SYMBOL INDEX (120 symbols across 10 files)

FILE: GLAttention.py
  function conv1x1 (line 4) | def conv1x1(in_planes, out_planes):
  function func_attention (line 10) | def func_attention(query, context, gamma1):
  class GLAttentionGeneral (line 51) | class GLAttentionGeneral(nn.Module):
    method __init__ (line 52) | def __init__(self, idf, cdf):
    method applyMask (line 60) | def applyMask(self, mask):
    method forward (line 63) | def forward(self, input, sentence, context):

FILE: cfg/config.py
  function _merge_a_into_b (line 77) | def _merge_a_into_b(a, b):
  function cfg_from_file (line 110) | def cfg_from_file(filename):

FILE: datasets.py
  function prepare_data (line 28) | def prepare_data(data):
  function get_imgs (line 59) | def get_imgs(img_path, imsize, bbox=None,
  class TextDataset (line 91) | class TextDataset(data.Dataset):
    method __init__ (line 92) | def __init__(self, data_dir, split='train',
    method load_bbox (line 121) | def load_bbox(self):
    method load_captions (line 145) | def load_captions(self, data_dir, filenames):
    method build_dictionary (line 179) | def build_dictionary(self, train_captions, test_captions):
    method load_text_data (line 219) | def load_text_data(self, data_dir, split):
    method load_class_id (line 251) | def load_class_id(self, data_dir, total_num):
    method load_filenames (line 259) | def load_filenames(self, data_dir, split):
    method get_caption (line 269) | def get_caption(self, sent_ix):
    method __getitem__ (line 289) | def __getitem__(self, index):
    method __len__ (line 311) | def __len__(self):

FILE: main.py
  function parse_args (line 24) | def parse_args():
  function gen_example (line 36) | def gen_example(wordtoix, algo):

FILE: miscc/losses.py
  function cosine_similarity (line 11) | def cosine_similarity(x1, x2, dim=1, eps=1e-8):
  function caption_loss (line 19) | def caption_loss(cap_output, captions):
  function sent_loss (line 24) | def sent_loss(cnn_code, rnn_code, labels, class_ids,
  function words_loss (line 66) | def words_loss(img_features, words_emb, labels,
  function discriminator_loss (line 140) | def discriminator_loss(netD, real_imgs, fake_imgs, conditions,
  function generator_loss (line 168) | def generator_loss(netsD, image_encoder, caption_cnn, caption_rnn, capti...
  function KL_loss (line 204) | def KL_loss(mu, logvar):

FILE: miscc/utils.py
  function drawCaption (line 30) | def drawCaption(convas, captions, ixtoword, vis_size, off1=2, off2=2):
  function build_super_images (line 53) | def build_super_images(real_imgs, captions, ixtoword,
  function build_super_images2 (line 179) | def build_super_images2(real_imgs, captions, cap_lens, ixtoword,
  function weights_init (line 285) | def weights_init(m):
  function load_params (line 298) | def load_params(model, new_param):
  function copy_G_params (line 303) | def copy_G_params(model):
  function mkdir_p (line 308) | def mkdir_p(path):

