SYMBOL INDEX (386 symbols across 52 files)

FILE: cycada/data/adda_datasets.py
  class AddaDataLoader (line 9) | class AddaDataLoader(object):
    method __init__ (line 10) | def __init__(self, net_transform, dataset, rootdir, downscale, crop_si...
    method __iter__ (line 31) | def __iter__(self):
    method __next__ (line 34) | def __next__(self):
    method next (line 37) | def next(self):
    method __len__ (line 51) | def __len__(self):
    method set_loader_src (line 54) | def set_loader_src(self):
    method set_loader_tgt (line 69) | def set_loader_tgt(self):

FILE: cycada/data/bdds.py
  class BDDS (line 10) | class BDDS(data.Dataset):
    method __init__ (line 11) | def __init__(self, root, num_cls=19, split='train', remap_labels=True,...
    method collect_ids (line 22) | def collect_ids(self):
    method img_path (line 32) | def img_path(self, filename):
    method label_path (line 35) | def label_path(self, filename):
    method __getitem__ (line 38) | def __getitem__(self, index, debug=False):
    method __len__ (line 51) | def __len__(self):

FILE: cycada/data/cityscapes.py
  function remap_labels_to_train_ids (line 10) | def remap_labels_to_train_ids(arr):
  class CityScapesParams (line 18) | class CityScapesParams(DatasetParams):
  class Cityscapes (line 28) | class Cityscapes(data.Dataset):
    method __init__ (line 29) | def __init__(self, root, num_cls=19, split='train', remap_labels=True,...
    method collect_ids (line 43) | def collect_ids(self):
    method img_path (line 52) | def img_path(self, id):
    method label_path (line 58) | def label_path(self, id):
    method __getitem__ (line 64) | def __getitem__(self, index, debug=False):
    method __len__ (line 78) | def __len__(self):

FILE: cycada/data/cityscapes_labels.py
  function label_img_to_color (line 7) | def label_img_to_color(img):

FILE: cycada/data/cyclegan.py
  class CycleGANDataset (line 10) | class CycleGANDataset(data.Dataset):
    method __init__ (line 11) | def __init__(self, root, regexp, transform=None, target_transform=None,
    method find_images (line 19) | def find_images(self, regexp='*.png'):
    method __getitem__ (line 28) | def __getitem__(self, index):
    method __len__ (line 39) | def __len__(self):
  class Svhn2MNIST (line 44) | class Svhn2MNIST(CycleGANDataset):
    method __init__ (line 45) | def __init__(self, root, train=True, transform=None, target_transform=...
  class Svhn2MNISTParams (line 56) | class Svhn2MNISTParams(DatasetParams):
  class Usps2Mnist (line 76) | class Usps2Mnist(CycleGANDataset):
    method __init__ (line 77) | def __init__(self, root, train=True, transform=None, target_transform=...
  class Usps2MnistParams (line 88) | class Usps2MnistParams(DatasetParams):
  class Mnist2Usps (line 100) | class Mnist2Usps(CycleGANDataset):
    method __init__ (line 101) | def __init__(self, root, train=True, transform=None, target_transform=...
  class Mnist2UspsParams (line 112) | class Mnist2UspsParams(DatasetParams):

FILE: cycada/data/cyclegta5.py
  class CycleGTA5 (line 12) | class CycleGTA5(GTA5):
    method collect_ids (line 13) | def collect_ids(self):
    method __getitem__ (line 29) | def __getitem__(self, index, debug=False):

FILE: cycada/data/cyclesynthia.py
  function syn_relabel (line 55) | def syn_relabel(arr):
  class SYNTHIAParams (line 63) | class SYNTHIAParams(DatasetParams):
  class CycleSYNTHIA (line 73) | class CycleSYNTHIA(data.Dataset):
    method __init__ (line 75) | def __init__(self, root, num_cls=19, split='train', remap_labels=True,...
    method collect_ids (line 85) | def collect_ids(self):
    method img_path (line 99) | def img_path(self, filename):
    method label_path (line 102) | def label_path(self, filename):
    method __getitem__ (line 110) | def __getitem__(self, index, debug=False):
    method __len__ (line 126) | def __len__(self):

