SYMBOL INDEX (127 symbols across 12 files)

FILE: cnn/tensorflow/insqa_cnn.py
  class InsQACNN (line 7) | class InsQACNN(object):
    method __init__ (line 8) | def __init__(self, _margin, sequence_length, batch_size,
    method conv (line 60) | def conv(self, tensor):
    method cosine (line 83) | def cosine(self, v1, v2):

FILE: cnn/tensorflow/insqa_train.py
  function train_step (line 116) | def train_step(q, qp, qn):
  function test_step (line 131) | def test_step():

FILE: cnn/tensorflow/insurance_qa_data_helpers.py
  function build_vocab (line 14) | def build_vocab():
  function rand_qa (line 37) | def rand_qa(qalist):
  function read_alist (line 41) | def read_alist():
  function vocab_plus_overlap (line 49) | def vocab_plus_overlap(vectors, sent, over, size):
  function load_vectors (line 74) | def load_vectors():
  function read_vector (line 86) | def read_vector(vectors, word):
  function load_test_and_vectors (line 94) | def load_test_and_vectors():
  function load_train_and_vectors (line 101) | def load_train_and_vectors():
  function load_data_val_10 (line 108) | def load_data_val_10(testList, vectors, index):
  function read_raw (line 118) | def read_raw():
  function encode_sent (line 126) | def encode_sent(vocab, string, size):
  function load_data_6 (line 136) | def load_data_6(vocab, alist, raw, size):
  function load_data_val_6 (line 148) | def load_data_val_6(testList, vocab, index, batch):
  function load_data_9 (line 162) | def load_data_9(trainList, vectors, size):
  function load_data_val_9 (line 179) | def load_data_val_9(testList, vectors, index):
  function load_data_10 (line 187) | def load_data_10(vectors, qalist, raw, size):
  function load_data_11 (line 198) | def load_data_11(vectors, qalist, raw, size):
  function batch_iter (line 209) | def batch_iter(data, batch_size, num_epochs, shuffle=True):

FILE: cnn/theano/insqa_cnn.py
  function build_vocab (line 23) | def build_vocab():
  function load_vectors (line 39) | def load_vectors():
  function load_word_embeddings (line 52) | def load_word_embeddings(vocab, dim):
  function encode_sent (line 66) | def encode_sent(vocab, string, size):
  function load_train_list (line 76) | def load_train_list():
  function load_test_list (line 83) | def load_test_list():
  function load_data (line 90) | def load_data(trainList, vocab, batch_size):
  function load_data_val (line 100) | def load_data_val(testList, vocab, index, batch_size):
  function validation (line 112) | def validation(validate_model, testList, vocab, batch_size):
  class QACnn (line 140) | class QACnn(object):
    method __init__ (line 141) | def __init__(self, input1, input2, input3, word_embeddings, batch_size...
    method _dropout (line 231) | def _dropout(self, rng, layer, keep_prob):
  function train (line 238) | def train():

FILE: gen.py
  function load_vocab (line 7) | def load_vocab():
  function ins_load_answers (line 18) | def ins_load_answers():
  function ins_w2v (line 29) | def ins_w2v():
  function ins_train (line 49) | def ins_train():
  function ins_test (line 65) | def ins_test():
  function ins_qa (line 83) | def ins_qa():
  function qur_prepare (line 88) | def qur_prepare():
  function qur_qa (line 124) | def qur_qa():

FILE: lstm_cnn/theano/insqa_lstm.py
  function build_vocab (line 25) | def build_vocab():
  function load_vectors (line 40) | def load_vectors():
  function load_word_embeddings (line 52) | def load_word_embeddings(vocab, dim):
  function encode_sent (line 66) | def encode_sent(vocab, string, size):
  function load_train_list (line 80) | def load_train_list():
  function load_test_list (line 88) | def load_test_list():
  function load_data (line 94) | def load_data(trainList, vocab, batch_size):
  function load_data_val (line 118) | def load_data_val(testList, vocab, index, batch_size):
  function validation (line 136) | def validation(validate_model, testList, vocab, batch_size):
  function ortho_weight (line 171) | def ortho_weight(ndim):
  function numpy_floatX (line 176) | def numpy_floatX(data):
  function param_init_cnn (line 179) | def param_init_cnn(filter_sizes, num_filters, proj_size, tparams, grad_p...
  function param_init_lstm (line 200) | def param_init_lstm(proj_size, tparams, grad_params):
  function dropout_layer (line 220) | def dropout_layer(state_before, use_noise, trng):
  class LSTM (line 229) | class LSTM(object):
    method __init__ (line 230) | def __init__(self, input1, input2, input3, mask1, mask2, mask3, word_e...
    method _cnn_net (line 271) | def _cnn_net(self, tparams, cnn_input, batch_size, sequence_len, num_f...
    method _lstm_net (line 286) | def _lstm_net(self, tparams, _input, sequence_len, batch_size, embeddi...
  function lstm_layer (line 298) | def lstm_layer(tparams, state_below, proj_size, prefix='lstm', mask=None):
  function _p (line 355) | def _p(pp, name):
  function train (line 358) | def train():