FILE: model.py
  class GLU (line 13) | class GLU(nn.Module):
    method __init__ (line 14) | def __init__(self):
    method forward (line 17) | def forward(self, x):
  function conv1x1 (line 24) | def conv1x1(in_planes, out_planes, bias=False):
  function conv3x3 (line 29) | def conv3x3(in_planes, out_planes):
  function upBlock (line 35) | def upBlock(in_planes, out_planes):
  function Block3x3_relu (line 44) | def Block3x3_relu(in_planes, out_planes):
  class ResBlock (line 52) | class ResBlock(nn.Module):
    method __init__ (line 53) | def __init__(self, channel_num):
    method forward (line 62) | def forward(self, x):
  class RNN_ENCODER (line 70) | class RNN_ENCODER(nn.Module):
    method __init__ (line 71) | def __init__(self, ntoken, ninput=300, drop_prob=0.5,
    method define_module (line 91) | def define_module(self):
    method init_weights (line 109) | def init_weights(self):
    method init_hidden (line 117) | def init_hidden(self, bsz):
    method forward (line 128) | def forward(self, captions, cap_lens, hidden, mask=None):
  class CNN_ENCODER (line 157) | class CNN_ENCODER(nn.Module):
    method __init__ (line 158) | def __init__(self, nef):
    method define_module (line 176) | def define_module(self, model):
    method init_trainable_weights (line 197) | def init_trainable_weights(self):
    method forward (line 202) | def forward(self, x):
  class CA_NET (line 266) | class CA_NET(nn.Module):
    method __init__ (line 269) | def __init__(self):
    method encode (line 276) | def encode(self, text_embedding):
    method reparametrize (line 282) | def reparametrize(self, mu, logvar):
    method forward (line 291) | def forward(self, text_embedding):
  class INIT_STAGE_G (line 297) | class INIT_STAGE_G(nn.Module):
    method __init__ (line 298) | def __init__(self, ngf, ncf):
    method define_module (line 305) | def define_module(self):
    method forward (line 317) | def forward(self, z_code, c_code):
  class NEXT_STAGE_G (line 380) | class NEXT_STAGE_G(nn.Module):
    method __init__ (line 381) | def __init__(self, ngf, nef, ncf):
    method _make_layer (line 392) | def _make_layer(self, block, channel_num):
    method define_module (line 398) | def define_module(self):
    method forward (line 404) | def forward(self, h_code, c_code, word_embs, mask):
  class GET_IMAGE_G (line 436) | class GET_IMAGE_G(nn.Module):
    method __init__ (line 437) | def __init__(self, ngf):
    method forward (line 445) | def forward(self, h_code):
  class G_NET (line 450) | class G_NET(nn.Module):
    method __init__ (line 451) | def __init__(self):
    method forward (line 469) | def forward(self, z_code, sent_emb, word_embs, mask):
  class G_DCGAN (line 508) | class G_DCGAN(nn.Module):
    method __init__ (line 509) | def __init__(self):
    method forward (line 526) | def forward(self, z_code, sent_emb, word_embs, mask):
  function Block3x3_leakRelu (line 552) | def Block3x3_leakRelu(in_planes, out_planes):
  function downBlock (line 562) | def downBlock(in_planes, out_planes):
  function encode_image_by_16times (line 572) | def encode_image_by_16times(ndf):
  class D_GET_LOGITS (line 593) | class D_GET_LOGITS(nn.Module):
    method __init__ (line 594) | def __init__(self, ndf, nef, bcondition=False):
    method forward (line 606) | def forward(self, h_code, c_code=None):
  class D_NET64 (line 622) | class D_NET64(nn.Module):
    method __init__ (line 623) | def __init__(self, b_jcu=True):
    method forward (line 634) | def forward(self, x_var):
  class D_NET128 (line 640) | class D_NET128(nn.Module):
    method __init__ (line 641) | def __init__(self, b_jcu=True):
    method forward (line 655) | def forward(self, x_var):
  class D_NET256 (line 663) | class D_NET256(nn.Module):
    method __init__ (line 664) | def __init__(self, b_jcu=True):
    method forward (line 679) | def forward(self, x_var):
  class CAPTION_CNN (line 686) | class CAPTION_CNN(nn.Module):
    method __init__ (line 687) | def __init__(self, embed_size):
    method forward (line 698) | def forward(self, images):
  class CAPTION_RNN (line 709) | class CAPTION_RNN(nn.Module):
    method __init__ (line 710) | def __init__(self, embed_size, hidden_size, vocab_size, num_layers, ma...
    method forward (line 730) | def forward(self, features, captions, cap_lens):
    method sample (line 739) | def sample(self, features, states=None):

FILE: pretrain_DAMSM.py
  function parse_args (line 37) | def parse_args():
  function train (line 49) | def train(dataloader, cnn_model, rnn_model, batch_size,
  function evaluate (line 133) | def evaluate(dataloader, cnn_model, rnn_model, batch_size):
  function build_models (line 166) | def build_models():

FILE: test.py
  function conv1x1 (line 5) | def conv1x1(in_planes, out_planes):

FILE: trainer.py
  class Trainer (line 23) | class Trainer(object):
    method __init__ (line 24) | def __init__(self, output_dir, data_loader, n_words, ixtoword):
    method build_models (line 43) | def build_models(self):
    method define_optimizers (line 142) | def define_optimizers(self, netG, netsD):
    method prepare_labels (line 157) | def prepare_labels(self):
    method save_model (line 169) | def save_model(self, netG, avg_param_G, netsD, epoch):
    method set_requires_grad_value (line 182) | def set_requires_grad_value(self, models_list, brequires):
    method save_img_results (line 187) | def save_img_results(self, netG, noise, sent_emb, words_embs, mask,
    method train (line 227) | def train(self):
    method save_singleimages (line 318) | def save_singleimages(self, images, filenames, save_dir,
    method sampling (line 337) | def sampling(self, split_dir):
    method gen_example (line 418) | def gen_example(self, data_dic):