FILE: cycada/data/cyclesynthia_cyclegta5.py
  function syn_relabel (line 56) | def syn_relabel(arr):
  class SYNTHIAParams (line 64) | class SYNTHIAParams(DatasetParams):
  class CycleSYNTHIACycleGTA5 (line 74) | class CycleSYNTHIACycleGTA5(data.Dataset):
    method __init__ (line 76) | def __init__(self, root, num_cls=19, split='train', remap_labels=True,...
    method collect_ids (line 89) | def collect_ids(self, datasets_name):
    method img_path (line 110) | def img_path(self, prefix, filename):
    method syn_label_path (line 115) | def syn_label_path(self, filename):
    method gta_label_path (line 121) | def gta_label_path(self, filename):
    method __getitem__ (line 127) | def __getitem__(self, index, debug=False):
    method __len__ (line 166) | def __len__(self):

FILE: cycada/data/data_loader.py
  function load_data (line 15) | def load_data(name, dset, batch=64, rootdir='', num_channels=3,
  function get_transform_dataset (line 34) | def get_transform_dataset(dataset_name, rootdir, net_transform, downscal...
  function get_orig_size (line 43) | def get_orig_size(dataset_name):
  function get_transform2 (line 51) | def get_transform2(dataset_name, net_transform, downscale, resize):
  function get_transform (line 72) | def get_transform(params, image_size, num_channels):
  function get_target_transform (line 98) | def get_target_transform(params):
  class AddaDataset (line 108) | class AddaDataset(data.Dataset):
    method __init__ (line 110) | def __init__(self, src_data, tgt_data):
    method __getitem__ (line 114) | def __getitem__(self, index):
    method __len__ (line 121) | def __len__(self):
  function register_data_params (line 128) | def register_data_params(name):
  function register_dataset_obj (line 139) | def register_dataset_obj(name):
  class DatasetParams (line 147) | class DatasetParams(object):
  function get_dataset (line 157) | def get_dataset(name, rootdir, dset, image_size, num_channels, download=...
  function get_fcn_dataset (line 167) | def get_fcn_dataset(name, rootdir, **kwargs):

FILE: cycada/data/gta5.py
  class GTA5Params (line 13) | class GTA5Params(DatasetParams):
  class GTA5 (line 23) | class GTA5(data.Dataset):
    method __init__ (line 25) | def __init__(self, root, num_cls=19, split='train', remap_labels=True,...
    method collect_ids (line 41) | def collect_ids(self):
    method img_path (line 46) | def img_path(self, id):
    method label_path (line 50) | def label_path(self, id):
    method __getitem__ (line 54) | def __getitem__(self, index, debug=False):
    method __len__ (line 71) | def __len__(self):

FILE: cycada/data/rotater.py
  class Rotater (line 1) | class Rotater(object):
    method __init__ (line 3) | def __init__(self, dataset, orientations=6, transform=None,
    method __getitem__ (line 10) | def __getitem__(self, index):
    method __len__ (line 21) | def __len__(self):

FILE: cycada/data/synthia.py
  function syn_relabel (line 9) | def syn_relabel(arr):
  class SYNTHIAParams (line 16) | class SYNTHIAParams(DatasetParams):
  class SYNTHIA (line 26) | class SYNTHIA(data.Dataset):
    method __init__ (line 28) | def __init__(self, root, num_cls=19, split='train', remap_labels=True,...
    method collect_ids (line 40) | def collect_ids(self):
    method img_path (line 48) | def img_path(self, filename):
    method label_path (line 56) | def label_path(self, filename):
    method __getitem__ (line 64) | def __getitem__(self, index, debug=False):
    method __len__ (line 87) | def __len__(self):

FILE: cycada/data/util.py
  function maybe_download (line 57) | def maybe_download(url, dest):
  function download (line 66) | def download(url, dest):

