SYMBOL INDEX (88 symbols across 12 files)

FILE: draw_plot.py
  function main (line 12) | def main():

FILE: kg_data/EntityMatcher.py
  class EntityMatcher (line 6) | class EntityMatcher:
    method __init__ (line 7) | def __init__(self, entity_file, sentences_folder, process_num):
    method match (line 20) | def match(self, file_name):
    method write_file (line 35) | def write_file(self, data):
    method run (line 39) | def run(self):

FILE: kg_data/SentenceSegment.py
  function read_txt (line 7) | def read_txt(file_name):
  class SentenceSegment (line 16) | class SentenceSegment:
    method __init__ (line 17) | def __init__(self, dict_file, stop_word_file, sentences_folder, proces...
    method segment (line 28) | def segment(self, file_name):
    method write_file (line 54) | def write_file(self, data):
    method run (line 58) | def run(self):

FILE: nrekit/data_loader.py
  class file_data_loader (line 9) | class file_data_loader:
    method __next__ (line 10) | def __next__(self):
    method next (line 13) | def next(self):
    method next_batch (line 16) | def next_batch(self, batch_size):
  class npy_data_loader (line 19) | class npy_data_loader(file_data_loader):
    method __iter__ (line 24) | def __iter__(self):
    method __init__ (line 27) | def __init__(self, data_dir, prefix, mode, word_vec_npy='vec.npy', shu...
    method __next__ (line 61) | def __next__(self):
    method next_batch (line 64) | def next_batch(self, batch_size):
  class json_file_data_loader (line 136) | class json_file_data_loader(file_data_loader):
    method _load_preprocessed_file (line 141) | def _load_preprocessed_file(self):
    method __init__ (line 185) | def __init__(self, file_name, word_vec_file_name, rel2id_file_name, mo...
    method __iter__ (line 436) | def __iter__(self):
    method __next__ (line 439) | def __next__(self):
    method next_batch (line 442) | def next_batch(self, batch_size):

FILE: nrekit/framework.py
  function average_gradients (line 8) | def average_gradients(tower_grads):
  class re_model (line 45) | class re_model:
    method __init__ (line 46) | def __init__(self, train_data_loader, batch_size, max_length=120):
    method loss (line 58) | def loss(self):
    method train_logit (line 61) | def train_logit(self):
    method test_logit (line 64) | def test_logit(self):
  class re_framework (line 67) | class re_framework:
    method __init__ (line 71) | def __init__(self, train_data_loader, test_data_loader, max_length=120...
    method one_step_multi_models (line 76) | def one_step_multi_models(self, sess, models, batch_data_gen, run_arra...
    method one_step (line 99) | def one_step(self, sess, model, batch_data, run_array):
    method train (line 114) | def train(self,
    method test (line 225) | def test(self,
    method __test_bag__ (line 237) | def __test_bag__(self, model, ckpt=None, return_result=False):

FILE: nrekit/network/classifier.py
  function softmax_cross_entropy (line 4) | def softmax_cross_entropy(x, label, rel_tot, weights_table=None, weights...
  function sigmoid_cross_entropy (line 13) | def sigmoid_cross_entropy(x, label, rel_tot, weights_table=None, var_sco...
  function soft_label_softmax_cross_entropy (line 26) | def soft_label_softmax_cross_entropy(x):
  function output (line 35) | def output(x):

FILE: nrekit/network/embedding.py
  function word_embedding (line 4) | def word_embedding(word, word_vec_mat, var_scope=None, word_embedding_di...
  function pos_embedding (line 15) | def pos_embedding(pos1, pos2, var_scope=None, pos_embedding_dim=5, max_l...
  function word_position_embedding (line 29) | def word_position_embedding(word, word_vec_mat, pos1, pos2, var_scope=No...

FILE: nrekit/network/encoder.py
  function __dropout__ (line 5) | def __dropout__(x, keep_prob=1.0):
  function __pooling__ (line 8) | def __pooling__(x):
  function __piecewise_pooling__ (line 11) | def __piecewise_pooling__(x, mask):
  function __cnn_cell__ (line 18) | def __cnn_cell__(x, hidden_size=230, kernel_size=3, stride_size=1):
  function cnn (line 27) | def cnn(x, hidden_size=230, kernel_size=3, stride_size=1, activation=tf....
  function pcnn (line 36) | def pcnn(x, mask, hidden_size=230, kernel_size=3, stride_size=1, activat...
  function __rnn_cell__ (line 45) | def __rnn_cell__(hidden_size, cell_name='lstm'):
  function rnn (line 57) | def rnn(x, length, hidden_size=230, cell_name='lstm', var_scope=None, ke...
  function birnn (line 66) | def birnn(x, length, hidden_size=230, cell_name='lstm', var_scope=None, ...

FILE: nrekit/network/selector.py
  function __dropout__ (line 4) | def __dropout__(x, keep_prob=1.0):
  function __logit__ (line 7) | def __logit__(x, rel_tot, var_scope=None):
  function __attention_train_logit__ (line 14) | def __attention_train_logit__(x, query, rel_tot, var_scope=None):
  function __attention_test_logit__ (line 22) | def __attention_test_logit__(x, rel_tot, var_scope=None):
  function instance (line 29) | def instance(x, rel_tot, var_scope=None, keep_prob=1.0):
  function bag_attention (line 34) | def bag_attention(x, scope, query, rel_tot, is_training, var_scope=None,...
  function bag_average (line 64) | def bag_average(x, scope, rel_tot, var_scope=None, dropout_before=False,...
  function bag_one (line 77) | def bag_one(x, scope, query, rel_tot, is_training, var_scope=None, dropo...
  function bag_cross_max (line 106) | def bag_cross_max(x, scope, rel_tot, var_scope=None, dropout_before=Fals...

FILE: nrekit/rl.py
  class policy_agent (line 11) | class policy_agent(framework.re_model):
    method __init__ (line 12) | def __init__(self, train_data_loader, batch_size, max_length=120):
    method loss (line 23) | def loss(self):
    method train_logit (line 26) | def train_logit(self):
    method test_logit (line 29) | def test_logit(self):
  class rl_re_framework (line 32) | class rl_re_framework(framework.re_framework):
    method __init__ (line 33) | def __init__(self, train_data_loader, test_data_loader, max_length=120...
    method agent_one_step (line 36) | def agent_one_step(self, sess, agent_model, batch_data, run_array, wei...
    method pretrain_main_model (line 50) | def pretrain_main_model(self, max_epoch):
    method pretrain_agent_model (line 80) | def pretrain_agent_model(self, max_epoch):
    method train (line 111) | def train(self,

FILE: test_demo.py
  class model (line 29) | class model(nrekit.framework.re_model):
    method __init__ (line 33) | def __init__(self, train_data_loader, batch_size, max_length=120):
    method loss (line 74) | def loss(self):
    method train_logit (line 77) | def train_logit(self):
    method test_logit (line 80) | def test_logit(self):
    method get_weights (line 83) | def get_weights(self):

FILE: train_demo.py
  class model (line 28) | class model(nrekit.framework.re_model):
    method __init__ (line 32) | def __init__(self, train_data_loader, batch_size, max_length=120):
    method loss (line 77) | def loss(self):
    method train_logit (line 80) | def train_logit(self):
    method test_logit (line 83) | def test_logit(self):
    method get_weights (line 86) | def get_weights(self):