SYMBOL INDEX (130 symbols across 14 files)

FILE: attention.py
  class Att_0 (line 8) | class Att_0(nn.Module):
    method __init__ (line 9) | def __init__(self, v_dim, q_dim, num_hid, norm, act, dropout=0.0):
    method forward (line 15) | def forward(self, v, q):
    method logits (line 24) | def logits(self, v, q):
  class Att_1 (line 34) | class Att_1(nn.Module):
    method __init__ (line 35) | def __init__(self, v_dim, q_dim, num_hid, norm, act, dropout=0.0):
    method forward (line 41) | def forward(self, v, q):
    method logits (line 50) | def logits(self, v, q):
  class Att_2 (line 60) | class Att_2(nn.Module):
    method __init__ (line 61) | def __init__(self, v_dim, q_dim, num_hid, norm, act, dropout=0.0):
    method forward (line 68) | def forward(self, v, q):
    method logits (line 77) | def logits(self, v, q):
  class Att_3 (line 87) | class Att_3(nn.Module):
    method __init__ (line 88) | def __init__(self, v_dim, q_dim, num_hid, norm, act, dropout=0.0):
    method forward (line 96) | def forward(self, v, q):
    method logits (line 105) | def logits(self, v, q):
  class Att_3S (line 115) | class Att_3S(nn.Module):
    method __init__ (line 116) | def __init__(self, v_dim, q_dim, num_hid, norm, act, dropout=0.0):
    method forward (line 124) | def forward(self, v, q):
    method logits (line 133) | def logits(self, v, q):
  class Att_PD (line 144) | class Att_PD(nn.Module):
    method __init__ (line 145) | def __init__(self, v_dim, q_dim, num_hid, norm, act, dropout=0.0):
    method forward (line 152) | def forward(self, v, q):
    method logits (line 161) | def logits(self, v, q):
  class Att_P (line 173) | class Att_P(nn.Module):
    method __init__ (line 174) | def __init__(self, v_dim, q_dim, num_hid, norm, act, dropout=0.0):
    method forward (line 181) | def forward(self, v, q):
    method logits (line 190) | def logits(self, v, q):

FILE: classifier.py
  class SimpleClassifier (line 5) | class SimpleClassifier(nn.Module):
    method __init__ (line 6) | def __init__(self, in_dim, hid_dim, out_dim, norm, act, dropout=0.5):
    method forward (line 20) | def forward(self, x):
  class PaperClassifier (line 24) | class PaperClassifier(nn.Module):
    method __init__ (line 25) | def __init__(self, in_dim, hid_dim_1, hid_dim_2, out_dim, norm, act, d...
    method forward (line 48) | def forward(self, x):

FILE: dataset.py
  class Dictionary (line 12) | class Dictionary(object):
    method __init__ (line 13) | def __init__(self, word2idx=None, idx2word=None):
    method ntoken (line 22) | def ntoken(self):
    method padding_idx (line 26) | def padding_idx(self):
    method tokenize (line 29) | def tokenize(self, sentence, add_word):
    method dump_to_file (line 42) | def dump_to_file(self, path):
    method load_from_file (line 47) | def load_from_file(cls, path):
    method add_word (line 53) | def add_word(self, word):
    method __len__ (line 59) | def __len__(self):
  function _create_entry (line 63) | def _create_entry(img, question, answer):
  function _load_dataset (line 75) | def _load_dataset(dataroot, name, img_id2val):
  class VQAFeatureDataset (line 101) | class VQAFeatureDataset(Dataset):
    method __init__ (line 102) | def __init__(self, name, dictionary, dataroot='data'):
    method tokenize (line 129) | def tokenize(self, max_length=14):
    method tensorize (line 145) | def tensorize(self):
    method __getitem__ (line 165) | def __getitem__(self, index):
    method __len__ (line 180) | def __len__(self):

FILE: fc.py
  function get_norm (line 6) | def get_norm(norm):
  function get_act (line 22) | def get_act(act):
  class FCNet (line 48) | class FCNet(nn.Module):
    method __init__ (line 51) | def __init__(self, dims, dropout, norm, act):
    method forward (line 70) | def forward(self, x):
  class GTH (line 75) | class GTH(nn.Module):
    method __init__ (line 78) | def __init__(self, in_dim, out_dim, dropout, norm, act):
    method forward (line 84) | def forward(self, x):

FILE: heatmap.py
  function plot_heatmap (line 7) | def plot_heatmap(a, b, title='title', saveLoc='temp'):

FILE: language_model.py
  class WordEmbedding (line 7) | class WordEmbedding(nn.Module):
    method __init__ (line 13) | def __init__(self, ntoken, emb_dim, dropout):
    method init_embedding (line 20) | def init_embedding(self, np_file):
    method forward (line 25) | def forward(self, x):
  class QuestionEmbedding (line 31) | class QuestionEmbedding(nn.Module):
    method __init__ (line 32) | def __init__(self, in_dim, num_hid, nlayers, bidirect, dropout, rnn_ty...
    method init_hidden (line 51) | def init_hidden(self, batch):
    method forward (line 61) | def forward(self, x):
    method forward_all (line 75) | def forward_all(self, x):

