SYMBOL INDEX (239 symbols across 30 files)

FILE: drawing_and_style_transfer/data/__init__.py
  function CreateDataLoader (line 5) | def CreateDataLoader(opt):
  function CreateDataset (line 12) | def CreateDataset(opt):
  class CustomDatasetDataLoader (line 30) | class CustomDatasetDataLoader(BaseDataLoader):
    method name (line 31) | def name(self):
    method initialize (line 34) | def initialize(self, opt):
    method load_data (line 43) | def load_data(self):
    method __len__ (line 46) | def __len__(self):
    method __iter__ (line 49) | def __iter__(self):

FILE: drawing_and_style_transfer/data/aligned_dataset.py
  class AlignedDataset (line 10) | class AlignedDataset(BaseDataset):
    method initialize (line 11) | def initialize(self, opt):
    method __getitem__ (line 18) | def __getitem__(self, index):
    method __len__ (line 60) | def __len__(self):
    method name (line 63) | def name(self):

FILE: drawing_and_style_transfer/data/base_data_loader.py
  class BaseDataLoader (line 1) | class BaseDataLoader():
    method __init__ (line 2) | def __init__(self):
    method initialize (line 5) | def initialize(self, opt):
    method load_data (line 9) | def load_data(self):

FILE: drawing_and_style_transfer/data/base_dataset.py
  class BaseDataset (line 6) | class BaseDataset(data.Dataset):
    method __init__ (line 7) | def __init__(self):
    method name (line 10) | def name(self):
    method initialize (line 13) | def initialize(self, opt):
  function get_transform (line 17) | def get_transform(opt):
  function __scale_width (line 44) | def __scale_width(img, target_width):

FILE: drawing_and_style_transfer/data/image_folder.py
  function is_image_file (line 20) | def is_image_file(filename):
  function make_dataset (line 24) | def make_dataset(dir, max_items=-1, start=0):
  function default_loader (line 39) | def default_loader(path):
  class ImageFolder (line 43) | class ImageFolder(data.Dataset):
    method __init__ (line 44) | def __init__(self, root, transform=None, return_paths=False,
    method __getitem__ (line 58) | def __getitem__(self, index):
    method __len__ (line 68) | def __len__(self):

FILE: drawing_and_style_transfer/data/single_dataset.py
  class SingleDataset (line 7) | class SingleDataset(BaseDataset):
    method initialize (line 8) | def initialize(self, opt):
    method __getitem__ (line 19) | def __getitem__(self, index):
    method __len__ (line 34) | def __len__(self):
    method name (line 37) | def name(self):

FILE: drawing_and_style_transfer/data/unaligned_dataset.py
  class UnalignedDataset (line 8) | class UnalignedDataset(BaseDataset):
    method initialize (line 9) | def initialize(self, opt):
    method __getitem__ (line 23) | def __getitem__(self, index):
    method __len__ (line 53) | def __len__(self):
    method name (line 56) | def name(self):

FILE: drawing_and_style_transfer/datasets/make_dataset_aligned.py
  function get_file_paths (line 6) | def get_file_paths(folder):
  function align_images (line 20) | def align_images(a_file_paths, b_file_paths, target_path):

FILE: drawing_and_style_transfer/models/__init__.py
  function create_model (line 1) | def create_model(opt):

FILE: drawing_and_style_transfer/models/autoencoder_model.py
  class AutoEncoderModel (line 11) | class AutoEncoderModel(BaseModel):
    method name (line 12) | def name(self):
    method set_encoders_and_decoders (line 15) | def set_encoders_and_decoders(self, opt):
    method initialize (line 52) | def initialize(self, opt):
    method set_input (line 103) | def set_input(self, input):
    method forward (line 112) | def forward(self):
    method netEnc (line 115) | def netEnc(self, x):
    method netDec (line 118) | def netDec(self, x):
    method test (line 121) | def test(self):
    method get_image_paths (line 127) | def get_image_paths(self):
    method backward_D_basic (line 130) | def backward_D_basic(self, netD, real, fake):
    method backward_D (line 143) | def backward_D(self):
    method _compute_kl (line 148) | def _compute_kl(self, mu):
    method backward_G (line 153) | def backward_G(self):
    method optimize_parameters (line 172) | def optimize_parameters(self):
    method get_current_errors (line 188) | def get_current_errors(self):
    method get_current_visuals (line 192) | def get_current_visuals(self):
    method save (line 198) | def save(self, label):

