SYMBOL INDEX (164 symbols across 20 files)

FILE: data/aligned_dataset.py
  class AlignedDataset (line 6) | class AlignedDataset(BaseDataset):
    method initialize (line 7) | def initialize(self, opt):
    method __getitem__ (line 35) | def __getitem__(self, index):
    method __len__ (line 72) | def __len__(self):
    method name (line 75) | def name(self):

FILE: data/base_data_loader.py
  class BaseDataLoader (line 2) | class BaseDataLoader():
    method __init__ (line 3) | def __init__(self):
    method initialize (line 6) | def initialize(self, opt):
    method load_data (line 10) | def load_data():

FILE: data/base_dataset.py
  class BaseDataset (line 7) | class BaseDataset(data.Dataset):
    method __init__ (line 8) | def __init__(self):
    method name (line 11) | def name(self):
    method initialize (line 14) | def initialize(self, opt):
  function get_params (line 17) | def get_params(opt, size):
  function get_transform (line 33) | def get_transform(opt, params, method=Image.BICUBIC, normalize=True):
  function normalize (line 60) | def normalize():
  function __make_power_2 (line 63) | def __make_power_2(img, base, method=Image.BICUBIC):
  function __scale_width (line 71) | def __scale_width(img, target_width, method=Image.BICUBIC):
  function __crop (line 79) | def __crop(img, pos, size):
  function __flip (line 87) | def __flip(img, flip):

FILE: data/custom_dataset_data_loader.py
  function CreateDataset (line 5) | def CreateDataset(opt):
  class CustomDatasetDataLoader (line 14) | class CustomDatasetDataLoader(BaseDataLoader):
    method name (line 15) | def name(self):
    method initialize (line 18) | def initialize(self, opt):
    method load_data (line 27) | def load_data(self):
    method __len__ (line 30) | def __len__(self):

FILE: data/data_loader.py
  function CreateDataLoader (line 2) | def CreateDataLoader(opt):

FILE: data/image_folder.py
  function is_image_file (line 17) | def is_image_file(filename):
  function make_dataset (line 21) | def make_dataset(dir):
  function default_loader (line 34) | def default_loader(path):
  class ImageFolder (line 38) | class ImageFolder(data.Dataset):
    method __init__ (line 40) | def __init__(self, root, transform=None, return_paths=False,
    method __getitem__ (line 54) | def __getitem__(self, index):
    method __len__ (line 64) | def __len__(self):

FILE: models/base_model.py
  class BaseModel (line 5) | class BaseModel(torch.nn.Module):
    method name (line 6) | def name(self):
    method initialize (line 9) | def initialize(self, opt):
    method set_input (line 16) | def set_input(self, input):
    method forward (line 19) | def forward(self):
    method test (line 23) | def test(self):
    method get_image_paths (line 26) | def get_image_paths(self):
    method optimize_parameters (line 29) | def optimize_parameters(self):
    method get_current_visuals (line 32) | def get_current_visuals(self):
    method get_current_errors (line 35) | def get_current_errors(self):
    method save (line 38) | def save(self, label):
    method save_network (line 42) | def save_network(self, network, network_label, epoch_label, gpu_ids):
    method load_network (line 50) | def load_network(self, network, network_label, epoch_label, save_dir=''):
    method update_learning_rate (line 90) | def update_learning_rate():

