SYMBOL INDEX (109 symbols across 10 files)

FILE: cache_elmo.py
  function build_elmo (line 12) | def build_elmo():
  function cache_dataset (line 25) | def cache_dataset(data_path, session, token_ph, len_ph, lm_emb, out_file):

FILE: conll.py
  function get_doc_key (line 17) | def get_doc_key(doc_id, part):
  function output_conll (line 20) | def output_conll(input_file, output_file, predictions):
  function official_conll_eval (line 74) | def official_conll_eval(gold_path, predicted_path, metric, official_stdo...
  function evaluate_conll (line 94) | def evaluate_conll(gold_path, predictions, official_stdout=False):

FILE: continuous_evaluate.py
  function copy_checkpoint (line 15) | def copy_checkpoint(source, target):

FILE: coref_kernels.cc
  class ExtractSpansOp (line 18) | class ExtractSpansOp : public OpKernel {
    method ExtractSpansOp (line 20) | explicit ExtractSpansOp(OpKernelConstruction* context) : OpKernel(cont...
    method Compute (line 24) | void Compute(OpKernelContext* context) override {

FILE: coref_model.py
  class CorefModel (line 21) | class CorefModel(object):
    method __init__ (line 22) | def __init__(self, config):
    method start_enqueue_thread (line 73) | def start_enqueue_thread(self, session):
    method restore (line 87) | def restore(self, session):
    method load_lm_embeddings (line 96) | def load_lm_embeddings(self, doc_key):
    method tensorize_mentions (line 108) | def tensorize_mentions(self, mentions):
    method tensorize_span_labels (line 115) | def tensorize_span_labels(self, tuples, label_dict):
    method tensorize_example (line 122) | def tensorize_example(self, example, is_training):
    method truncate_example (line 170) | def truncate_example(self, tokens, context_word_emb, head_word_emb, lm...
    method get_candidate_labels (line 193) | def get_candidate_labels(self, candidate_starts, candidate_ends, label...
    method get_dropout (line 201) | def get_dropout(self, dropout_rate, is_training):
    method coarse_to_fine_pruning (line 204) | def coarse_to_fine_pruning(self, top_span_emb, top_span_mention_scores...
    method distance_pruning (line 219) | def distance_pruning(self, top_span_emb, top_span_mention_scores, c):
    method get_predictions_and_loss (line 230) | def get_predictions_and_loss(self, tokens, context_word_emb, head_word...
    method get_span_emb (line 352) | def get_span_emb(self, head_emb, context_outputs, span_starts, span_en...
    method get_mention_scores (line 385) | def get_mention_scores(self, span_emb):
    method softmax_loss (line 389) | def softmax_loss(self, antecedent_scores, antecedent_labels):
    method bucket_distance (line 395) | def bucket_distance(self, distances):
    method get_slow_antecedent_scores (line 405) | def get_slow_antecedent_scores(self, top_span_emb, top_antecedents, to...
    method get_fast_antecedent_scores (line 439) | def get_fast_antecedent_scores(self, top_span_emb):
    method flatten_emb_by_sentence (line 445) | def flatten_emb_by_sentence(self, emb, text_len_mask):
    method lstm_contextualize (line 458) | def lstm_contextualize(self, text_emb, text_len, text_len_mask):
    method get_predicted_antecedents (line 489) | def get_predicted_antecedents(self, antecedents, antecedent_scores):
    method get_predicted_clusters (line 498) | def get_predicted_clusters(self, top_span_starts, top_span_ends, predi...
    method evaluate_coref (line 522) | def evaluate_coref(self, top_span_starts, top_span_ends, predicted_ant...
    method load_eval_data (line 533) | def load_eval_data(self):
    method evaluate (line 543) | def evaluate(self, session, official_stdout=False):

FILE: demo.py
  function create_example (line 14) | def create_example(text):
  function print_predictions (line 25) | def print_predictions(example):
  function make_predictions (line 30) | def make_predictions(text, model):

FILE: get_char_vocab.py
  function get_char_vocab (line 9) | def get_char_vocab(input_filenames, output_filename):
  function get_char_vocab_language (line 24) | def get_char_vocab_language(language):

