SYMBOL INDEX (389 symbols across 37 files)

FILE: config.py
  class AttrDict (line 10) | class AttrDict(dict):
    method __init__ (line 13) | def __init__(self, *args, **kwargs):
    method yaml (line 25) | def yaml(self):
    method __repr__ (line 43) | def __repr__(self):
  class Config (line 67) | class Config(AttrDict):
    method __init__ (line 71) | def __init__(self, filename=None, args=None, verbose=False, is_train=T...
  function rsetattr (line 186) | def rsetattr(obj, attr, val):
  function rgetattr (line 192) | def rgetattr(obj, attr, *args):
  function recursive_update (line 202) | def recursive_update(d, u):

FILE: data/__init__.py
  function find_dataset_using_name (line 6) | def find_dataset_using_name(dataset_name):
  function get_option_setter (line 23) | def get_option_setter(dataset_name):
  function create_dataloader (line 28) | def create_dataloader(opt, is_inference):
  function data_sampler (line 46) | def data_sampler(dataset, shuffle, distributed):
  function get_dataloader (line 55) | def get_dataloader(opt, is_inference=False):
  function get_train_val_dataloader (line 60) | def get_train_val_dataloader(opt):

FILE: data/image_dataset.py
  class ImageDataset (line 12) | class ImageDataset():
    method __init__ (line 13) | def __init__(self, opt, input_name):
    method next_image (line 22) | def next_image(self):
    method obtain_inputs (line 38) | def obtain_inputs(self, root):
    method transform_semantic (line 52) | def transform_semantic(self, semantic):
    method trans_image (line 62) | def trans_image(self, image):
    method __len__ (line 69) | def __len__(self):

FILE: data/vox_dataset.py
  function format_for_lmdb (line 13) | def format_for_lmdb(*args):
  class VoxDataset (line 21) | class VoxDataset(Dataset):
    method __init__ (line 22) | def __init__(self, opt, is_inference):
    method get_video_index (line 53) | def get_video_index(self, videos):
    method group_by_key (line 62) | def group_by_key(self, video_list, key):
    method Video_Item (line 68) | def Video_Item(self, video_name):
    method __len__ (line 79) | def __len__(self):
    method __getitem__ (line 82) | def __getitem__(self, index):
    method random_select_frames (line 108) | def random_select_frames(self, video_item):
    method transform_semantic (line 113) | def transform_semantic(self, semantic, frame_index):
    method obtain_seq_index (line 127) | def obtain_seq_index(self, index, num_frames):

FILE: data/vox_video_dataset.py
  class VoxVideoDataset (line 14) | class VoxVideoDataset(VoxDataset):
    method __init__ (line 15) | def __init__(self, opt, is_inference):
    method __len__ (line 23) | def __len__(self):
    method load_next_video (line 26) | def load_next_video(self):
    method random_video (line 61) | def random_video(self, target_video_item):
    method find_crop_norm_ratio (line 71) | def find_crop_norm_ratio(self, source_coeff, target_coeffs):
    method transform_semantic (line 79) | def transform_semantic(self, semantic, frame_index, crop_norm_ratio):
    method obtain_name (line 96) | def obtain_name(self, target_name, source_name):

