SYMBOL INDEX (91 symbols across 9 files)

FILE: GRU.py
  class SRUCell (line 27) | class SRUCell(RNNCell):
    method __init__ (line 35) | def __init__(self, num_units, activation=None, is_training = True, reu...
    method output_size (line 41) | def output_size(self):
    method state_size (line 45) | def state_size(self):
    method __call__ (line 48) | def __call__(self, inputs, state, scope=None):
  class GRUCell (line 69) | class GRUCell(RNNCell):
    method __init__ (line 72) | def __init__(self,
    method state_size (line 87) | def state_size(self):
    method output_size (line 91) | def output_size(self):
    method __call__ (line 94) | def __call__(self, inputs, state, scope = None):
  class gated_attention_Wrapper (line 121) | class gated_attention_Wrapper(RNNCell):
    method __init__ (line 122) | def __init__(self,
    method state_size (line 147) | def state_size(self):
    method output_size (line 151) | def output_size(self):
    method __call__ (line 154) | def __call__(self, inputs, state, scope = None):
  function linear (line 168) | def linear(args,

FILE: data_load.py
  function producer_func (line 17) | def producer_func(func):
  class _FuncQueueRunner (line 65) | class _FuncQueueRunner(tf.train.QueueRunner):
    method __init__ (line 67) | def __init__(self, func, queue=None, enqueue_ops=None, close_op=None,
    method _run (line 77) | def _run(self, sess, enqueue_op, coord=None):
  function load_data (line 115) | def load_data(dir_):
  function get_dev (line 171) | def get_dev():
  function get_batch (line 180) | def get_batch(is_training = True):

FILE: demo.py
  function home (line 18) | def home():
  function answer (line 24) | def answer():
  class Demo (line 38) | class Demo(object):
    method __init__ (line 39) | def __init__(self, model):
    method demo_backend (line 51) | def demo_backend(self, model, run_event):

FILE: evaluate.py
  function f1_and_EM (line 10) | def f1_and_EM(index, ground_truth, passage, dict_):
  function normalize_answer (line 27) | def normalize_answer(s):
  function f1_score (line 45) | def f1_score(prediction, ground_truth):
  function exact_match_score (line 58) | def exact_match_score(prediction, ground_truth):
  function metric_max_over_ground_truths (line 62) | def metric_max_over_ground_truths(metric_fn, prediction, ground_truths):
  function evaluate (line 70) | def evaluate(dataset, predictions):

FILE: layers.py
  function get_attn_params (line 23) | def get_attn_params(attn_size,initializer = tf.truncated_normal_initiali...
  function encoding (line 46) | def encoding(word, char, word_embeddings, char_embeddings, scope = "embe...
  function apply_dropout (line 52) | def apply_dropout(inputs, size = None, is_training = True):
  function bidirectional_GRU (line 69) | def bidirectional_GRU(inputs, inputs_len, cell = None, cell_fn = tf.cont...
  function pointer_net (line 105) | def pointer_net(passage, passage_len, question, question_len, cell, para...
  function attention_rnn (line 133) | def attention_rnn(inputs, inputs_len, units, attn_cell, bidirection = Tr...
  function question_pooling (line 148) | def question_pooling(memory, units, weights, memory_len = None, scope = ...
  function gated_attention (line 157) | def gated_attention(memory, inputs, states, units, params, self_matching...
  function mask_attn_score (line 171) | def mask_attn_score(score, memory_sequence_length, score_mask_value = -1...
  function attention (line 177) | def attention(inputs, units, weights, scope = "attention", memory_len = ...
  function cross_entropy (line 204) | def cross_entropy(output, target):
  function total_params (line 210) | def total_params():

FILE: model.py
  class Model (line 23) | class Model(object):
    method __init__ (line 24) | def __init__(self,is_training = True, demo = False):
    method encode_ids (line 83) | def encode_ids(self):
    method attention_match_rnn (line 135) | def attention_match_rnn(self):
    method bidirectional_readout (line 165) | def bidirectional_readout(self):
    method pointer_network (line 174) | def pointer_network(self):
    method outputs (line 180) | def outputs(self):
    method loss_function (line 190) | def loss_function(self):
    method summary (line 205) | def summary(self):
  function debug (line 220) | def debug():
  function test (line 224) | def test():
  function main (line 242) | def main():

FILE: params.py
  class Params (line 1) | class Params():

FILE: process.py
  function str2bool (line 20) | def str2bool(v):
  function tokenize_corenlp (line 36) | def tokenize_corenlp(text):
  class data_loader (line 41) | class data_loader(object):
    method __init__ (line 42) | def __init__(self,use_pretrained = None):
    method ind2word (line 61) | def ind2word(self,ids):
    method ind2char (line 67) | def ind2char(self,ids):
    method process_glove (line 75) | def process_glove(self, wordvecs, dict_, count, emb_size):
    method process_json (line 96) | def process_json(self,file_dir,out_dir, write_ = True):
    method loop (line 105) | def loop(self, data, dir_ = Params.train_dir, write_ = True):
    method process_word (line 133) | def process_word(self,line):
    method process_char (line 142) | def process_char(self,line):
    method add_to_dict (line 150) | def add_to_dict(self, line):
    method realtime_process (line 179) | def realtime_process(self, data):
  function load_glove (line 216) | def load_glove(dir_, name, vocab_size):
  function reduce_glove (line 247) | def reduce_glove(dir_, dict_):
  function find_answer_index (line 272) | def find_answer_index(context, answer):
  function normalize_text (line 290) | def normalize_text(text):
  function write_file (line 293) | def write_file(indices, dir_, separate = "\n"):
  function pad_data (line 297) | def pad_data(data, max_word):
  function pad_char_len (line 306) | def pad_char_len(data, max_word, max_char):
  function pad_char_data (line 315) | def pad_char_data(data, max_char, max_words):
  function get_char_line (line 328) | def get_char_line(line):
  function load_target (line 338) | def load_target(dir):
  function load_word (line 350) | def load_word(dir):
  function load_char (line 364) | def load_char(dir):
  function max_value (line 386) | def max_value(inputlist):
  function main (line 394) | def main():

FILE: zoneout.py
  class ZoneoutWrapper (line 12) | class ZoneoutWrapper(tf.nn.rnn_cell.RNNCell):
    method __init__ (line 15) | def __init__(self, cell, state_zoneout_prob, is_training=True, seed=No...
    method state_size (line 28) | def state_size(self):
    method output_size (line 32) | def output_size(self):
    method __call__ (line 35) | def __call__(self, inputs, state, scope=None):