SYMBOL INDEX (316 symbols across 38 files)

FILE: data/__init__.py
  function find_dataset_using_name (line 11) | def find_dataset_using_name(dataset_name):
  function get_option_setter (line 36) | def get_option_setter(dataset_name):
  function create_dataloader (line 41) | def create_dataloader(opt):

FILE: data/ade20k_dataset.py
  class ADE20KDataset (line 10) | class ADE20KDataset(Pix2pixDataset):
    method modify_commandline_options (line 13) | def modify_commandline_options(parser, is_train):
    method get_paths (line 29) | def get_paths(self, opt):
    method postprocess (line 50) | def postprocess(self, input_dict):

FILE: data/base_dataset.py
  class BaseDataset (line 13) | class BaseDataset(data.Dataset):
    method __init__ (line 14) | def __init__(self):
    method modify_commandline_options (line 18) | def modify_commandline_options(parser, is_train):
    method initialize (line 21) | def initialize(self, opt):
  function get_params (line 25) | def get_params(opt, size):
  function get_transform (line 47) | def get_transform(opt, params, method=Image.BICUBIC, normalize=True, toT...
  function normalize (line 81) | def normalize():
  function __resize (line 85) | def __resize(img, w, h, method=Image.BICUBIC):
  function __make_power_2 (line 89) | def __make_power_2(img, base, method=Image.BICUBIC):
  function __scale_width (line 98) | def __scale_width(img, target_width, method=Image.BICUBIC):
  function __scale_shortside (line 107) | def __scale_shortside(img, target_width, method=Image.BICUBIC):
  function __crop (line 118) | def __crop(img, pos, size):
  function __flip (line 125) | def __flip(img, flip):

FILE: data/cityscapes_dataset.py
  class CityscapesDataset (line 11) | class CityscapesDataset(Pix2pixDataset):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train):
    method get_paths (line 27) | def get_paths(self, opt):
    method paths_match (line 45) | def paths_match(self, path1, path2):

FILE: data/coco_dataset.py
  class CocoDataset (line 11) | class CocoDataset(Pix2pixDataset):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train):
    method get_paths (line 30) | def get_paths(self, opt):

FILE: data/custom_dataset.py
  class CustomDataset (line 10) | class CustomDataset(Pix2pixDataset):
    method modify_commandline_options (line 17) | def modify_commandline_options(parser, is_train):
    method get_paths (line 35) | def get_paths(self, opt):

FILE: data/deepfashion_dataset.py
  class DeepfashionDataset (line 11) | class DeepfashionDataset(Pix2pixDataset):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train):
    method get_paths (line 24) | def get_paths(self, opt):

FILE: data/facades_dataset.py
  class FacadesDataset (line 11) | class FacadesDataset(Pix2pixDataset):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train):
    method get_paths (line 27) | def get_paths(self, opt):

FILE: data/image_folder.py
  function is_image_file (line 22) | def is_image_file(filename):
  function make_dataset_rec (line 26) | def make_dataset_rec(dir, images):
  function make_dataset (line 36) | def make_dataset(dir, recursive=False, read_cache=False, write_cache=Fal...
  function default_loader (line 67) | def default_loader(path):
  class ImageFolder (line 71) | class ImageFolder(data.Dataset):
    method __init__ (line 73) | def __init__(self, root, transform=None, return_paths=False,
    method __getitem__ (line 87) | def __getitem__(self, index):
    method __len__ (line 97) | def __len__(self):

FILE: data/pix2pix_dataset.py
  class Pix2pixDataset (line 12) | class Pix2pixDataset(BaseDataset):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train):
    method initialize (line 19) | def initialize(self, opt):
    method get_paths (line 39) | def get_paths(self, opt):
    method paths_match (line 46) | def paths_match(self, path1, path2):
    method __getitem__ (line 51) | def __getitem__(self, index):
    method postprocess (line 91) | def postprocess(self, input_dict):
    method __len__ (line 94) | def __len__(self):