FILE: cycada/models/MDAN.py
  class GradientReversalLayer (line 13) | class GradientReversalLayer(torch.autograd.Function):
    method forward (line 19) | def forward(self, inputs):
    method backward (line 22) | def backward(self, grad_output):
  class MDANet (line 28) | class MDANet(nn.Module):
    method __init__ (line 33) | def __init__(self, configs):
    method forward (line 54) | def forward(self, sinputs_syn, sinputs_gta, tinputs):
    method inference (line 94) | def inference(self, inputs):

FILE: cycada/models/adda_net.py
  class AddaNet (line 10) | class AddaNet(nn.Module):
    method __init__ (line 12) | def __init__(self, num_cls=10, model='LeNet', src_weights_init=None,
    method forward (line 30) | def forward(self, x_s, x_t):
    method setup_net (line 44) | def setup_net(self):
    method load (line 61) | def load(self, init_path):
    method load_src_net (line 66) | def load_src_net(self, init_path):
    method save (line 72) | def save(self, out_path):
    method save_tgt_net (line 75) | def save_tgt_net(self, out_path):

FILE: cycada/models/drn.py
  function conv3x3 (line 20) | def conv3x3(in_planes, out_planes, stride=1, padding=1, dilation=1):
  class BasicBlock (line 25) | class BasicBlock(nn.Module):
    method __init__ (line 28) | def __init__(self, inplanes, planes, stride=1, downsample=None,
    method forward (line 42) | def forward(self, x):
  class Bottleneck (line 61) | class Bottleneck(nn.Module):
    method __init__ (line 64) | def __init__(self, inplanes, planes, stride=1, downsample=None,
    method forward (line 79) | def forward(self, x):
  class DRN (line 102) | class DRN(nn.Module):
    method __init__ (line 110) | def __init__(self, block, layers, num_cls=1000,
    method _make_layer (line 175) | def _make_layer(self, block, planes, blocks, stride=1, dilation=1,
    method forward (line 199) | def forward(self, x):
  function drn26 (line 252) | def drn26(pretrained=True, finetune=False, out_map=True, **kwargs):
  function drn42 (line 267) | def drn42(pretrained=False, finetune=False, out_map=True, **kwargs):
  function drn58 (line 275) | def drn58(pretrained=False, **kwargs):

FILE: cycada/models/fcn8s.py
  function get_upsample_filter (line 14) | def get_upsample_filter(size):
  class Bilinear (line 27) | class Bilinear(nn.Module):
    method __init__ (line 29) | def __init__(self, factor, num_channels):
    method forward (line 38) | def forward(self, x):
  class VGG16_FCN8s (line 43) | class VGG16_FCN8s(nn.Module):
    method __init__ (line 51) | def __init__(self, num_cls=19, pretrained=True, weights_init=None,
    method load_base_vgg (line 86) | def load_base_vgg(self, weights_state_dict):
    method load_vgg_head (line 90) | def load_vgg_head(self, weights_state_dict):
    method get_dict_by_prefix (line 94) | def get_dict_by_prefix(self, weights_state_dict, prefix):
    method load_weights (line 99) | def load_weights(self, weights_state_dict):
    method split_vgg_head (line 103) | def split_vgg_head(self):
    method forward (line 107) | def forward(self, x):
    method load_base_weights (line 142) | def load_base_weights(self):
  class VGG16_FCN8s_caffe (line 161) | class VGG16_FCN8s_caffe(VGG16_FCN8s):
    method load_base_weights (line 171) | def load_base_weights(self):
  class Discriminator (line 188) | class Discriminator(nn.Module):
    method __init__ (line 189) | def __init__(self, input_dim=4096, output_dim=2, pretrained=False, wei...
    method forward (line 206) | def forward(self, x):
    method load_weights (line 210) | def load_weights(self, weights):
  class Transform_Module (line 215) | class Transform_Module(nn.Module):
    method __init__ (line 216) | def __init__(self, input_dim=4096):
    method forward (line 229) | def forward(self, x):
  function init_eye (line 234) | def init_eye(tensor):
  function _crop (line 241) | def _crop(input, shape, offset=0):
  function make_layers (line 246) | def make_layers(cfg, batch_norm=False):

