_pooled_output (line 244) | def get_pooled_output(self):
    method get_sequence_output (line 247) | def get_sequence_output(self):
    method get_all_encoder_layers (line 255) | def get_all_encoder_layers(self):
    method get_word_embedding_output (line 258) | def get_word_embedding_output(self):
    method get_embedding_output (line 268) | def get_embedding_output(self):
    method get_embedding_table (line 278) | def get_embedding_table(self):
  function gelu (line 282) | def gelu(x):
  function get_activation (line 296) | def get_activation(activation_string):
  function get_assignment_map_from_checkpoint (line 332) | def get_assignment_map_from_checkpoint(tvars, init_checkpoint, num_of_gr...
  function dropout (line 391) | def dropout(input_tensor, dropout_prob):
  function layer_norm (line 407) | def layer_norm(input_tensor, name=None):
  function layer_norm_and_dropout (line 413) | def layer_norm_and_dropout(input_tensor, dropout_prob, name=None):
  function create_initializer (line 420) | def create_initializer(initializer_range=0.02):
  function get_timing_signal_1d_given_position (line 425) | def get_timing_signal_1d_given_position(channels,
  function embedding_lookup (line 455) | def embedding_lookup(input_ids,
  function embedding_postprocessor (line 501) | def embedding_postprocessor(input_tensor,
  function dense_layer_3d (line 594) | def dense_layer_3d(input_tensor,
  function dense_layer_3d_proj (line 634) | def dense_layer_3d_proj(input_tensor,
  function dense_layer_2d (line 670) | def dense_layer_2d(input_tensor,
  function dense_layer_2d_old (line 721) | def dense_layer_2d_old(input_tensor,
  function dot_product_attention (line 789) | def dot_product_attention(q, k, v, bias, dropout_rate=0.0):
  function attention_layer (line 833) | def attention_layer(from_tensor,
  function attention_ffn_block (line 922) | def attention_ffn_block(layer_input,
  function transformer_model (line 1000) | def transformer_model(input_tensor,
  function get_shape_list (line 1084) | def get_shape_list(tensor, expected_rank=None, name=None):
  function reshape_to_matrix (line 1119) | def reshape_to_matrix(input_tensor):
  function reshape_from_matrix (line 1133) | def reshape_from_matrix(output_tensor, orig_shape_list):
  function assert_rank (line 1146) | def assert_rank(tensor, expected_rank, name=None):

FILE: 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):
  class LAMBOptimizer (line 178) | class LAMBOptimizer(tf.train.Optimizer):
    method __init__ (line 195) | def __init__(self,
    method apply_gradients (line 213) | def apply_gradients(self, grads_and_vars, global_step=None, name=None):
    method _do_use_weight_decay (line 285) | def _do_use_weight_decay(self, param_name):
    method _get_variable_name (line 295) | def _get_variable_name(self, param_name):

FILE: optimization_finetuning.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: optimization_google.py
  function create_optimizer (line 32) | def create_optimizer(loss, init_lr, num_train_steps, num_warmup_steps, u...
  class AdamWeightDecayOptimizer (line 118) | class AdamWeightDecayOptimizer(tf.train.Optimizer):
    method __init__ (line 121) | def __init__(self,
    method apply_gradients (line 139) | def apply_gradients(self, grads_and_vars, global_step=None, name=None):
    method _do_use_weight_decay (line 190) | def _do_use_weight_decay(self, param_name):
    method _get_variable_name (line 200) | def _get_variable_name(self, param_name):

FILE: resources/create_pretraining_data_roberta.py
  class TrainingInstance (line 70) | class TrainingInstance(object):
    method __init__ (line 73) | def __init__(self, tokens, segment_ids, masked_lm_positions, masked_lm...
    method __str__ (line 81) | def __str__(self):
    method __repr__ (line 94) | def __repr__(self):
  function write_instance_to_example_files (line 98) | def write_instance_to_example_files(instances, tokenizer, max_seq_length,
  function create_int_feature (line 172) | def create_int_feature(values):
  function create_float_feature (line 177) | def create_float_feature(values):
  function create_training_instances (line 182) | def create_training_instances(input_files, tokenizer, max_seq_length,
  function _is_chinese_char (line 229) | def _is_chinese_char(cp):
  function get_new_segment (line 250) | def get_new_segment(segment): #  新增的方法 ####
  function get_raw_instance (line 282) | def get_raw_instance(document,max_sequence_length): # 新增的方法 TODO need ch...
  function create_instances_from_document (line 319) | def create_instances_from_document( # 新增的方法
  function create_instances_from_document_original (line 376) | def create_instances_from_document_original(
  function create_masked_lm_predictions (line 501) | def create_masked_lm_predictions(tokens, masked_lm_prob,
  function truncate_seq_pair (line 579) | def truncate_seq_pair(tokens_a, tokens_b, max_num_tokens, rng):
  function main (line 597) | def main(_):