FILE: docs/b5m.js
  function f (line 1) | function f(a,b){return u.call(a,b)}
  function g (line 1) | function g(a){return"[object Array]"===w.call(a)}
  function i (line 1) | function i(a,b){var c=document.getElementsByTagName("head")[0],d=documen...
  function j (line 1) | function j(a){for(var b=0,c=a.length;c>b;b++)if(!f(x,a[b]))return!1;retu...
  function l (line 1) | function l(a){if(a){"string"==typeof a&&(a=[a]);for(var b=0,c=a.length;c...
  function m (line 1) | function m(b){for(var c=b.dependencies||[],d=[],e=0,f=c.length;f>e;e++)d...
  function n (line 1) | function n(a,b){x[a]=b,q(),s()}
  function o (line 1) | function o(a){if(a){var b=a.name;f(B,b)||(B[b]=!0,A.push(a))}}
  function p (line 1) | function p(a){if(!D){D=!0,"undefined"!=typeof a&&a||(a=y);var b=a.shift(...
  function q (line 1) | function q(a){"undefined"!=typeof a&&a||(a=A);for(var b,c=-1;++c<a.lengt...
  function r (line 1) | function r(b){for(var c=b.dependencies||[],d=[],e=0,f=c.length;f>e;e++)d...
  function s (line 1) | function s(a){if("undefined"!=typeof a&&a||(a=C),0!==a.length)for(var b,...
  function t (line 1) | function t(a){C.push(a)}

FILE: docs/lib.js
  function map (line 139) | function map(list, func) {
  function filter (line 146) | function filter(list, func) {
  function getElem (line 156) | function getElem(elem) {
  function hasClass (line 168) | function hasClass(elem, className) {
  function getElementsByClass (line 172) | function getElementsByClass(className, tagName, parentNode) {
  function listen (line 182) | function listen(event, elem, func) {
  function mlisten (line 192) | function mlisten(event, elem_list, func) {
  function W3CDOM_Event (line 196) | function W3CDOM_Event(currentTarget) {
  function isUndefined (line 205) | function isUndefined(v) {

FILE: docs/popup.js
  function raw_popup (line 6) | function raw_popup(url, target, features) {
  function link_popup (line 15) | function link_popup(src, features) {
  function event_popup (line 21) | function event_popup(e) {
  function event_popup_features (line 28) | function event_popup_features(features) {

FILE: models/__init__.py
  function find_model_using_name (line 10) | def find_model_using_name(model_name):
  function get_option_setter (line 34) | def get_option_setter(model_name):
  function create_model (line 39) | def create_model(opt):

FILE: models/networks/__init__.py
  function find_network_using_name (line 15) | def find_network_using_name(target_network_name, filename):
  function modify_commandline_options (line 26) | def modify_commandline_options(parser, is_train):
  function create_network (line 40) | def create_network(cls, opt):
  function define_G (line 50) | def define_G(opt):
  function define_D (line 55) | def define_D(opt):
  function define_E (line 60) | def define_E(opt):

FILE: models/networks/architecture.py
  class SPADEV2ResnetBlock (line 22) | class SPADEV2ResnetBlock(nn.Module):
    method __init__ (line 23) | def __init__(self, fin, fout, opt, group_num=8):
    method forward (line 57) | def forward(self, x, seg):
    method shortcut (line 66) | def shortcut(self, x, seg):
    method actvn (line 73) | def actvn(self, x):
  class SPADEResnetBlock (line 76) | class SPADEResnetBlock(nn.Module):
    method __init__ (line 77) | def __init__(self, fin, fout, opt):
    method forward (line 105) | def forward(self, x, seg):
    method shortcut (line 115) | def shortcut(self, x, seg):
    method actvn (line 122) | def actvn(self, x):
  class ResnetBlock (line 128) | class ResnetBlock(nn.Module):
    method __init__ (line 129) | def __init__(self, dim, norm_layer, activation=nn.ReLU(False), kernel_...
    method forward (line 141) | def forward(self, x):
  class VGG19 (line 148) | class VGG19(torch.nn.Module):
    method __init__ (line 149) | def __init__(self, vgg_path,requires_grad=False):
    method forward (line 179) | def forward(self, X):