FILE: cycada/models/models.py
  function register_model (line 4) | def register_model(name):
  function get_model (line 11) | def get_model(name, num_cls=10, **args):

FILE: cycada/models/task_net.py
  class TaskNet (line 8) | class TaskNet(nn.Module):
    method __init__ (line 15) | def __init__(self, num_cls=10, weights_init=None):
    method forward (line 25) | def forward(self, x, with_ft=False):
    method setup_net (line 35) | def setup_net(self):
    method load (line 39) | def load(self, init_path):
    method save (line 43) | def save(self, out_path):
  class LeNet (line 47) | class LeNet(TaskNet):
    method setup_net (line 55) | def setup_net(self):
  class DTNClassifier (line 76) | class DTNClassifier(TaskNet):
    method setup_net (line 84) | def setup_net(self):

FILE: cycada/models/util.py
  function init_weights (line 4) | def init_weights(obj):

FILE: cycada/tools/train_adda_net.py
  function train (line 21) | def train(loader_src, loader_tgt, net, opt_net, opt_dis, epoch):
  function train_adda (line 118) | def train_adda(src, tgt, model, num_cls, num_epoch=200,

FILE: cycada/tools/train_task_net.py
  function train_epoch (line 22) | def train_epoch(loader, net, opt_net, epoch):
  function train (line 55) | def train(data, datadir, model, num_cls, outdir='',

FILE: cycada/tools/util.py
  function make_variable (line 7) | def make_variable(tensor, volatile=False, requires_grad=True):
  function pairwise_distance (line 15) | def pairwise_distance(x, y):
  function gaussian_kernel_matrix (line 30) | def gaussian_kernel_matrix(x, y, sigmas):
  function maximum_mean_discrepancy (line 40) | def maximum_mean_discrepancy(x, y, kernel=gaussian_kernel_matrix):
  function mmd_loss (line 48) | def mmd_loss(source_features, target_features):

FILE: cycada/transforms.py
  class RandomCrop (line 17) | class RandomCrop(object):
    method __init__ (line 23) | def __init__(self, size):
    method __call__ (line 29) | def __call__(self, tensors):
  class HalfCrop (line 48) | class HalfCrop(object):
    method __call__ (line 54) | def __call__(self, tensors):
  class RandomHorizontalFlip (line 65) | class RandomHorizontalFlip(object):
    method __call__ (line 69) | def __call__(self, tensors):
  function augment_collate (line 79) | def augment_collate(batch, crop=None, halfcrop=None, flip=True, resize=N...

FILE: cycada/util.py
  class TqdmHandler (line 13) | class TqdmHandler(logging.StreamHandler):
    method __init__ (line 15) | def __init__(self):
    method emit (line 18) | def emit(self, record):
  function config_logging (line 23) | def config_logging(logfile=None):
  function to_tensor_raw (line 35) | def to_tensor_raw(im):
  function safe_load_state_dict (line 39) | def safe_load_state_dict(net, state_dict):
  function step_lr (line 66) | def step_lr(optimizer, mult):

FILE: cyclegan/data/__init__.py
  function CreateDataLoader (line 10) | def CreateDataLoader(opt):
  function CreateDataset (line 17) | def CreateDataset(opt):
  class CustomDatasetDataLoader (line 39) | class CustomDatasetDataLoader(BaseDataLoader):
    method name (line 40) | def name(self):
    method initialize (line 43) | def initialize(self, opt):
    method load_data (line 52) | def load_data(self):
    method __len__ (line 55) | def __len__(self):
    method __iter__ (line 58) | def __iter__(self):

FILE: cyclegan/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():

FILE: cyclegan/data/base_dataset.py
  class BaseDataset (line 8) | class BaseDataset(data.Dataset):
    method __init__ (line 9) | def __init__(self):
    method name (line 12) | def name(self):
    method initialize (line 15) | def initialize(self, opt):
  function get_transform (line 20) | def get_transform(opt):
  function get_label_transform (line 46) | def get_label_transform(opt):
  function __scale_width (line 71) | def __scale_width(img, target_width):
  function to_tensor_raw (line 80) | def to_tensor_raw(im):

