SYMBOL INDEX (224 symbols across 23 files)

FILE: data/__init__.py
  function find_dataset_using_name (line 18) | def find_dataset_using_name(dataset_name):
  function get_option_setter (line 41) | def get_option_setter(dataset_name):
  function create_dataset (line 47) | def create_dataset(opt):
  class CustomDatasetDataLoader (line 62) | class CustomDatasetDataLoader():
    method __init__ (line 65) | def __init__(self, opt):
    method load_data (line 81) | def load_data(self):
    method __len__ (line 84) | def __len__(self):
    method __iter__ (line 88) | def __iter__(self):

FILE: data/base_dataset.py
  class BaseDataset (line 13) | class BaseDataset(data.Dataset):
    method __init__ (line 24) | def __init__(self, opt):
    method modify_commandline_options (line 34) | def modify_commandline_options(parser, is_train):
    method __len__ (line 47) | def __len__(self):
    method __getitem__ (line 52) | def __getitem__(self, index):
  function get_params (line 64) | def get_params(opt, size):
  function get_transform (line 82) | def get_transform(opt, params=None, grayscale=False, method=Image.BICUBI...
  function get_transform_mask (line 115) | def get_transform_mask(opt, params=None, grayscale=False, method=Image.B...
  function __make_power_2 (line 144) | def __make_power_2(img, base, method=Image.BICUBIC):
  function __scale_width (line 155) | def __scale_width(img, target_width, method=Image.BICUBIC):
  function __crop (line 164) | def __crop(img, pos, size):
  function __flip (line 173) | def __flip(img, flip):
  function __print_size_warning (line 179) | def __print_size_warning(ow, oh, w, h):

FILE: data/image_folder.py
  function is_image_file (line 19) | def is_image_file(filename):
  function make_dataset (line 23) | def make_dataset(dir, max_dataset_size=float("inf")):
  function default_loader (line 35) | def default_loader(path):
  class ImageFolder (line 39) | class ImageFolder(data.Dataset):
    method __init__ (line 41) | def __init__(self, root, transform=None, return_paths=False,
    method __getitem__ (line 55) | def __getitem__(self, index):
    method __len__ (line 65) | def __len__(self):

FILE: data/single_dataset.py
  class SingleDataset (line 8) | class SingleDataset(BaseDataset):
    method __init__ (line 14) | def __init__(self, opt):
    method __getitem__ (line 28) | def __getitem__(self, index):
    method __len__ (line 61) | def __len__(self):

FILE: data/unaligned_mask_stylecls_dataset.py
  class UnalignedMaskStyleClsDataset (line 12) | class UnalignedMaskStyleClsDataset(BaseDataset):
    method __init__ (line 13) | def __init__(self, opt):
    method __getitem__ (line 34) | def __getitem__(self, index):
    method __len__ (line 98) | def __len__(self):

FILE: models/__init__.py
  function find_model_using_name (line 25) | def find_model_using_name(model_name):
  function get_option_setter (line 48) | def get_option_setter(model_name):
  function create_model (line 54) | def create_model(opt):

FILE: models/asymmetric_cycle_gan_cls_model.py
  function truncate (line 10) | def truncate(fake_B,a=127.5):#[-1,1]
  class AsymmetricCycleGANClsModel (line 13) | class AsymmetricCycleGANClsModel(BaseModel):
    method modify_commandline_options (line 15) | def modify_commandline_options(parser, is_train=True):
    method __init__ (line 44) | def __init__(self, opt):
    method set_input (line 176) | def set_input(self, input):
    method forward (line 206) | def forward(self):
    method backward_D_basic (line 231) | def backward_D_basic(self, netD, real, fake):
    method backward_D_basic_cls (line 253) | def backward_D_basic_cls(self, netD, real, fake):
    method backward_D_A (line 275) | def backward_D_A(self):
    method backward_D_A_l (line 280) | def backward_D_A_l(self):
    method backward_D_A_le (line 285) | def backward_D_A_le(self):
    method backward_D_A_ll (line 290) | def backward_D_A_ll(self):
    method backward_D_B (line 295) | def backward_D_B(self):
    method update_process (line 300) | def update_process(self, epoch):
    method backward_G (line 303) | def backward_G(self):
    method optimize_parameters (line 374) | def optimize_parameters(self):