FILE: models/networks/base_network.py
  class BaseNetwork (line 10) | class BaseNetwork(nn.Module):
    method __init__ (line 11) | def __init__(self):
    method modify_commandline_options (line 15) | def modify_commandline_options(parser, is_train):
    method print_network (line 18) | def print_network(self):
    method init_weights (line 28) | def init_weights(self, init_type='normal', gain=0.02):

FILE: models/networks/discriminator.py
  class MultiscaleDiscriminator (line 14) | class MultiscaleDiscriminator(BaseNetwork):
    method modify_commandline_options (line 16) | def modify_commandline_options(parser, is_train):
    method __init__ (line 30) | def __init__(self, opt):
    method create_single_discriminator (line 38) | def create_single_discriminator(self, opt):
    method downsample (line 46) | def downsample(self, input):
    method forward (line 53) | def forward(self, input):
  class NLayerDiscriminator (line 67) | class NLayerDiscriminator(BaseNetwork):
    method modify_commandline_options (line 69) | def modify_commandline_options(parser, is_train):
    method __init__ (line 74) | def __init__(self, opt):
    method compute_D_input_nc (line 102) | def compute_D_input_nc(self, opt):
    method forward (line 110) | def forward(self, input):

FILE: models/networks/encoder.py
  class ConvEncoder (line 13) | class ConvEncoder(BaseNetwork):
    method __init__ (line 16) | def __init__(self, opt):
    method forward (line 42) | def forward(self, x):
  class FcEncoder (line 58) | class FcEncoder(BaseNetwork):
    method __init__ (line 61) | def __init__(self, opt):
    method forward (line 83) | def forward(self, x):

FILE: models/networks/generator.py
  class SPADEBaseGenerator (line 14) | class SPADEBaseGenerator(BaseNetwork):
    method modify_commandline_options (line 16) | def modify_commandline_options(parser, is_train):
    method __init__ (line 24) | def __init__(self, opt):
    method compute_latent_vector_size (line 59) | def compute_latent_vector_size(self, opt):
    method forward (line 75) | def forward(self, input, z=None):
  class ADE20KGenerator (line 119) | class ADE20KGenerator(BaseNetwork):
    method modify_commandline_options (line 121) | def modify_commandline_options(parser, is_train):
    method __init__ (line 129) | def __init__(self, opt):
    method compute_latent_vector_size (line 155) | def compute_latent_vector_size(self, opt):
    method forward (line 171) | def forward(self, input, z=None):
  class CityscapesGenerator (line 219) | class CityscapesGenerator(BaseNetwork):
    method modify_commandline_options (line 221) | def modify_commandline_options(parser, is_train):
    method __init__ (line 229) | def __init__(self, opt):
    method compute_latent_vector_size (line 255) | def compute_latent_vector_size(self, opt):
    method forward (line 271) | def forward(self, input, z=None):
  class DeepFashionGenerator (line 321) | class DeepFashionGenerator(BaseNetwork):
    method modify_commandline_options (line 323) | def modify_commandline_options(parser, is_train):
    method __init__ (line 331) | def __init__(self, opt):
    method compute_latent_vector_size (line 360) | def compute_latent_vector_size(self, opt):
    method forward (line 376) | def forward(self, input, z=None):
  class Pix2PixHDGenerator (line 422) | class Pix2PixHDGenerator(BaseNetwork):
    method modify_commandline_options (line 424) | def modify_commandline_options(parser, is_train):
    method __init__ (line 436) | def __init__(self, opt):
    method forward (line 484) | def forward(self, input, z=None):

FILE: models/networks/loss.py
  class GANLoss (line 16) | class GANLoss(nn.Module):
    method __init__ (line 17) | def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=...
    method get_target_tensor (line 39) | def get_target_tensor(self, input, target_is_real):
    method get_zero_tensor (line 51) | def get_zero_tensor(self, input):
    method loss (line 57) | def loss(self, input, target_is_real, for_discriminator=True):
    method __call__ (line 84) | def __call__(self, input, target_is_real, for_discriminator=True):
  class VGGLoss (line 102) | class VGGLoss(nn.Module):
    method __init__ (line 103) | def __init__(self, gpu_ids, vgg_path=None):
    method forward (line 109) | def forward(self, x, y):
  class KLDLoss (line 118) | class KLDLoss(nn.Module):
    method forward (line 119) | def forward(self, mu, logvar):