FILE: cyclegan/data/cityscapes.py
  function remap_labels_to_train_ids (line 18) | def remap_labels_to_train_ids(arr):

FILE: cyclegan/data/gta5_cityscapes.py
  class GTAVCityscapesDataset (line 57) | class GTAVCityscapesDataset(BaseDataset):
    method initialize (line 58) | def initialize(self, opt):
    method __getitem__ (line 83) | def __getitem__(self, index):
    method __len__ (line 134) | def __len__(self):
    method name (line 137) | def name(self):

FILE: cyclegan/data/gta_synthia_cityscapes.py
  function syn_relabel (line 56) | def syn_relabel(arr):
  class GTASynthiaCityscapesDataset (line 63) | class GTASynthiaCityscapesDataset(BaseDataset):
    method initialize (line 64) | def initialize(self, opt):
    method __getitem__ (line 98) | def __getitem__(self, index):
    method __len__ (line 160) | def __len__(self):
    method name (line 163) | def name(self):

FILE: cyclegan/data/image_folder.py
  function is_image_file (line 21) | def is_image_file(filename):
  function make_cs_labels (line 24) | def make_cs_labels(dir):
  function make_dataset (line 37) | def make_dataset(dir):
  function load_labels (line 49) | def load_labels(dir, images):
  function default_loader (line 64) | def default_loader(path):
  class ImageFolder (line 68) | class ImageFolder(data.Dataset):
    method __init__ (line 70) | def __init__(self, root, transform=None, return_paths=False,
    method __getitem__ (line 84) | def __getitem__(self, index):
    method __len__ (line 94) | def __len__(self):

FILE: cyclegan/data/synthia_cityscapes.py
  function syn_relabel (line 57) | def syn_relabel(arr):
  class SynthiaCityscapesDataset (line 64) | class SynthiaCityscapesDataset(BaseDataset):
    method initialize (line 65) | def initialize(self, opt):
    method __getitem__ (line 90) | def __getitem__(self, index):
    method __len__ (line 137) | def __len__(self):
    method name (line 140) | def name(self):

FILE: cyclegan/models/__init__.py
  function create_model (line 3) | def create_model(opt):

FILE: cyclegan/models/base_model.py
  class BaseModel (line 9) | class BaseModel():
    method name (line 10) | def name(self):
    method initialize (line 13) | def initialize(self, opt):
    method set_input (line 26) | def set_input(self, input):
    method forward (line 29) | def forward(self):
    method setup (line 33) | def setup(self, opt):
    method eval (line 42) | def eval(self):
    method test (line 50) | def test(self):
    method get_image_paths (line 55) | def get_image_paths(self):
    method optimize_parameters (line 58) | def optimize_parameters(self):
    method update_learning_rate (line 62) | def update_learning_rate(self):
    method get_current_visuals (line 69) | def get_current_visuals(self):
    method get_current_losses (line 77) | def get_current_losses(self):
    method save_networks (line 86) | def save_networks(self, which_epoch):
    method __patch_instance_norm_state_dict (line 100) | def __patch_instance_norm_state_dict(self, state_dict, module, keys, i...
    method load_networks (line 111) | def load_networks(self, which_epoch):
    method print_networks (line 130) | def print_networks(self, verbose):
    method set_requires_grad (line 144) | def set_requires_grad(self, nets, requires_grad=False):

FILE: cyclegan/models/cycle_gan_model.py
  class CycleGANModel (line 8) | class CycleGANModel(BaseModel):
    method name (line 9) | def name(self):
    method initialize (line 12) | def initialize(self, opt):
    method set_input (line 64) | def set_input(self, input):
    method forward (line 70) | def forward(self):
    method backward_D_basic (line 77) | def backward_D_basic(self, netD, real, fake):
    method backward_D_A (line 90) | def backward_D_A(self):
    method backward_D_B (line 94) | def backward_D_B(self):
    method backward_G (line 98) | def backward_G(self):
    method optimize_parameters (line 126) | def optimize_parameters(self):