FILE: models/base_model.py
  class BaseModel (line 8) | class BaseModel():
    method __init__ (line 19) | def __init__(self, opt):
    method modify_commandline_options (line 48) | def modify_commandline_options(parser, is_train):
    method set_input (line 61) | def set_input(self, input):
    method forward (line 70) | def forward(self):
    method optimize_parameters (line 75) | def optimize_parameters(self):
    method setup (line 79) | def setup(self, opt):
    method eval (line 92) | def eval(self):
    method test (line 99) | def test(self):
    method compute_visuals (line 109) | def compute_visuals(self):
    method get_image_paths (line 113) | def get_image_paths(self):
    method update_learning_rate (line 117) | def update_learning_rate(self):
    method get_current_visuals (line 128) | def get_current_visuals(self):
    method get_current_losses (line 136) | def get_current_losses(self):
    method save_networks (line 144) | def save_networks(self, epoch):
    method __patch_instance_norm_state_dict (line 162) | def __patch_instance_norm_state_dict(self, state_dict, module, keys, i...
    method load_networks (line 176) | def load_networks(self, epoch):
    method print_networks (line 201) | def print_networks(self, verbose):
    method set_requires_grad (line 219) | def set_requires_grad(self, nets, requires_grad=False):
    method masked (line 233) | def masked(self, A,mask):

FILE: models/dist_model.py
  class DistModel (line 20) | class DistModel(BaseModel):
    method name (line 21) | def name(self):
    method __init__ (line 24) | def __init__(self, opt, model='net-lin', net='alex', pnet_rand=False, ...
    method forward_pair (line 106) | def forward_pair(self,in1,in2,retPerLayer=False):
    method forward (line 112) | def forward(self, in0, in1, retNumpy=False):
    method optimize_parameters (line 159) | def optimize_parameters(self):
    method clamp_weights (line 166) | def clamp_weights(self):
    method set_input (line 171) | def set_input(self, data):
    method forward_train (line 187) | def forward_train(self): # run forward pass
    method backward_train (line 198) | def backward_train(self):
    method compute_accuracy (line 201) | def compute_accuracy(self,d0,d1,judge):
    method get_current_errors (line 207) | def get_current_errors(self):
    method get_current_visuals (line 216) | def get_current_visuals(self):
    method save (line 231) | def save(self, path, label):
    method update_learning_rate (line 235) | def update_learning_rate(self,nepoch_decay):
  function score_2afc_dataset (line 247) | def score_2afc_dataset(data_loader,func):
  function score_jnd_dataset (line 284) | def score_jnd_dataset(data_loader,func):