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

FILE: models/networks.py
  function weights_init (line 10) | def weights_init(m):
  function get_norm_layer (line 18) | def get_norm_layer(norm_type='instance'):
  function define_G (line 27) | def define_G(input_nc, output_nc, ngf, netG, n_downsample_global=3, n_bl...
  function define_D (line 46) | def define_D(input_nc, ndf, n_layers_D, norm='instance', use_sigmoid=Fal...
  function print_network (line 56) | def print_network(net):
  class GANLoss (line 68) | class GANLoss(nn.Module):
    method __init__ (line 69) | def __init__(self, use_lsgan=True, target_real_label=1.0, target_fake_...
    method get_target_tensor (line 82) | def get_target_tensor(self, input, target_is_real):
    method __call__ (line 100) | def __call__(self, input, target_is_real):
  class VGGLoss (line 112) | class VGGLoss(nn.Module):
    method __init__ (line 113) | def __init__(self, gpu_ids):
    method forward (line 119) | def forward(self, x, y):
  class LocalEnhancer (line 129) | class LocalEnhancer(nn.Module):
    method __init__ (line 130) | def __init__(self, input_nc, output_nc, ngf=32, n_downsample_global=3,...
    method forward (line 167) | def forward(self, input):
  class GlobalGenerator (line 183) | class GlobalGenerator(nn.Module):
    method __init__ (line 184) | def __init__(self, input_nc, output_nc, ngf=64, n_downsampling=3, n_bl...
    method forward (line 210) | def forward(self, input):
  class ResnetBlock (line 214) | class ResnetBlock(nn.Module):
    method __init__ (line 215) | def __init__(self, dim, padding_type, norm_layer, activation=nn.ReLU(T...
    method build_conv_block (line 219) | def build_conv_block(self, dim, padding_type, norm_layer, activation, ...
    method forward (line 251) | def forward(self, x):
  class Encoder (line 255) | class Encoder(nn.Module):
    method __init__ (line 256) | def __init__(self, input_nc, output_nc, ngf=32, n_downsampling=4, norm...
    method forward (line 277) | def forward(self, input, inst):
  class MultiscaleDiscriminator (line 292) | class MultiscaleDiscriminator(nn.Module):
    method __init__ (line 293) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method singleD_forward (line 310) | def singleD_forward(self, model, input):
    method forward (line 319) | def forward(self, input):
  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 375) | def forward(self, input):
  class Vgg19 (line 386) | class Vgg19(torch.nn.Module):
    method __init__ (line 387) | def __init__(self, requires_grad=False):
    method forward (line 409) | def forward(self, X):

FILE: models/pix2pixHD_model.py
  class Pix2PixHDModel (line 9) | class Pix2PixHDModel(BaseModel):
    method name (line 10) | def name(self):
    method init_loss_filter (line 13) | def init_loss_filter(self, use_gan_feat_loss, use_vgg_loss):
    method initialize (line 19) | def initialize(self, opt):
    method encode_input (line 111) | def encode_input(self, label_map, inst_map=None, real_image=None, feat...
    method discriminate (line 144) | def discriminate(self, input_label, test_image, use_pool=False):
    method forward (line 152) | def forward(self, label, inst, image, feat, infer=False):
    method inference (line 195) | def inference(self, label, inst, image=None):
    method sample_features (line 219) | def sample_features(self, inst):
    method encode_features (line 240) | def encode_features(self, image, inst):
    method get_edges (line 262) | def get_edges(self, t):
    method save (line 273) | def save(self, which_epoch):
    method update_fixed_params (line 279) | def update_fixed_params(self):
    method update_learning_rate (line 288) | def update_learning_rate(self):
  class InferenceModel (line 299) | class InferenceModel(Pix2PixHDModel):
    method forward (line 300) | def forward(self, inp):

FILE: models/ui_model.py
  class UIModel (line 11) | class UIModel(BaseModel):
    method name (line 12) | def name(self):
    method initialize (line 15) | def initialize(self, opt):
    method toTensor (line 33) | def toTensor(self, img, normalize=False):
    method load_image (line 41) | def load_image(self, label_path, inst_path, feat_path):
    method reset (line 91) | def reset(self):
    method undo (line 99) | def undo(self):
    method get_edges (line 108) | def get_edges(self, t):
    method change_labels (line 117) | def change_labels(self, click_src, click_tgt):
    method add_strokes (line 152) | def add_strokes(self, click_src, label_tgt, bw, save):
    method add_objects (line 190) | def add_objects(self, click_src, label_tgt, mask, style_id=0):
    method single_forward (line 215) | def single_forward(self, net_input, feat_map):
    method style_forward (line 225) | def style_forward(self, click_pt, style_id=-1):
    method backup_current_state (line 286) | def backup_current_state(self):
    method get_crop_region (line 293) | def get_crop_region(self, idx):
    method update_features (line 309) | def update_features(self, cluster_idx, mask=None, click_pt=None):
    method set_features (line 326) | def set_features(self, idx, feat, cluster_idx):
    method copy_features (line 331) | def copy_features(self, idx_src, idx_tgt):
    method get_current_visuals (line 336) | def get_current_visuals(self, getLabel=False):