FILE: cyclegan/models/cycle_gan_semantic_model.py
  class CycleGANSemanticModel (line 15) | class CycleGANSemanticModel(BaseModel):
    method name (line 16) | def name(self):
    method initialize (line 19) | def initialize(self, opt):
    method set_input (line 90) | def set_input(self, input):
    method forward (line 101) | def forward(self):
    method backward_D_basic (line 117) | def backward_D_basic(self, netD, real, fake):
    method backward_PixelCLS (line 130) | def backward_PixelCLS(self):
    method backward_D_A (line 137) | def backward_D_A(self):
    method backward_D_B (line 141) | def backward_D_B(self):
    method backward_G (line 145) | def backward_G(self, opt):
    method optimize_parameters (line 182) | def optimize_parameters(self, opt):

FILE: cyclegan/models/multi_cycle_gan_semantic_model.py
  class CycleGANSemanticModel (line 15) | class CycleGANSemanticModel(BaseModel):
    method name (line 16) | def name(self):
    method initialize (line 19) | def initialize(self, opt):
    method set_input (line 193) | def set_input(self, input):
    method forward (line 206) | def forward(self, opt):
    method backward_D_basic (line 242) | def backward_D_basic(self, netD, real, fake, SAD=False):
    method backward_D_A (line 259) | def backward_D_A(self, Shared_DT):
    method backward_D_B (line 273) | def backward_D_B(self):
    method backward_D (line 282) | def backward_D(self, which_D):
    method backward_G (line 301) | def backward_G(self, opt):
    method backward_HF_CCD (line 383) | def backward_HF_CCD(self, opt):
    method optimize_parameters (line 409) | def optimize_parameters(self, opt):

FILE: cyclegan/models/networks.py
  function get_norm_layer (line 14) | def get_norm_layer(norm_type='instance'):
  function get_scheduler (line 26) | def get_scheduler(optimizer, opt):
  function init_weights (line 42) | def init_weights(net, init_type='normal', gain=0.02):
  function init_net (line 66) | def init_net(net, init_type='normal', gpu_ids=[]):
  function print_network (line 75) | def print_network(net):
  function define_G (line 83) | def define_G(input_nc, output_nc, ngf, which_model_netG, norm='batch', u...
  function define_D (line 100) | def define_D(input_nc, ndf, which_model_netD,
  function define_C (line 117) | def define_C(output_nc, ndf, init_type='normal', gpu_ids=[]):
  class GANLoss (line 135) | class GANLoss(nn.Module):
    method __init__ (line 136) | def __init__(self, use_lsgan=True, target_real_label=1.0, target_fake_...
    method get_target_tensor (line 145) | def get_target_tensor(self, input, target_is_real):
    method __call__ (line 152) | def __call__(self, input, target_is_real):
  class ResnetGenerator (line 161) | class ResnetGenerator(nn.Module):
    method __init__ (line 162) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 205) | def forward(self, input):
  class ResnetBlock (line 210) | class ResnetBlock(nn.Module):
    method __init__ (line 211) | def __init__(self, dim, padding_type, norm_layer, use_dropout, use_bias):
    method build_conv_block (line 215) | def build_conv_block(self, dim, padding_type, norm_layer, use_dropout,...
    method forward (line 247) | def forward(self, x):
  class UnetGenerator (line 256) | class UnetGenerator(nn.Module):
    method __init__ (line 257) | def __init__(self, input_nc, output_nc, num_downs, ngf=64,
    method forward (line 273) | def forward(self, input):
  class UnetSkipConnectionBlock (line 280) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 281) | def __init__(self, outer_nc, inner_nc, input_nc=None,
    method forward (line 326) | def forward(self, x):
  class NLayerDiscriminator (line 334) | class NLayerDiscriminator(nn.Module):
    method __init__ (line 335) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method forward (line 377) | def forward(self, input):
  class PixelDiscriminator (line 381) | class PixelDiscriminator(nn.Module):
    method __init__ (line 382) | def __init__(self, input_nc, ndf=64, norm_layer=nn.BatchNorm2d, use_si...
    method forward (line 402) | def forward(self, input):
  class Classifier (line 406) | class Classifier(nn.Module):
    method __init__ (line 407) | def __init__(self, input_nc, ndf, norm_layer=nn.BatchNorm2d):
    method forward (line 436) | def forward(self, x):