FILE: models/networks.py
  class Identity (line 13) | class Identity(nn.Module):
    method forward (line 14) | def forward(self, x):
  function get_norm_layer (line 18) | def get_norm_layer(norm_type='instance'):
  function get_scheduler (line 38) | def get_scheduler(optimizer, opt):
  function init_weights (line 67) | def init_weights(net, init_type='normal', init_gain=0.02):
  function init_net (line 101) | def init_net(net, init_type='normal', init_gain=0.02, gpu_ids=[]):
  function define_G (line 119) | def define_G(input_nc, output_nc, ngf, netG, norm='batch', use_dropout=F...
  function define_D (line 164) | def define_D(input_nc, ndf, netD, n_layers_D=3, norm='batch', init_type=...
  function define_HED (line 210) | def define_HED(init_weights_, gpu_ids_=[]):
  class GANLoss (line 233) | class GANLoss(nn.Module):
    method __init__ (line 240) | def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=...
    method get_target_tensor (line 264) | def get_target_tensor(self, prediction, target_is_real):
    method __call__ (line 281) | def __call__(self, prediction, target_is_real):
  function cal_gradient_penalty (line 302) | def cal_gradient_penalty(netD, real_data, fake_data, device, type='mixed...
  class ResnetGenerator (line 339) | class ResnetGenerator(nn.Module):
    method __init__ (line 345) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 395) | def forward(self, input):
  class ResnetStyle2Generator (line 399) | class ResnetStyle2Generator(nn.Module):
    method __init__ (line 400) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 459) | def forward(self, input1, input2):
  class ResnetBlock (line 465) | class ResnetBlock(nn.Module):
    method __init__ (line 468) | def __init__(self, dim, padding_type, norm_layer, use_dropout, use_bia...
    method build_conv_block (line 479) | def build_conv_block(self, dim, padding_type, norm_layer, use_dropout,...
    method forward (line 520) | def forward(self, x):
  class UnetGenerator (line 526) | class UnetGenerator(nn.Module):
    method __init__ (line 529) | def __init__(self, input_nc, output_nc, num_downs, ngf=64, norm_layer=...
    method forward (line 553) | def forward(self, input):
  class UnetSkipConnectionBlock (line 558) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 564) | def __init__(self, outer_nc, inner_nc, input_nc=None,
    method forward (line 621) | def forward(self, x):
  class NLayerDiscriminator (line 628) | class NLayerDiscriminator(nn.Module):
    method __init__ (line 631) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method forward (line 671) | def forward(self, input):
  class NLayerDiscriminatorCls (line 676) | class NLayerDiscriminatorCls(nn.Module):
    method __init__ (line 679) | def __init__(self, input_nc, ndf=64, n_layers=3, n_class=3, norm_layer...
    method forward (line 736) | def forward(self, input):
  class PixelDiscriminator (line 746) | class PixelDiscriminator(nn.Module):
    method __init__ (line 749) | def __init__(self, input_nc, ndf=64, norm_layer=nn.BatchNorm2d):
    method forward (line 773) | def forward(self, input):
  class HED (line 778) | class HED(nn.Module):
    method __init__ (line 779) | def __init__(self):
    method forward (line 838) | def forward(self, tensorInput):

FILE: models/networks_basic.py
  function spatial_average (line 17) | def spatial_average(in_tens, keepdim=True):
  function upsample (line 20) | def upsample(in_tens, out_H=64): # assumes scale factor is same for H and W
  class PNetLin (line 27) | class PNetLin(nn.Module):
    method __init__ (line 28) | def __init__(self, pnet_type='vgg', pnet_rand=False, pnet_tune=False, ...
    method forward (line 64) | def forward(self, in0, in1, retPerLayer=False):
  class ScalingLayer (line 94) | class ScalingLayer(nn.Module):
    method __init__ (line 95) | def __init__(self):
    method forward (line 100) | def forward(self, inp):
  class NetLinLayer (line 104) | class NetLinLayer(nn.Module):
    method __init__ (line 106) | def __init__(self, chn_in, chn_out=1, use_dropout=False):
  class Dist2LogitLayer (line 114) | class Dist2LogitLayer(nn.Module):
    method __init__ (line 116) | def __init__(self, chn_mid=32, use_sigmoid=True):
    method forward (line 128) | def forward(self,d0,d1,eps=0.1):
  class BCERankingLoss (line 131) | class BCERankingLoss(nn.Module):
    method __init__ (line 132) | def __init__(self, chn_mid=32):
    method forward (line 138) | def forward(self, d0, d1, judge):
  class FakeNet (line 144) | class FakeNet(nn.Module):
    method __init__ (line 145) | def __init__(self, use_gpu=True, colorspace='Lab'):
  class L2 (line 150) | class L2(FakeNet):
    method forward (line 152) | def forward(self, in0, in1, retPerLayer=None):
  class DSSIM (line 167) | class DSSIM(FakeNet):
    method forward (line 169) | def forward(self, in0, in1, retPerLayer=None):
  function print_network (line 182) | def print_network(net):

FILE: models/pretrained_networks.py
  class squeezenet (line 6) | class squeezenet(torch.nn.Module):
    method __init__ (line 7) | def __init__(self, requires_grad=False, pretrained=True):
    method forward (line 36) | def forward(self, X):
  class alexnet (line 57) | class alexnet(torch.nn.Module):
    method __init__ (line 58) | def __init__(self, requires_grad=False, pretrained=True):
    method forward (line 81) | def forward(self, X):
  class vgg16 (line 97) | class vgg16(torch.nn.Module):
    method __init__ (line 98) | def __init__(self, requires_grad=False, pretrained=True):
    method forward (line 121) | def forward(self, X):
  class resnet (line 139) | class resnet(torch.nn.Module):
    method __init__ (line 140) | def __init__(self, requires_grad=False, pretrained=True, num=18):
    method forward (line 163) | def forward(self, X):