FILE: models/networks/normalization.py
  function get_nonspade_norm_layer (line 15) | def get_nonspade_norm_layer(opt, norm_type='instance'):
  class GROUP_SPADE (line 69) | class GROUP_SPADE(nn.Module):
    method __init__ (line 70) | def __init__(self, config_text, norm_nc, label_nc, group_num=0, use_in...
    method forward (line 129) | def forward(self, x, segmap):
  class SPADE (line 145) | class SPADE(nn.Module):
    method __init__ (line 146) | def __init__(self, config_text, norm_nc, label_nc):
    method forward (line 175) | def forward(self, x, segmap):

FILE: models/networks/sync_batchnorm/batchnorm.py
  function _sum_ft (line 37) | def _sum_ft(tensor):
  function _unsqueeze_ft (line 42) | def _unsqueeze_ft(tensor):
  class _SynchronizedBatchNorm (line 51) | class _SynchronizedBatchNorm(_BatchNorm):
    method __init__ (line 52) | def __init__(self, num_features, eps=1e-5, momentum=0.1, affine=True):
    method forward (line 63) | def forward(self, input):
    method __data_parallel_replicate__ (line 95) | def __data_parallel_replicate__(self, ctx, copy_id):
    method _data_parallel_master (line 105) | def _data_parallel_master(self, intermediates):
    method _compute_mean_std (line 128) | def _compute_mean_std(self, sum_, ssum, size):
  class SynchronizedBatchNorm1d (line 148) | class SynchronizedBatchNorm1d(_SynchronizedBatchNorm):
    method _check_input_dim (line 204) | def _check_input_dim(self, input):
  class SynchronizedBatchNorm2d (line 211) | class SynchronizedBatchNorm2d(_SynchronizedBatchNorm):
    method _check_input_dim (line 267) | def _check_input_dim(self, input):
  class SynchronizedBatchNorm3d (line 274) | class SynchronizedBatchNorm3d(_SynchronizedBatchNorm):
    method _check_input_dim (line 331) | def _check_input_dim(self, input):
  function patch_sync_batchnorm (line 339) | def patch_sync_batchnorm():
  function convert_model (line 353) | def convert_model(module):

FILE: models/networks/sync_batchnorm/batchnorm_reimpl.py
  class BatchNorm2dReimpl (line 18) | class BatchNorm2dReimpl(nn.Module):
    method __init__ (line 27) | def __init__(self, num_features, eps=1e-5, momentum=0.1):
    method reset_running_stats (line 39) | def reset_running_stats(self):
    method reset_parameters (line 43) | def reset_parameters(self):
    method forward (line 48) | def forward(self, input_):

FILE: models/networks/sync_batchnorm/comm.py
  class FutureResult (line 18) | class FutureResult(object):
    method __init__ (line 21) | def __init__(self):
    method put (line 26) | def put(self, result):
    method get (line 32) | def get(self):
  class SlavePipe (line 46) | class SlavePipe(_SlavePipeBase):
    method run_slave (line 49) | def run_slave(self, msg):
  class SyncMaster (line 56) | class SyncMaster(object):
    method __init__ (line 67) | def __init__(self, master_callback):
    method __getstate__ (line 78) | def __getstate__(self):
    method __setstate__ (line 81) | def __setstate__(self, state):
    method register_slave (line 84) | def register_slave(self, identifier):
    method run_master (line 102) | def run_master(self, master_msg):
    method nr_slaves (line 136) | def nr_slaves(self):

FILE: models/networks/sync_batchnorm/replicate.py
  class CallbackContext (line 23) | class CallbackContext(object):
  function execute_replication_callbacks (line 27) | def execute_replication_callbacks(modules):
  class DataParallelWithCallback (line 50) | class DataParallelWithCallback(DataParallel):
    method replicate (line 64) | def replicate(self, module, device_ids):
  function patch_replication_callback (line 70) | def patch_replication_callback(data_parallel):