FILE: run_classifier.py
  class InputExample (line 128) | class InputExample(object):
    method __init__ (line 131) | def __init__(self, guid, text_a, text_b=None, label=None):
  class PaddingInputExample (line 148) | class PaddingInputExample(object):
  class InputFeatures (line 159) | class InputFeatures(object):
    method __init__ (line 162) | def __init__(self,
  class DataProcessor (line 175) | class DataProcessor(object):
    method get_train_examples (line 178) | 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 186) | def get_test_examples(self, data_dir):
    method get_labels (line 190) | def get_labels(self):
    method _read_tsv (line 195) | def _read_tsv(cls, input_file, quotechar=None):
  function convert_single_example (line 204) | def convert_single_example(ex_index, example, label_list, max_seq_length,
  function file_based_convert_examples_to_features (line 306) | def file_based_convert_examples_to_features(
  function file_based_input_fn_builder (line 336) | def file_based_input_fn_builder(input_file, seq_length, is_training,
  function _truncate_seq_pair (line 384) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function create_model (line 401) | def create_model(bert_config, is_training, input_ids, input_mask, segmen...
  function layer_norm (line 460) | def layer_norm(input_tensor, name=None):
  function model_fn_builder (line 465) | def model_fn_builder(bert_config, num_labels, init_checkpoint, learning_...
  function input_fn_builder (line 559) | def input_fn_builder(features, seq_length, is_training, drop_remainder):
  class LCQMCPairClassificationProcessor (line 610) | class LCQMCPairClassificationProcessor(DataProcessor): # TODO NEED CHANGE2
    method __init__ (line 612) | def __init__(self):
    method get_train_examples (line 615) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 621) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 626) | def get_test_examples(self, data_dir):
    method get_labels (line 631) | def get_labels(self):
    method _create_examples (line 636) | def _create_examples(self, lines, set_type):
  class SentencePairClassificationProcessor (line 655) | class SentencePairClassificationProcessor(DataProcessor):
    method __init__ (line 657) | def __init__(self):
    method get_train_examples (line 660) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 666) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 671) | def get_test_examples(self, data_dir):
    method get_labels (line 676) | def get_labels(self):
    method _create_examples (line 681) | def _create_examples(self, lines, set_type):
  function convert_examples_to_features (line 702) | def convert_examples_to_features(examples, label_list, max_seq_length,
  function main (line 718) | def main(_):

FILE: run_classifier_clue.py
  class InputFeatures (line 134) | class InputFeatures(object):
    method __init__ (line 137) | def __init__(self,
  function convert_single_example_for_inews (line 150) | def convert_single_example_for_inews(ex_index, tokens_a, tokens_b, label...
  function convert_example_list_for_inews (line 234) | def convert_example_list_for_inews(ex_index, example, label_list, max_se...
  function file_based_convert_examples_to_features_for_inews (line 272) | def file_based_convert_examples_to_features_for_inews(
  function convert_single_example (line 305) | def convert_single_example(ex_index, example, label_list, max_seq_length,
  function file_based_convert_examples_to_features (line 407) | def file_based_convert_examples_to_features(
  function file_based_input_fn_builder (line 437) | def file_based_input_fn_builder(input_file, seq_length, is_training,
  function _truncate_seq_pair (line 485) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function create_model (line 502) | def create_model(bert_config, is_training, input_ids, input_mask, segmen...
  function layer_norm (line 563) | def layer_norm(input_tensor, name=None):
  function model_fn_builder (line 569) | def model_fn_builder(bert_config, num_labels, init_checkpoint, learning_...
  function input_fn_builder (line 663) | def input_fn_builder(features, seq_length, is_training, drop_remainder):
  function convert_examples_to_features (line 717) | def convert_examples_to_features(examples, label_list, max_seq_length,
  function main (line 733) | def main(_):