FILE: cyclegan/models/test_model.py
  class TestModel (line 5) | class TestModel(BaseModel):
    method name (line 6) | def name(self):
    method initialize (line 9) | def initialize(self, opt):
    method set_input (line 37) | def set_input(self, input):
    method forward (line 42) | def forward(self):

FILE: cyclegan/options/base_options.py
  class BaseOptions (line 8) | class BaseOptions():
    method __init__ (line 9) | def __init__(self):
    method initialize (line 13) | def initialize(self):
    method parse (line 77) | def parse(self):

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

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

FILE: cyclegan/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: cyclegan/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: cyclegan/util/image_pool.py
  class ImagePool (line 5) | class ImagePool():
    method __init__ (line 6) | def __init__(self, pool_size):
    method query (line 12) | def query(self, images):

FILE: cyclegan/util/util.py
  function tensor2im (line 12) | def tensor2im(input_image, imtype=np.uint8):
  function diagnose_network (line 35) | def diagnose_network(net, name='network'):
  function save_image (line 48) | def save_image(image_numpy, image_path):
  function print_numpy (line 53) | def print_numpy(x, val=True, shp=False):
  function mkdirs (line 63) | def mkdirs(paths):
  function mkdir (line 71) | def mkdir(path):

FILE: cyclegan/util/visualizer.py
  function save_images (line 10) | def save_images(image_dir, visuals, image_path, aspect_ratio=1.0, width=...
  class Visualizer (line 26) | class Visualizer():
    method __init__ (line 27) | def __init__(self, opt):
    method reset (line 49) | def reset(self):
    method display_current_results (line 53) | def display_current_results(self, visuals, epoch, save_result):
    method plot_current_losses (line 119) | def plot_current_losses(self, epoch, counter_ratio, opt, losses):
    method print_current_losses (line 135) | def print_current_losses(self, epoch, i, losses, t, t_data):

FILE: scripts/eval_fcn.py
  function fmt_array (line 26) | def fmt_array(arr, fmt=','):
  function fast_hist (line 31) | def fast_hist(a, b, n):
  function result_stats (line 36) | def result_stats(hist):
  function main (line 57) | def main(path, dataset, datadir, model, gpu, num_cls, batch_size, loadSi...

FILE: scripts/train_fcn.py
  function to_tensor_raw (line 25) | def to_tensor_raw(im):
  function roundrobin_infinite (line 29) | def roundrobin_infinite(*loaders):
  function supervised_loss (line 43) | def supervised_loss(score, label, weights=None):
  function main (line 78) | def main(output, dataset, datadir, batch_size, lr, step, iterations,

FILE: scripts/train_fcn_adda.py
  function check_label (line 25) | def check_label(label, num_cls):
  function forward_pass (line 40) | def forward_pass(net, discriminator, im, requires_grad=False, discrim_fe...
  function supervised_loss (line 53) | def supervised_loss(score, label, weights=None):
  function discriminator_loss (line 59) | def discriminator_loss(score, target_val, lsgan=False):
  function fast_hist (line 69) | def fast_hist(a, b, n):
  function seg_accuracy (line 74) | def seg_accuracy(score, label, num_cls):
  function main (line 112) | def main(output, dataset, datadir, lr, momentum, snapshot, downscale, cl...

FILE: scripts/train_fcn_mdan.py
  function to_tensor_raw (line 29) | def to_tensor_raw(im):
  function roundrobin_infinite (line 33) | def roundrobin_infinite(*loaders):
  function multi_source_infinite (line 47) | def multi_source_infinite(loaders, target_loader):
  function supervised_loss (line 64) | def supervised_loss(score, label, weights=None):
  function main (line 96) | def main(output, dataset, target_name, datadir, batch_size, lr, iterations,