FILE: models/networks/sync_batchnorm/unittest.py
  class TorchTestCase (line 15) | class TorchTestCase(unittest.TestCase):
    method assertTensorClose (line 16) | def assertTensorClose(self, x, y):

FILE: models/pix2pix_model.py
  class Pix2pixModel (line 12) | class Pix2pixModel(torch.nn.Module):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train):
    method __init__ (line 18) | def __init__(self, opt):
    method forward (line 42) | def forward(self, data, mode):
    method create_optimizers (line 63) | def create_optimizers(self, opt):
    method save (line 82) | def save(self, epoch):
    method initialize_networks (line 92) | def initialize_networks(self, opt):
    method preprocess_input (line 111) | def preprocess_input(self, data):
    method compute_generator_loss (line 135) | def compute_generator_loss(self, input_semantics, real_image):
    method compute_discriminator_loss (line 168) | def compute_discriminator_loss(self, input_semantics, real_image):
    method encode_z (line 185) | def encode_z(self, real_image):
    method generate_fake (line 190) | def generate_fake(self, input_semantics, real_image, compute_kld_loss=...
    method vis_test (line 205) | def vis_test(self, input_semantics, times=1):
    method discriminate (line 214) | def discriminate(self, input_semantics, fake_image, real_image):
    method divide_pred (line 231) | def divide_pred(self, pred):
    method get_edges (line 246) | def get_edges(self, t):
    method reparameterize (line 254) | def reparameterize(self, mu, logvar):
    method use_gpu (line 259) | def use_gpu(self):

FILE: models/smis_model.py
  class SmisModel (line 8) | class SmisModel(torch.nn.Module):
    method modify_commandline_options (line 10) | def modify_commandline_options(parser, is_train):
    method __init__ (line 14) | def __init__(self, opt):
    method forward (line 38) | def forward(self, data, mode):
    method create_optimizers (line 63) | def create_optimizers(self, opt):
    method save (line 83) | def save(self, epoch):
    method initialize_networks (line 94) | def initialize_networks(self, opt):
    method preprocess_input (line 114) | def preprocess_input(self, data):
    method compute_generator_loss (line 139) | def compute_generator_loss(self, input_semantics, real_image):
    method compute_discriminator_loss (line 173) | def compute_discriminator_loss(self, input_semantics, real_image):
    method encode_z (line 190) | def encode_z(self, real_image):
    method trans_img (line 195) | def trans_img(self, input_semantics, real_image):
    method generate_fake (line 241) | def generate_fake(self, input_semantics, real_image, compute_kld_loss=...
    method vis_test (line 257) | def vis_test(self, input_semantics, times=1, test_mask=None):
    method discriminate (line 281) | def discriminate(self, input_semantics, fake_image, real_image):
    method divide_pred (line 298) | def divide_pred(self, pred):
    method get_edges (line 313) | def get_edges(self, t):
    method reparameterize (line 321) | def reparameterize(self, mu, logvar):
    method use_gpu (line 326) | def use_gpu(self):

FILE: options/base_options.py
  class BaseOptions (line 16) | class BaseOptions():
    method __init__ (line 17) | def __init__(self):
    method initialize (line 20) | def initialize(self, parser):
    method gather_options (line 100) | def gather_options(self):
    method print_options (line 131) | def print_options(self, opt):
    method option_file_path (line 143) | def option_file_path(self, opt, makedir=False):
    method save_options (line 150) | def save_options(self, opt):
    method update_options_from_file (line 163) | def update_options_from_file(self, parser, opt):
    method load_options (line 171) | def load_options(self, opt):
    method parse (line 176) | def parse(self, save=False):

FILE: options/test_options.py
  class TestOptions (line 9) | class TestOptions(BaseOptions):
    method initialize (line 10) | def initialize(self, parser):

FILE: options/train_options.py
  class TrainOptions (line 9) | class TrainOptions(BaseOptions):
    method initialize (line 10) | def initialize(self, parser):