FILE: run_classifier_sp_google.py
  class InputExample (line 139) | class InputExample(object):
    method __init__ (line 142) | def __init__(self, guid, text_a, text_b=None, label=None):
  class PaddingInputExample (line 159) | class PaddingInputExample(object):
  class InputFeatures (line 170) | class InputFeatures(object):
    method __init__ (line 173) | def __init__(self,
  class DataProcessor (line 186) | class DataProcessor(object):
    method get_train_examples (line 189) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 193) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 197) | def get_test_examples(self, data_dir):
    method get_labels (line 201) | def get_labels(self):
    method _read_tsv (line 206) | def _read_tsv(cls, input_file, quotechar=None):
  class XnliProcessor (line 216) | class XnliProcessor(DataProcessor):
    method __init__ (line 219) | def __init__(self):
    method get_train_examples (line 222) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 241) | def get_dev_examples(self, data_dir):
    method get_labels (line 259) | def get_labels(self):
  class MnliProcessor (line 264) | class MnliProcessor(DataProcessor):
    method get_train_examples (line 267) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 272) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 278) | def get_test_examples(self, data_dir):
    method get_labels (line 283) | def get_labels(self):
    method _create_examples (line 287) | def _create_examples(self, lines, set_type):
  class LCQMCPairClassificationProcessor (line 306) | class LCQMCPairClassificationProcessor(DataProcessor):
    method __init__ (line 308) | def __init__(self):
    method get_train_examples (line 311) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 317) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 322) | def get_test_examples(self, data_dir):
    method get_labels (line 327) | def get_labels(self):
    method _create_examples (line 331) | def _create_examples(self, lines, set_type):
  class MrpcProcessor (line 349) | class MrpcProcessor(DataProcessor):
    method get_train_examples (line 352) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 357) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 362) | def get_test_examples(self, data_dir):
    method get_labels (line 367) | def get_labels(self):
    method _create_examples (line 371) | def _create_examples(self, lines, set_type):
  class ColaProcessor (line 390) | class ColaProcessor(DataProcessor):
    method get_train_examples (line 393) | def get_train_examples(self, data_dir):
    method get_dev_examples (line 398) | def get_dev_examples(self, data_dir):
    method get_test_examples (line 403) | def get_test_examples(self, data_dir):
    method get_labels (line 408) | def get_labels(self):
    method _create_examples (line 412) | def _create_examples(self, lines, set_type):
  function convert_single_example (line 434) | def convert_single_example(ex_index, example, label_list, max_seq_length,
  function file_based_convert_examples_to_features (line 536) | def file_based_convert_examples_to_features(
  function file_based_input_fn_builder (line 566) | def file_based_input_fn_builder(input_file, seq_length, is_training,
  function _truncate_seq_pair (line 614) | def _truncate_seq_pair(tokens_a, tokens_b, max_length):
  function create_model (line 631) | def create_model(albert_config, is_training, input_ids, input_mask, segm...
  function model_fn_builder (line 682) | def model_fn_builder(albert_config, num_labels, init_checkpoint, learnin...
  function input_fn_builder (line 777) | def input_fn_builder(features, seq_length, is_training, drop_remainder):
  function convert_examples_to_features (line 831) | def convert_examples_to_features(examples, label_list, max_seq_length,
  function main (line 847) | def main(_):

FILE: 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 241) | def get_masked_lm_output(bert_config, input_tensor, output_weights,proje...
  function get_next_sentence_output (line 290) | def get_next_sentence_output(bert_config, input_tensor, labels):
  function gather_indexes (line 313) | def gather_indexes(sequence_tensor, positions):
  function input_fn_builder (line 329) | def input_fn_builder(input_files,
  function _decode_record (line 396) | def _decode_record(record, name_to_features):
  function main (line 411) | def main(_):

FILE: run_pretraining_google.py
  function model_fn_builder (line 133) | def model_fn_builder(albert_config, init_checkpoint, learning_rate,
  function get_masked_lm_output (line 296) | def get_masked_lm_output(albert_config, input_tensor, output_weights, po...
  function get_sentence_order_output (line 342) | def get_sentence_order_output(albert_config, input_tensor, labels):
  function gather_indexes (line 366) | def gather_indexes(sequence_tensor, positions):
  function input_fn_builder (line 382) | def input_fn_builder(input_files,
  function _decode_record (line 456) | def _decode_record(record, name_to_features):
  function main (line 471) | def main(_):

FILE: run_pretraining_google_fast.py
  function model_fn_builder (line 133) | def model_fn_builder(albert_config, init_checkpoint, learning_rate,
  function get_masked_lm_output (line 296) | def get_masked_lm_output(albert_config, input_tensor, output_weights, po...
  function get_sentence_order_output (line 342) | def get_sentence_order_output(albert_config, input_tensor, labels):
  function gather_indexes (line 366) | def gather_indexes(sequence_tensor, positions):
  function input_fn_builder (line 382) | def input_fn_builder(input_files,
  function _decode_record (line 456) | def _decode_record(record, name_to_features):
  function main (line 471) | def main(_):

FILE: similarity.py
  class SimProcessor (line 18) | class SimProcessor(DataProcessor):
    method get_sentence_examples (line 19) | def get_sentence_examples(self, questions):
    method get_labels (line 29) | def get_labels(self):
  class BertSim (line 36) | class BertSim:
    method __init__ (line 37) | def __init__(self, batch_size=args.batch_size):
    method start_model (line 49) | def start_model(self):
    method model_fn_builder (line 53) | def model_fn_builder(self, bert_config, num_labels, init_checkpoint, l...
    method get_estimator (line 97) | def get_estimator(self):
    method predict_sentences (line 126) | def predict_sentences(self,sentences):
    method _truncate_seq_pair (line 132) | def _truncate_seq_pair(self, tokens_a, tokens_b, max_length):
    method convert_single_example (line 148) | def convert_single_example(self, ex_index, example, label_list, max_se...
  function input_fn_builder (line 241) | def input_fn_builder(bertSim,sentences):