FILE: models/test_3styles_model.py
  class Test3StylesModel (line 5) | class Test3StylesModel(BaseModel):
    method modify_commandline_options (line 12) | def modify_commandline_options(parser, is_train=True):
    method __init__ (line 34) | def __init__(self, opt):
    method set_input (line 51) | def set_input(self, input):
    method forward (line 58) | def forward(self):
    method optimize_parameters (line 64) | def optimize_parameters(self):

FILE: models/test_model.py
  class TestModel (line 5) | class TestModel(BaseModel):
    method modify_commandline_options (line 12) | def modify_commandline_options(parser, is_train=True):
    method __init__ (line 40) | def __init__(self, opt):
    method set_input (line 71) | def set_input(self, input):
    method forward (line 84) | def forward(self):
    method optimize_parameters (line 93) | def optimize_parameters(self):

FILE: options/base_options.py
  class BaseOptions (line 9) | class BaseOptions():
    method __init__ (line 16) | def __init__(self):
    method initialize (line 20) | def initialize(self, parser):
    method gather_options (line 61) | def gather_options(self):
    method print_options (line 89) | def print_options(self, opt):
    method parse (line 114) | def parse(self):

FILE: options/test_options.py
  class TestOptions (line 4) | class TestOptions(BaseOptions):
    method initialize (line 10) | def initialize(self, parser):

FILE: options/train_options.py
  class TrainOptions (line 4) | class TrainOptions(BaseOptions):
    method initialize (line 10) | def initialize(self, parser):

FILE: test_seq_style.py
  function opts (line 4) | def opts():

FILE: util/get_data.py
  class GetData (line 11) | class GetData(object):
    method __init__ (line 27) | def __init__(self, technique='cyclegan', verbose=True):
    method _print (line 35) | def _print(self, text):
    method _get_options (line 40) | def _get_options(r):
    method _present_options (line 46) | def _present_options(self):
    method _download_data (line 56) | def _download_data(self, dataset_url, save_path):
    method get (line 79) | def get(self, save_path, dataset=None):

FILE: util/html.py
  class HTML (line 6) | class HTML:
    method __init__ (line 14) | def __init__(self, web_dir, title, refresh=0, folder='images'):
    method get_image_dir (line 37) | def get_image_dir(self):
    method add_header (line 41) | def add_header(self, text):
    method add_images (line 50) | def add_images(self, ims, txts, links, width=400):
    method save (line 71) | def save(self):

FILE: util/image_pool.py
  class ImagePool (line 5) | class ImagePool():
    method __init__ (line 12) | def __init__(self, pool_size):
    method query (line 23) | def query(self, images):

FILE: util/util.py
  function tensor2im (line 11) | def tensor2im(input_image, imtype=np.uint8):
  function diagnose_network (line 36) | def diagnose_network(net, name='network'):
  function save_image (line 55) | def save_image(image_numpy, image_path):
  function print_numpy (line 67) | def print_numpy(x, val=True, shp=False):
  function mkdirs (line 83) | def mkdirs(paths):
  function mkdir (line 96) | def mkdir(path):
  function normalize_tensor (line 105) | def normalize_tensor(in_feat,eps=1e-10):

FILE: util/visualizer.py
  function save_images (line 16) | def save_images(webpage, visuals, image_path, aspect_ratio=1.0, width=25...
  class Visualizer (line 56) | class Visualizer():
    method __init__ (line 62) | def __init__(self, opt):
    method reset (line 97) | def reset(self):
    method create_visdom_connections (line 101) | def create_visdom_connections(self):
    method display_current_results (line 108) | def display_current_results(self, visuals, epoch, save_result):
    method plot_current_losses (line 189) | def plot_current_losses(self, epoch, counter_ratio, losses):
    method print_current_losses (line 217) | def print_current_losses(self, epoch, iters, losses, t_comp, t_data):
    method print_current_losses_process (line 236) | def print_current_losses_process(self, epoch, iters, losses, t_comp, t...