FILE: drawing_and_style_transfer/models/base_model.py
  class BaseModel (line 5) | class BaseModel(object):
    method name (line 6) | def name(self):
    method initialize (line 9) | def initialize(self, opt):
    method set_input (line 17) | def set_input(self, input):
    method forward (line 20) | def forward(self):
    method test (line 24) | def test(self):
    method get_image_paths (line 27) | def get_image_paths(self):
    method optimize_parameters (line 30) | def optimize_parameters(self):
    method get_current_visuals (line 33) | def get_current_visuals(self):
    method get_current_errors (line 36) | def get_current_errors(self):
    method save (line 39) | def save(self, label):
    method save_network (line 43) | def save_network(self, network, network_label, epoch_label, gpu_ids):
    method load_network (line 51) | def load_network(self, network, network_label, epoch_label):
    method update_learning_rate (line 57) | def update_learning_rate(self):
    method as_np (line 63) | def as_np(self, data):

FILE: drawing_and_style_transfer/models/networks.py
  class pixel_norm (line 13) | class pixel_norm(nn.Module):
    method forward (line 14) | def forward(self, x, epsilon=1e-8):
  function weights_init_normal (line 18) | def weights_init_normal(m):
  function weights_init_xavier (line 30) | def weights_init_xavier(m):
  function weights_init_kaiming (line 42) | def weights_init_kaiming(m):
  function weights_init_orthogonal (line 54) | def weights_init_orthogonal(m):
  function init_weights (line 66) | def init_weights(net, init_type='normal'):
  function get_norm_layer (line 80) | def get_norm_layer(norm_type='instance'):
  function get_scheduler (line 92) | def get_scheduler(optimizer, opt):
  function define_ED (line 108) | def define_ED(input_nc, output_nc, ngf, which_model_netG, norm='batch', ...
  function define_G (line 141) | def define_G(input_nc, output_nc, ngf, which_model_netG, norm='batch', u...
  function define_D (line 170) | def define_D(input_nc, ndf, which_model_netD,
  function print_network (line 194) | def print_network(net):
  class GANLoss (line 211) | class GANLoss(nn.Module):
    method __init__ (line 212) | def __init__(self, use_lsgan=True, target_real_label=1.0, target_fake_...
    method get_target_tensor (line 225) | def get_target_tensor(self, input, target_is_real):
    method __call__ (line 243) | def __call__(self, input, target_is_real):
  class ResnetEncoder (line 253) | class ResnetEncoder(nn.Module):
    method __init__ (line 254) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 290) | def forward(self, input):
  class ResnetDecoder (line 297) | class ResnetDecoder(nn.Module):
    method __init__ (line 298) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 333) | def forward(self, input):
  class ResnetGenerator (line 344) | class ResnetGenerator(nn.Module):
    method __init__ (line 345) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 391) | def forward(self, input):
  class ResnetBlock (line 399) | class ResnetBlock(nn.Module):
    method __init__ (line 400) | def __init__(self, dim, padding_type, norm_layer, use_dropout, use_bias):
    method build_conv_block (line 404) | def build_conv_block(self, dim, padding_type, norm_layer, use_dropout,...
    method forward (line 436) | def forward(self, x):
  class UnetGenerator (line 445) | class UnetGenerator(nn.Module):
    method __init__ (line 446) | def __init__(self, input_nc, output_nc, num_downs, ngf=64,
    method forward (line 467) | def forward(self, input):
  class UnetSkipConnectionBlock (line 477) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 478) | def __init__(self, outer_nc, inner_nc, input_nc=None,
    method forward (line 523) | def forward(self, x):
  class NLayerDiscriminator (line 531) | class NLayerDiscriminator(nn.Module):
    method __init__ (line 532) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method forward (line 575) | def forward(self, input):
  class PixelDiscriminator (line 582) | class PixelDiscriminator(nn.Module):
    method __init__ (line 583) | def __init__(self, input_nc, ndf=64, norm_layer=nn.BatchNorm2d, use_si...
    method forward (line 604) | def forward(self, input):