FILE: main.py
  function parse_args (line 19) | def parse_args():
  function weights_init_xn (line 42) | def weights_init_xn(m):
  function weights_init_xu (line 46) | def weights_init_xu(m):
  function weights_init_kn (line 52) | def weights_init_kn(m):
  function weights_init_ku (line 55) | def weights_init_ku(m):

FILE: models.py
  class Model (line 16) | class Model(nn.Module):
    method __init__ (line 17) | def __init__(self, w_emb, q_emb, v_att, q_net, v_net, classifier):
    method forward (line 26) | def forward(self, v, b, q, labels):
  class Model_2 (line 48) | class Model_2(nn.Module):
    method __init__ (line 49) | def __init__(self, w_emb, q_emb, v_att_1, v_att_2, q_net, v_net, class...
    method forward (line 59) | def forward(self, v, b, q, labels):
  class Model_3 (line 83) | class Model_3(nn.Module):
    method __init__ (line 84) | def __init__(self, w_emb, q_emb, v_att_1, v_att_2, v_att_3, q_net, v_n...
    method forward (line 95) | def forward(self, v, b, q, labels):
  function build_baseline (line 120) | def build_baseline(dataset, num_hid, dropout, norm, activation, dropL , ...
  function build_model_A1 (line 133) | def build_model_A1(dataset, num_hid, dropout, norm, activation, dropL , ...
  function build_model_A2 (line 146) | def build_model_A2(dataset, num_hid, dropout, norm, activation, dropL , ...
  function build_model_A3 (line 159) | def build_model_A3(dataset, num_hid, dropout, norm, activation, dropL , ...
  function build_model_A3S (line 172) | def build_model_A3S(dataset, num_hid, dropout, norm, activation, dropL ,...
  function build_model_A3x2 (line 185) | def build_model_A3x2(dataset, num_hid, dropout, norm, activation, dropL ...
  function build_model_A2x2 (line 201) | def build_model_A2x2(dataset, num_hid, dropout, norm, activation, dropL ...
  function build_model_A23P (line 217) | def build_model_A23P(dataset, num_hid, dropout, norm, activation, dropL ...
  function build_model_A3x3 (line 235) | def build_model_A3x3(dataset, num_hid, dropout, norm, activation, dropL ...
  function build_model_A2x3 (line 253) | def build_model_A2x3(dataset, num_hid, dropout, norm, activation, dropL ...
  function build_model_AP (line 272) | def build_model_AP(dataset, num_hid, dropout, norm, activation, dropL , ...
  function build_model_APx2 (line 285) | def build_model_APx2(dataset, num_hid, dropout, norm, activation, dropL ...
  function build_model_APD (line 300) | def build_model_APD(dataset, num_hid, dropout, norm, activation, dropL ,...
  function build_model_AP_PC (line 312) | def build_model_AP_PC(dataset, num_hid, dropout, norm, activation, dropL...
  function build_model_P_exact (line 325) | def build_model_P_exact(dataset, num_hid, dropout, norm, activation):
  function build_model_P_mod (line 337) | def build_model_P_mod(dataset, num_hid, dropout, norm, activation, dropL...

FILE: plot.py
  function plot_charts (line 8) | def plot_charts(modelLoc):

FILE: test.py
  function test (line 21) | def test(args):

FILE: tools/compute_softscore.py
  function get_score (line 80) | def get_score(occurences):
  function process_punctuation (line 93) | def process_punctuation(inText):
  function process_digit_article (line 105) | def process_digit_article(inText):
  function multiple_replace (line 121) | def multiple_replace(text, wordDict):
  function preprocess_answer (line 127) | def preprocess_answer(answer):
  function filter_answers (line 133) | def filter_answers(answers_dset, min_occurence):
  function create_ans2label (line 154) | def create_ans2label(occurence, name, cache_root='data/cache'):
  function compute_target (line 178) | def compute_target(answers_dset, ans2label, name, cache_root='data/cache'):
  function get_answer (line 215) | def get_answer(qid, answers):
  function get_question (line 221) | def get_question(qid, questions):

FILE: tools/create_dictionary.py
  function create_dictionary (line 10) | def create_dictionary(dataroot):
  function create_glove_embedding_init (line 27) | def create_glove_embedding_init(idx2word, glove_file):

FILE: train.py
  function instance_bce_with_logits (line 12) | def instance_bce_with_logits(logits, labels):
  function compute_score_with_logits (line 20) | def compute_score_with_logits(logits, labels):
  function train (line 28) | def train(model, train_loader, eval_loader, num_epochs, output, opt, wd):
  function evaluate (line 82) | def evaluate(model, dataloader):

FILE: utils.py
  function assert_eq (line 14) | def assert_eq(real, expected):
  function assert_array_eq (line 18) | def assert_array_eq(real, expected):
  function load_folder (line 23) | def load_folder(folder, suffix):
  function load_imageid (line 31) | def load_imageid(folder):
  function pil_loader (line 40) | def pil_loader(path):
  function weights_init (line 46) | def weights_init(m):
  function init_net (line 58) | def init_net(net, net_file):
  function create_dir (line 65) | def create_dir(path):
  class Logger (line 74) | class Logger(object):
    method __init__ (line 75) | def __init__(self, output_name):
    method append (line 83) | def append(self, key, val):
    method log (line 87) | def log(self, extra_msg=''):
    method write (line 97) | def write(self, msg):