FILE: generators/base_function.py
  class LayerNorm2d (line 11) | class LayerNorm2d(nn.Module):
    method __init__ (line 12) | def __init__(self, n_out, affine=True):
    method forward (line 21) | def forward(self, x):
  class ADAINHourglass (line 31) | class ADAINHourglass(nn.Module):
    method __init__ (line 32) | def __init__(self, image_nc, pose_nc, ngf, img_f, encoder_layers, deco...
    method forward (line 38) | def forward(self, x, z):
  class ADAINEncoder (line 43) | class ADAINEncoder(nn.Module):
    method __init__ (line 44) | def __init__(self, image_nc, pose_nc, ngf, img_f, layers, nonlinearity...
    method forward (line 55) | def forward(self, x, z):
  class ADAINDecoder (line 64) | class ADAINDecoder(nn.Module):
    method __init__ (line 66) | def __init__(self, pose_nc, ngf, img_f, encoder_layers, decoder_layers...
    method forward (line 84) | def forward(self, x, z):
  class ADAINEncoderBlock (line 92) | class ADAINEncoderBlock(nn.Module):
    method __init__ (line 93) | def __init__(self, input_nc, output_nc, feature_nc, nonlinearity=nn.Le...
    method forward (line 106) | def forward(self, x, z):
  class ADAINDecoderBlock (line 111) | class ADAINDecoderBlock(nn.Module):
    method __init__ (line 112) | def __init__(self, input_nc, output_nc, hidden_nc, feature_nc, use_tra...
    method forward (line 139) | def forward(self, x, z):
    method shortcut (line 146) | def shortcut(self, x, z):
  function spectral_norm (line 151) | def spectral_norm(module, use_spect=True):
  class ADAIN (line 159) | class ADAIN(nn.Module):
    method __init__ (line 160) | def __init__(self, norm_nc, feature_nc):
    method forward (line 175) | def forward(self, x, feature):
  class FineEncoder (line 193) | class FineEncoder(nn.Module):
    method __init__ (line 195) | def __init__(self, image_nc, ngf, img_f, layers, norm_layer=nn.BatchNo...
    method forward (line 206) | def forward(self, x):
  class FineDecoder (line 215) | class FineDecoder(nn.Module):
    method __init__ (line 217) | def __init__(self, image_nc, feature_nc, ngf, img_f, layers, num_block...
    method forward (line 235) | def forward(self, x, z):
  class FirstBlock2d (line 247) | class FirstBlock2d(nn.Module):
    method __init__ (line 251) | def __init__(self, input_nc, output_nc, norm_layer=nn.BatchNorm2d, non...
    method forward (line 262) | def forward(self, x):
  class DownBlock2d (line 266) | class DownBlock2d(nn.Module):
    method __init__ (line 267) | def __init__(self, input_nc, output_nc, norm_layer=nn.BatchNorm2d, non...
    method forward (line 280) | def forward(self, x):
  class UpBlock2d (line 284) | class UpBlock2d(nn.Module):
    method __init__ (line 285) | def __init__(self, input_nc, output_nc, norm_layer=nn.BatchNorm2d, non...
    method forward (line 294) | def forward(self, x):
  class FineADAINResBlocks (line 298) | class FineADAINResBlocks(nn.Module):
    method __init__ (line 299) | def __init__(self, num_block, input_nc, feature_nc, norm_layer=nn.Batc...
    method forward (line 306) | def forward(self, x, z):
  class Jump (line 312) | class Jump(nn.Module):
    method __init__ (line 313) | def __init__(self, input_nc, norm_layer=nn.BatchNorm2d, nonlinearity=n...
    method forward (line 323) | def forward(self, x):
  class FineADAINResBlock2d (line 327) | class FineADAINResBlock2d(nn.Module):
    method __init__ (line 331) | def __init__(self, input_nc, feature_nc, norm_layer=nn.BatchNorm2d, no...
    method forward (line 344) | def forward(self, x, z):
  class FinalBlock2d (line 350) | class FinalBlock2d(nn.Module):
    method __init__ (line 354) | def __init__(self, input_nc, output_nc, use_spect=False, tanh_or_sigmo...
    method forward (line 366) | def forward(self, x):

FILE: generators/face_model.py
  class FaceGenerator (line 11) | class FaceGenerator(nn.Module):
    method __init__ (line 12) | def __init__(
    method forward (line 24) | def forward(
  class MappingNet (line 39) | class MappingNet(nn.Module):
    method __init__ (line 40) | def __init__(self, coeff_nc, descriptor_nc, layer):
    method forward (line 57) | def forward(self, input_3dmm):
  class WarpingNet (line 65) | class WarpingNet(nn.Module):
    method __init__ (line 66) | def __init__(
    method forward (line 92) | def forward(self, input_image, descriptor):
  class EditingNet (line 102) | class EditingNet(nn.Module):
    method __init__ (line 103) | def __init__(
    method forward (line 123) | def forward(self, input_image, warp_image, descriptor):

FILE: inference.py
  function parse_args (line 22) | def parse_args():
  function write2video (line 40) | def write2video(results_dir, *video_list):

FILE: intuitive_control.py
  function parse_args (line 20) | def parse_args():
  function get_control (line 37) | def get_control(input_name):

FILE: loss/perceptual.py
  function apply_imagenet_normalization (line 8) | def apply_imagenet_normalization(input):
  class PerceptualLoss (line 25) | class PerceptualLoss(nn.Module):
    method __init__ (line 41) | def __init__(self, network='vgg19', layers='relu_4_1', weights=None,
    method forward (line 91) | def forward(self, inp, target, mask=None):
    method compute_gram (line 164) | def compute_gram(self, x):
  class _PerceptualNetwork (line 171) | class _PerceptualNetwork(nn.Module):
    method __init__ (line 181) | def __init__(self, network, layer_name_mapping, layers):
    method forward (line 191) | def forward(self, x):
  function _vgg19 (line 203) | def _vgg19(layers):
  function _vgg16 (line 222) | def _vgg16(layers):
  function _alexnet (line 239) | def _alexnet(layers):
  function _inception_v3 (line 255) | def _inception_v3(layers):
  function _resnet50 (line 284) | def _resnet50(layers):
  function _robust_resnet50 (line 303) | def _robust_resnet50(layers):
  function _vgg_face_dag (line 329) | def _vgg_face_dag(layers):