FILE: drawing_and_style_transfer/models/ost.py
  class OSTModel (line 11) | class OSTModel(BaseModel):
    method name (line 12) | def name(self):
    method _compute_kl (line 15) | def _compute_kl(self, mu):
    method set_encoders_and_decoders (line 20) | def set_encoders_and_decoders(self, opt):
    method initialize (line 67) | def initialize(self, opt):
    method set_input (line 144) | def set_input(self, input):
    method forward (line 155) | def forward(self):
    method test (line 159) | def test(self):
    method get_image_paths (line 178) | def get_image_paths(self):
    method backward_D_basic (line 181) | def backward_D_basic(self, netD, real, fake):
    method backward_D (line 194) | def backward_D(self):
    method backward_G (line 203) | def backward_G(self):
    method optimize_parameters (line 239) | def optimize_parameters(self):
    method get_current_errors (line 265) | def get_current_errors(self):
    method get_current_visuals (line 273) | def get_current_visuals(self):
    method save (line 286) | def save(self, label):

FILE: drawing_and_style_transfer/models/test_model.py
  class TestModel (line 8) | class TestModel(BaseModel):
    method name (line 9) | def name(self):
    method initialize (line 12) | def initialize(self, opt):
    method set_input (line 27) | def set_input(self, input):
    method test (line 35) | def test(self):
    method get_image_paths (line 40) | def get_image_paths(self):
    method get_current_visuals (line 43) | def get_current_visuals(self):

FILE: drawing_and_style_transfer/options/base_options.py
  class BaseOptions (line 7) | class BaseOptions():
    method __init__ (line 8) | def __init__(self):
    method initialize (line 12) | def initialize(self):
    method parse (line 74) | def parse(self):

FILE: drawing_and_style_transfer/options/test_options.py
  class TestOptions (line 4) | class TestOptions(BaseOptions):
    method initialize (line 5) | def initialize(self):

FILE: drawing_and_style_transfer/options/train_options.py
  class TrainOptions (line 4) | class TrainOptions(BaseOptions):
    method initialize (line 5) | def initialize(self):

FILE: drawing_and_style_transfer/util/get_data.py
  class GetData (line 11) | class GetData(object):
    method __init__ (line 29) | def __init__(self, technique='cyclegan', verbose=True):
    method _print (line 37) | def _print(self, text):
    method _get_options (line 42) | def _get_options(r):
    method _present_options (line 48) | def _present_options(self):
    method _download_data (line 58) | def _download_data(self, dataset_url, save_path):
    method get (line 81) | def get(self, save_path, dataset=None):

FILE: drawing_and_style_transfer/util/html.py
  class HTML (line 6) | class HTML:
    method __init__ (line 7) | def __init__(self, web_dir, title, reflesh=0):
    method get_image_dir (line 22) | def get_image_dir(self):
    method add_header (line 25) | def add_header(self, str):
    method add_table (line 29) | def add_table(self, border=1):
    method add_images (line 33) | def add_images(self, ims, txts, links, width=400):
    method save (line 45) | def save(self):

FILE: drawing_and_style_transfer/util/image_pool.py
  class ImagePool (line 6) | class ImagePool():
    method __init__ (line 7) | def __init__(self, pool_size):
    method query (line 13) | def query(self, images):

FILE: drawing_and_style_transfer/util/util.py
  function tensor2im (line 10) | def tensor2im(image_tensor, imtype=np.uint8):
  function diagnose_network (line 18) | def diagnose_network(net, name='network'):
  function save_image (line 31) | def save_image(image_numpy, image_path):
  function print_numpy (line 36) | def print_numpy(x, val=True, shp=False):
  function mkdirs (line 46) | def mkdirs(paths):
  function mkdir (line 54) | def mkdir(path):

FILE: drawing_and_style_transfer/util/visualizer.py
  class Visualizer (line 10) | class Visualizer():
    method __init__ (line 11) | def __init__(self, opt):
    method reset (line 33) | def reset(self):
    method display_current_results (line 37) | def display_current_results(self, visuals, epoch, save_result):
    method plot_current_errors (line 101) | def plot_current_errors(self, epoch, counter_ratio, opt, errors):
    method print_current_errors (line 117) | def print_current_errors(self, epoch, i, errors, t, t_data):
    method save_images (line 127) | def save_images(self, webpage, visuals, image_path, aspect_ratio=1.0, ...