FILE: rnn_attention/tensorflow/insurance_qa_data_helpers.py
  function build_vocab (line 17) | def build_vocab():
  function read_alist (line 39) | def read_alist():
  function load_vectors (line 47) | def load_vectors():
  function read_vector (line 59) | def read_vector(vectors, word):
  function load_train_list (line 67) | def load_train_list():
  function load_test_list (line 75) | def load_test_list():
  function load_train_and_vectors (line 81) | def load_train_and_vectors():
  function read_raw (line 88) | def read_raw():
  function encode_sent (line 96) | def encode_sent(vocab, string, size):
  function load_val_data (line 106) | def load_val_data(test_list, vocab, index, batch_size, max_len):
  function load_train_data (line 124) | def load_train_data(trainList, vocab, batch_size, max_len):
  function evaluation (line 148) | def evaluation(score_list, test_list):

FILE: rnn_attention/tensorflow/tf_rnn_char.py
  class RNN_Model (line 11) | class RNN_Model(object):
    method _rnn_net (line 12) | def _rnn_net(self, inputs, mask, embedding, keep_prob, batch_size, emb...
    method _max_pooling (line 37) | def _max_pooling(self, lstm):
    method __init__ (line 44) | def __init__(self, config, is_training=True):
  function train_step (line 101) | def train_step(model, qlist, plist, nlist, mask_q, mask_p, mask_n):
  function dev_step (line 117) | def dev_step(model, vocab, batch_size, max_len):
  class Config (line 159) | class Config(object):

FILE: swem/swem_hier.py
  class SWEM_HIER (line 15) | class SWEM_HIER(object):
    method __init__ (line 16) | def __init__(self,
    method logloss (line 53) | def logloss(self, y, v_one, sim):
    method cosine (line 61) | def cosine(self, t1, t2):
  function get_constant (line 68) | def get_constant(batch_size):
  function train_step (line 104) | def train_step():
  function test_step (line 113) | def test_step():

FILE: swem/swem_hier_margin.py
  class SWEM_HIER (line 9) | class SWEM_HIER(object):
    method __init__ (line 10) | def __init__(self,
    method margin_loss (line 70) | def margin_loss(self, zero, margin, cos_q_qp, cos_q_qn):
    method logloss (line 75) | def logloss(self, y, v_one, sim):
    method cosine (line 83) | def cosine(self, t1, t2):
  function get_constant (line 90) | def get_constant(batch_size):
  function train_step (line 127) | def train_step():
  function test_step (line 136) | def test_step():

FILE: swem/swem_max_margin.py
  class SWEM_HIER (line 8) | class SWEM_HIER(object):
    method __init__ (line 9) | def __init__(self,
    method margin_loss (line 47) | def margin_loss(self, zero, margin, cos_q_qp, cos_q_qn):
    method logloss (line 52) | def logloss(self, y, v_one, sim):
    method cosine (line 60) | def cosine(self, t1, t2):
  function get_constant (line 67) | def get_constant(batch_size):
  function train_step (line 104) | def train_step():
  function test_step (line 113) | def test_step():

FILE: utils.py
  function load_embeddings (line 7) | def load_embeddings():
  function encode_sent (line 24) | def encode_sent(s, vocab, max_len):
  function load_train_data (line 33) | def load_train_data(vocab, max_len):
  function qur_load_train_test_data (line 41) | def qur_load_train_test_data(_file, vocab, max_len):
  function ins_load_train_data (line 49) | def ins_load_train_data(vocab, max_len):
  function load_test_data (line 57) | def load_test_data(vocab, max_len):
  function ins_load_test_data (line 65) | def ins_load_test_data(vocab, max_len):
  function gen_train_batch_qpn (line 73) | def gen_train_batch_qpn(_data, batch_size):
  function gen_train_batch_yxx (line 81) | def gen_train_batch_yxx(_data, batch_size):
  function qur_gen_train_batch_yxx (line 89) | def qur_gen_train_batch_yxx(_data, batch_size):
  function ins_gen_train_batch_yxx (line 96) | def ins_gen_train_batch_yxx(_data, batch_size):
  function gen_test_batch_qpn (line 105) | def gen_test_batch_qpn(_data, start, end):
  function gen_test_batch_yxx (line 115) | def gen_test_batch_yxx(_data, start, end):
  function qur_gen_test_batch_yxx (line 123) | def qur_gen_test_batch_yxx(_data, start, end):
  function ins_gen_test_batch_yxx (line 130) | def ins_gen_test_batch_yxx(_data, start, end):
  function _eval (line 140) | def _eval(y, g, yp):
  function eval_best_prec (line 148) | def eval_best_prec(y, g, yp):
  function eval_auc (line 163) | def eval_auc(y, g, yp):
  function eval_top1_prec (line 168) | def eval_top1_prec(y, g, yp):