FILE: trainers/pix2pix_trainer.py
  class Pix2PixTrainer (line 11) | class Pix2PixTrainer():
    method __init__ (line 18) | def __init__(self, opt):
    method run_generator_one_step (line 40) | def run_generator_one_step(self, data):
    method run_discriminator_one_step (line 49) | def run_discriminator_one_step(self, data):
    method clean_grad (line 57) | def clean_grad(self):
    method get_latest_losses (line 61) | def get_latest_losses(self):
    method get_latest_generated (line 64) | def get_latest_generated(self):
    method update_learning_rate (line 67) | def update_learning_rate(self, epoch):
    method save (line 70) | def save(self, epoch):
    method update_learning_rate (line 77) | def update_learning_rate(self, epoch):

FILE: util/coco.py
  function id2label (line 7) | def id2label(id):

FILE: util/html.py
  class HTML (line 12) | class HTML:
    method __init__ (line 13) | def __init__(self, web_dir, title, refresh=0):
    method get_image_dir (line 34) | def get_image_dir(self):
    method add_header (line 37) | def add_header(self, str):
    method add_table (line 41) | def add_table(self, border=1):
    method add_images (line 45) | def add_images(self, ims, txts, links, width=512):
    method save (line 57) | def save(self):

FILE: util/iter_counter.py
  class IterationCounter (line 12) | class IterationCounter():
    method __init__ (line 13) | def __init__(self, opt, dataset_size):
    method training_epochs (line 33) | def training_epochs(self):
    method record_epoch_start (line 36) | def record_epoch_start(self, epoch):
    method record_one_iteration (line 42) | def record_one_iteration(self):
    method record_epoch_end (line 52) | def record_epoch_end(self):
    method record_current_iter (line 62) | def record_current_iter(self):
    method needs_saving (line 67) | def needs_saving(self):
    method needs_printing (line 70) | def needs_printing(self):
    method needs_displaying (line 73) | def needs_displaying(self):
    method needs_many_test (line 76) | def needs_many_test(self):

FILE: util/util.py
  function save_obj (line 18) | def save_obj(obj, name):
  function load_obj (line 23) | def load_obj(name):
  function copyconf (line 32) | def copyconf(default_opt, **kwargs):
  function tile_images (line 40) | def tile_images(imgs, picturesPerRow=4):
  function tensor2im (line 64) | def tensor2im(image_tensor, imtype=np.uint8, normalize=True, tile=False):
  function tensor2label (line 99) | def tensor2label(label_tensor, n_label, imtype=np.uint8, tile=False):
  function save_image (line 129) | def save_image(image_numpy, image_path, create_dir=False):
  function mkdirs (line 142) | def mkdirs(paths):
  function mkdir (line 150) | def mkdir(path):
  function atoi (line 155) | def atoi(text):
  function natural_keys (line 159) | def natural_keys(text):
  function natural_sort (line 168) | def natural_sort(items):
  function str2bool (line 172) | def str2bool(v):
  function find_class_in_module (line 181) | def find_class_in_module(target_cls_name, module):
  function save_network (line 196) | def save_network(net, label, epoch, opt):
  function load_network (line 204) | def load_network(net, label, epoch, opt):
  function uint82bin (line 218) | def uint82bin(n, count=8):
  function labelcolormap (line 223) | def labelcolormap(N):
  class Colorize (line 263) | class Colorize(object):
    method __init__ (line 264) | def __init__(self, n=35):
    method __call__ (line 269) | def __call__(self, gray_image):

FILE: util/visualizer.py
  class Visualizer (line 19) | class Visualizer():
    method __init__ (line 20) | def __init__(self, opt):
    method display_current_results (line 44) | def display_current_results(self, visuals, epoch, step):
    method plot_current_errors (line 111) | def plot_current_errors(self, errors, step):
    method print_current_errors (line 119) | def print_current_errors(self, epoch, i, errors, t):
    method convert_visuals_to_numpy (line 131) | def convert_visuals_to_numpy(self, visuals):
    method save_images (line 142) | def save_images(self, webpage, visuals, image_path):