FILE: mnist_to_svhn/data_loader.py
  function get_loader (line 6) | def get_loader(config):

FILE: mnist_to_svhn/main_autoencoder.py
  function str2bool (line 9) | def str2bool(v):
  function main (line 13) | def main(config):

FILE: mnist_to_svhn/main_mnist_to_svhn.py
  function str2bool (line 10) | def str2bool(v):
  function main (line 14) | def main(config):

FILE: mnist_to_svhn/main_svhn_to_mnist.py
  function str2bool (line 10) | def str2bool(v):
  function main (line 14) | def main(config):

FILE: mnist_to_svhn/model.py
  function deconv (line 5) | def deconv(c_in, c_out, k_size, stride=2, pad=1, bn=True):
  function conv (line 14) | def conv(c_in, c_out, k_size, stride=2, pad=1, bn=True):
  class G11 (line 23) | class G11(nn.Module):
    method __init__ (line 24) | def __init__(self, conv_dim=64):
    method forward (line 42) | def forward(self, x, svhn=False):
    method encode (line 60) | def encode(self, x, svhn=False):
    method decode (line 72) | def decode(self, out, svhn=False):
    method encode_params (line 84) | def encode_params(self):
    method decode_params (line 92) | def decode_params(self):
    method unshared_parameters (line 100) | def unshared_parameters(self):
  class G22 (line 105) | class G22(nn.Module):
    method __init__ (line 106) | def __init__(self, conv_dim=64):
    method forward (line 124) | def forward(self, x, mnist=False):
    method encode (line 142) | def encode(self, x, mnist=False):
    method decode (line 154) | def decode(self, out, mnist=False):
    method encode_params (line 166) | def encode_params(self):
    method decode_params (line 174) | def decode_params(self):
    method unshared_parameters (line 182) | def unshared_parameters(self):
  class D1 (line 187) | class D1(nn.Module):
    method __init__ (line 190) | def __init__(self, conv_dim=64, use_labels=False):
    method forward (line 198) | def forward(self, x_0):
  class D2 (line 207) | class D2(nn.Module):
    method __init__ (line 210) | def __init__(self, conv_dim=64, use_labels=False):
    method forward (line 218) | def forward(self, x_0):

FILE: mnist_to_svhn/solver_autoencoder.py
  class Solver (line 13) | class Solver(object):
    method __init__ (line 14) | def __init__(self, config, svhn_loader, mnist_loader):
    method build_model (line 38) | def build_model(self):
    method merge_images (line 57) | def merge_images(self, sources, targets, k=10):
    method to_var (line 68) | def to_var(self, x):
    method to_data (line 74) | def to_data(self, x):
    method reset_grad (line 80) | def reset_grad(self):
    method _compute_kl (line 85) | def _compute_kl(self, mu):
    method train (line 90) | def train(self):

FILE: mnist_to_svhn/solver_mnist_to_svhn.py
  class Solver (line 13) | class Solver(object):
    method __init__ (line 14) | def __init__(self, config, svhn_loader, mnist_loader):
    method build_model (line 42) | def build_model(self):
    method merge_images (line 61) | def merge_images(self, sources, targets, k=10):
    method to_var (line 72) | def to_var(self, x, volatile=False):
    method to_no_grad_var (line 80) | def to_no_grad_var(self, x):
    method to_data (line 84) | def to_data(self, x, no_numpy=False):
    method reset_grad (line 92) | def reset_grad(self):
    method _compute_kl (line 98) | def _compute_kl(self, mu):
    method train (line 104) | def train(self):

FILE: mnist_to_svhn/solver_svhn_to_mnist.py
  class Solver (line 13) | class Solver(object):
    method __init__ (line 14) | def __init__(self, config, svhn_loader, mnist_loader):
    method build_model (line 42) | def build_model(self):
    method merge_images (line 61) | def merge_images(self, sources, targets, k=10):
    method to_var (line 72) | def to_var(self, x, volatile=False):
    method to_no_grad_var (line 80) | def to_no_grad_var(self, x):
    method to_data (line 84) | def to_data(self, x, no_numpy=False):
    method reset_grad (line 92) | def reset_grad(self):
    method _compute_kl (line 98) | def _compute_kl(self, mu):
    method train (line 103) | def train(self):