FILE: test_changes.py
  function get_total_parameters (line 16) | def get_total_parameters():
  function test_factorized_embedding (line 35) | def test_factorized_embedding():
  function test_share_parameters (line 44) | def test_share_parameters():
  function test_sentence_order_prediction (line 64) | def test_sentence_order_prediction():

FILE: 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 146) | def convert_tokens_to_ids(vocab, tokens):
  function convert_ids_to_tokens (line 150) | def convert_ids_to_tokens(inv_vocab, ids):
  function whitespace_tokenize (line 154) | def whitespace_tokenize(text):
  class FullTokenizer (line 163) | class FullTokenizer(object):
    method __init__ (line 166) | def __init__(self, vocab_file, do_lower_case=True):
    method tokenize (line 172) | def tokenize(self, text):
    method convert_tokens_to_ids (line 180) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 183) | def convert_ids_to_tokens(self, ids):
  class BasicTokenizer (line 187) | class BasicTokenizer(object):
    method __init__ (line 190) | def __init__(self, do_lower_case=True):
    method tokenize (line 198) | def tokenize(self, text):
    method _run_strip_accents (line 222) | def _run_strip_accents(self, text):
    method _run_split_on_punc (line 233) | def _run_split_on_punc(self, text):
    method _tokenize_chinese_chars (line 253) | def _tokenize_chinese_chars(self, text):
    method _is_chinese_char (line 266) | def _is_chinese_char(self, cp):
    method _clean_text (line 288) | def _clean_text(self, text):
  class WordpieceTokenizer (line 302) | class WordpieceTokenizer(object):
    method __init__ (line 305) | def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=...
    method tokenize (line 310) | def tokenize(self, text):
  function _is_whitespace (line 364) | def _is_whitespace(char):
  function _is_control (line 376) | def _is_control(char):
  function _is_punctuation (line 388) | def _is_punctuation(char):

FILE: tokenization_google.py
  function validate_case_matches_checkpoint (line 35) | def validate_case_matches_checkpoint(do_lower_case, init_checkpoint):
  function preprocess_text (line 86) | def preprocess_text(inputs, remove_space=True, lower=False):
  function encode_pieces (line 106) | def encode_pieces(sp_model, text, return_unicode=True, sample=False):
  function encode_ids (line 144) | def encode_ids(sp_model, text, sample=False):
  function convert_to_unicode (line 150) | def convert_to_unicode(text):
  function printable_text (line 170) | def printable_text(text):
  function load_vocab (line 193) | def load_vocab(vocab_file):
  function convert_by_vocab (line 207) | def convert_by_vocab(vocab, items):
  function convert_tokens_to_ids (line 215) | def convert_tokens_to_ids(vocab, tokens):
  function convert_ids_to_tokens (line 219) | def convert_ids_to_tokens(inv_vocab, ids):
  function whitespace_tokenize (line 223) | def whitespace_tokenize(text):
  class FullTokenizer (line 232) | class FullTokenizer(object):
    method __init__ (line 235) | def __init__(self, vocab_file, do_lower_case=True, spm_model_file=None):
    method tokenize (line 255) | def tokenize(self, text):
    method convert_tokens_to_ids (line 266) | def convert_tokens_to_ids(self, tokens):
    method convert_ids_to_tokens (line 274) | def convert_ids_to_tokens(self, ids):
  class BasicTokenizer (line 282) | class BasicTokenizer(object):
    method __init__ (line 285) | def __init__(self, do_lower_case=True):
    method tokenize (line 293) | def tokenize(self, text):
    method _run_strip_accents (line 317) | def _run_strip_accents(self, text):
    method _run_split_on_punc (line 328) | def _run_split_on_punc(self, text):
    method _tokenize_chinese_chars (line 348) | def _tokenize_chinese_chars(self, text):
    method _is_chinese_char (line 361) | def _is_chinese_char(self, cp):
    method _clean_text (line 383) | def _clean_text(self, text):
  class WordpieceTokenizer (line 397) | class WordpieceTokenizer(object):
    method __init__ (line 400) | def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=...
    method tokenize (line 405) | def tokenize(self, text):
  function _is_whitespace (line 459) | def _is_whitespace(char):
  function _is_control (line 471) | def _is_control(char):
  function _is_punctuation (line 483) | def _is_punctuation(char):