FILE: options/base_options.py
  class BaseOptions (line 6) | class BaseOptions():
    method __init__ (line 7) | def __init__(self):
    method initialize (line 11) | def initialize(self):
    method parse (line 65) | def parse(self, save=True):

FILE: options/test_options.py
  class TestOptions (line 3) | class TestOptions(BaseOptions):
    method initialize (line 4) | def initialize(self):

FILE: options/train_options.py
  class TrainOptions (line 3) | class TrainOptions(BaseOptions):
    method initialize (line 4) | def initialize(self):

FILE: run_engine.py
  class Profiler (line 35) | class Profiler(trt.infer.Profiler):
    method __init__ (line 42) | def __init__(self, timing_iter):
    method report_layer_time (line 47) | def report_layer_time(self, layerName, ms):
    method print_layer_times (line 54) | def print_layer_times(self):
  function get_input_output_names (line 62) | def get_input_output_names(trt_engine):
  function create_memory (line 82) | def create_memory(engine, name,  buf, mem, batchsize, inp, inp_idx):
  function time_inference (line 104) | def time_inference(engine, batch_size, inp):
  function convert_to_datatype (line 123) | def convert_to_datatype(v):
  function run_trt_engine (line 134) | def run_trt_engine(engine_file, bs, it):
  function run_onnx (line 138) | def run_onnx(onnx_file, data_type, bs, inp):

FILE: train.py
  function lcm (line 9) | def lcm(a,b): return abs(a * b)/fractions.gcd(a,b) if a and b else 0

FILE: util/html.py
  class HTML (line 6) | class HTML:
    method __init__ (line 7) | def __init__(self, web_dir, title, refresh=0):
    method get_image_dir (line 21) | def get_image_dir(self):
    method add_header (line 24) | def add_header(self, str):
    method add_table (line 28) | def add_table(self, border=1):
    method add_images (line 32) | def add_images(self, ims, txts, links, width=512):
    method save (line 44) | def save(self):

FILE: util/image_pool.py
  class ImagePool (line 4) | class ImagePool():
    method __init__ (line 5) | def __init__(self, pool_size):
    method query (line 11) | def query(self, images):

FILE: util/util.py
  function tensor2im (line 10) | def tensor2im(image_tensor, imtype=np.uint8, normalize=True):
  function tensor2label (line 27) | def tensor2label(label_tensor, n_label, imtype=np.uint8):
  function save_image (line 37) | def save_image(image_numpy, image_path):
  function mkdirs (line 41) | def mkdirs(paths):
  function mkdir (line 48) | def mkdir(path):
  function uint82bin (line 57) | def uint82bin(n, count=8):
  function labelcolormap (line 61) | def labelcolormap(N):
  class Colorize (line 85) | class Colorize(object):
    method __init__ (line 86) | def __init__(self, n=35):
    method __call__ (line 90) | def __call__(self, gray_image):

FILE: util/visualizer.py
  class Visualizer (line 13) | class Visualizer():
    method __init__ (line 14) | def __init__(self, opt):
    method display_current_results (line 37) | def display_current_results(self, visuals, epoch, step):
    method plot_current_errors (line 95) | def plot_current_errors(self, errors, step):
    method print_current_errors (line 102) | def print_current_errors(self, epoch, i, errors, t):
    method save_images (line 113) | def save_images(self, webpage, visuals, image_path):