FILE: metrics.py
  function f1 (line 10) | def f1(p_num, p_den, r_num, r_den, beta=1):
  class CorefEvaluator (line 15) | class CorefEvaluator(object):
    method __init__ (line 16) | def __init__(self):
    method update (line 19) | def update(self, predicted, gold, mention_to_predicted, mention_to_gold):
    method get_f1 (line 23) | def get_f1(self):
    method get_recall (line 26) | def get_recall(self):
    method get_precision (line 29) | def get_precision(self):
    method get_prf (line 32) | def get_prf(self):
  class Evaluator (line 35) | class Evaluator(object):
    method __init__ (line 36) | def __init__(self, metric, beta=1):
    method update (line 44) | def update(self, predicted, gold, mention_to_predicted, mention_to_gold):
    method get_f1 (line 55) | def get_f1(self):
    method get_recall (line 58) | def get_recall(self):
    method get_precision (line 61) | def get_precision(self):
    method get_prf (line 64) | def get_prf(self):
    method get_counts (line 67) | def get_counts(self):
  function evaluate_documents (line 71) | def evaluate_documents(documents, metric, beta=1):
  function b_cubed (line 78) | def b_cubed(clusters, mention_to_gold):
  function muc (line 100) | def muc(clusters, mention_to_gold):
  function phi4 (line 115) | def phi4(c1, c2):
  function ceafe (line 119) | def ceafe(clusters, gold_clusters):
  function lea (line 130) | def lea(clusters, mention_to_gold):

FILE: minimize.py
  class DocumentState (line 16) | class DocumentState(object):
    method __init__ (line 17) | def __init__(self):
    method assert_empty (line 30) | def assert_empty(self):
    method assert_finalizable (line 43) | def assert_finalizable(self):
    method span_dict_to_list (line 54) | def span_dict_to_list(self, span_dict):
    method finalize (line 57) | def finalize(self):
  function normalize_word (line 86) | def normalize_word(word, language):
  function handle_bit (line 94) | def handle_bit(word_index, bit, stack, spans):
  function handle_line (line 125) | def handle_line(line, document_state, language, labels, stats):
  function minimize_partition (line 180) | def minimize_partition(name, language, extension, labels, stats):
  function minimize_language (line 197) | def minimize_language(language, labels, stats):

FILE: util.py
  function initialize_from_env (line 19) | def initialize_from_env():
  function copy_checkpoint (line 34) | def copy_checkpoint(source, target):
  function make_summary (line 38) | def make_summary(value_dict):
  function flatten (line 41) | def flatten(l):
  function set_gpus (line 44) | def set_gpus(*gpus):
  function mkdirs (line 48) | def mkdirs(path):
  function load_char_dict (line 56) | def load_char_dict(char_vocab_path):
  function maybe_divide (line 64) | def maybe_divide(x, y):
  function projection (line 67) | def projection(inputs, output_size, initializer=None):
  function highway (line 70) | def highway(inputs, num_layers, dropout):
  function shape (line 81) | def shape(x, dim):
  function ffnn (line 84) | def ffnn(inputs, num_hidden_layers, hidden_size, output_size, dropout, o...
  function cnn (line 113) | def cnn(inputs, filter_sizes, num_filters):
  function batch_gather (line 128) | def batch_gather(emb, indices):
  class RetrievalEvaluator (line 142) | class RetrievalEvaluator(object):
    method __init__ (line 143) | def __init__(self):
    method update (line 148) | def update(self, gold_set, predicted_set):
    method recall (line 153) | def recall(self):
    method precision (line 156) | def precision(self):
    method metrics (line 159) | def metrics(self):
  class EmbeddingDictionary (line 165) | class EmbeddingDictionary(object):
    method __init__ (line 166) | def __init__(self, info, normalize=True, maybe_cache=None):
    method size (line 177) | def size(self):
    method load_embedding_dict (line 180) | def load_embedding_dict(self, path):
    method __getitem__ (line 198) | def __getitem__(self, key):
    method normalize (line 204) | def normalize(self, v):
  class CustomLSTMCell (line 211) | class CustomLSTMCell(tf.contrib.rnn.RNNCell):
    method __init__ (line 212) | def __init__(self, num_units, batch_size, dropout):
    method state_size (line 222) | def state_size(self):
    method output_size (line 226) | def output_size(self):
    method initial_state (line 230) | def initial_state(self):
    method __call__ (line 233) | def __call__(self, inputs, state, scope=None):
    method _orthonormal_initializer (line 246) | def _orthonormal_initializer(self, scale=1.0):
    method _block_orthonormal_initializer (line 259) | def _block_orthonormal_initializer(self, output_sizes):