SYMBOL INDEX (34 symbols across 3 files)

FILE: attention_gru_cell.py
  class AttentionGRUCell (line 26) | class AttentionGRUCell(RNNCell):
    method __init__ (line 35) | def __init__(self, num_units, input_size=None, activation=tanh):
    method state_size (line 42) | def state_size(self):
    method output_size (line 47) | def output_size(self):
    method __call__ (line 50) | def __call__(self, inputs, state, scope=None):
  function _linear (line 72) | def _linear(args, output_size, bias, bias_start=0.0):

FILE: babi_input.py
  function init_babi (line 13) | def init_babi(fname):
  function get_babi_raw (line 47) | def get_babi_raw(id, test_id):
  function load_glove (line 102) | def load_glove(dim):
  function create_vector (line 116) | def create_vector(word, word2vec, word_vector_size, silent=True):
  function process_word (line 124) | def process_word(word, word2vec, vocab, ivocab, word_vector_size, to_ret...
  function process_input (line 139) | def process_input(data_raw, floatX, word2vec, vocab, ivocab, embed_size,...
  function get_lens (line 201) | def get_lens(inputs, split_sentences=False):
  function get_sentence_lens (line 207) | def get_sentence_lens(inputs):
  function pad_inputs (line 221) | def pad_inputs(inputs, lens, max_len, mode="", sen_lens=None, max_sen_le...
  function create_embedding (line 242) | def create_embedding(word2vec, ivocab, embed_size):
  function load_babi (line 249) | def load_babi(config, split_sentences=False):

FILE: dmn_plus.py
  class Config (line 17) | class Config(object):
  function _add_gradient_noise (line 55) | def _add_gradient_noise(t, stddev=1e-3, name=None):
  function _position_encoding (line 65) | def _position_encoding(sentence_size, embedding_size):
  class DMN_PLUS (line 78) | class DMN_PLUS(object):
    method load_data (line 80) | def load_data(self, debug=False):
    method add_placeholders (line 88) | def add_placeholders(self):
    method get_predictions (line 100) | def get_predictions(self, output):
    method add_loss_op (line 105) | def add_loss_op(self, output):
    method add_training_op (line 118) | def add_training_op(self, loss):
    method get_question_representation (line 133) | def get_question_representation(self):
    method get_input_representation (line 146) | def get_input_representation(self):
    method get_attention (line 172) | def get_attention(self, q_vec, prev_memory, fact_vec, reuse):
    method generate_episode (line 195) | def generate_episode(self, memory, q_vec, fact_vecs, hop_index):
    method add_answer_module (line 221) | def add_answer_module(self, rnn_output, q_vec):
    method inference (line 232) | def inference(self):
    method run_epoch (line 275) | def run_epoch(self, session, data, num_epoch=0, train_writer=None, tra...
    method __init__ (line 326) | def __init__(self, config):