FILE: scripts/coeff_detector.py
  class CoeffDetector (line 18) | class CoeffDetector(nn.Module):
    method __init__ (line 19) | def __init__(self, opt):
    method forward (line 30) | def forward(self, img, lm):
    method image_transform (line 53) | def image_transform(self, images, lm):
  function get_data_path (line 74) | def get_data_path(root, keypoint_root):

FILE: scripts/extract_kp_videos.py
  class KeypointExtractor (line 14) | class KeypointExtractor():
    method __init__ (line 15) | def __init__(self):
    method extract_keypoint (line 18) | def extract_keypoint(self, images, name=None):
  function read_video (line 52) | def read_video(filename):
  function run (line 66) | def run(data):

FILE: scripts/face_recon_images.py
  function get_data_path (line 17) | def get_data_path(root, keypoint_root):
  class ImagePathDataset (line 36) | class ImagePathDataset(torch.utils.data.Dataset):
    method __init__ (line 37) | def __init__(self, filenames, txt_filenames, bfm_folder):
    method __len__ (line 42) | def __len__(self):
    method __getitem__ (line 45) | def __getitem__(self, i):
    method image_transform (line 55) | def image_transform(self, images, lm):
    method read_data (line 72) | def read_data(self, filename, txt_filename):
  function main (line 80) | def main(opt, model):

FILE: scripts/face_recon_videos.py
  function get_data_path (line 18) | def get_data_path(root, keypoint_root):
  class VideoPathDataset (line 34) | class VideoPathDataset(torch.utils.data.Dataset):
    method __init__ (line 35) | def __init__(self, filenames, txt_filenames, bfm_folder):
    method __len__ (line 40) | def __len__(self):
    method __getitem__ (line 43) | def __getitem__(self, index):
    method read_video (line 61) | def read_video(self, filename):
    method image_transform (line 75) | def image_transform(self, images, lm):
  function main (line 92) | def main(opt, model):

FILE: scripts/inference_options.py
  class InferenceOptions (line 4) | class InferenceOptions(BaseOptions):
    method initialize (line 10) | def initialize(self, parser):

FILE: scripts/prepare_vox_lmdb.py
  function format_for_lmdb (line 15) | def format_for_lmdb(*args):
  class Resizer (line 23) | class Resizer:
    method __init__ (line 24) | def __init__(self, size, kp_root, coeff_3dmm_root, img_format):
    method get_resized_bytes (line 30) | def get_resized_bytes(self, img, img_format='jpeg'):
    method prepare (line 37) | def prepare(self, filename):
    method __call__ (line 57) | def __call__(self, index_filename):
  function get_others (line 62) | def get_others(root, video_name, data_type):
  function convert_kp (line 78) | def convert_kp(file_path):
  function convert_3dmm (line 83) | def convert_3dmm(file_path):
  function prepare_data (line 94) | def prepare_data(path, keypoint_path, coeff_3dmm_path, out, n_worker, si...

FILE: third_part/PerceptualSimilarity/models/base_model.py
  class BaseModel (line 7) | class BaseModel():
    method __init__ (line 8) | def __init__(self):
    method name (line 11) | def name(self):
    method initialize (line 14) | def initialize(self, use_gpu=True):
    method forward (line 19) | def forward(self):
    method get_image_paths (line 22) | def get_image_paths(self):
    method optimize_parameters (line 25) | def optimize_parameters(self):
    method get_current_visuals (line 28) | def get_current_visuals(self):
    method get_current_errors (line 31) | def get_current_errors(self):
    method save (line 34) | def save(self, label):
    method save_network (line 38) | def save_network(self, network, path, network_label, epoch_label):
    method load_network (line 44) | def load_network(self, network, network_label, epoch_label):
    method update_learning_rate (line 51) | def update_learning_rate():
    method get_image_paths (line 54) | def get_image_paths(self):
    method save_done (line 57) | def save_done(self, flag=False):

FILE: third_part/PerceptualSimilarity/models/dist_model.py
  class DistModel (line 25) | class DistModel(BaseModel):
    method name (line 26) | def name(self):
    method initialize (line 29) | def initialize(self, model='net-lin', net='alex', pnet_rand=False, pne...
    method forward_pair (line 106) | def forward_pair(self,in1,in2,retPerLayer=False):
    method forward (line 112) | def forward(self, in0, in1, retNumpy=True):
    method optimize_parameters (line 163) | def optimize_parameters(self):
    method clamp_weights (line 170) | def clamp_weights(self):
    method set_input (line 175) | def set_input(self, data):
    method forward_train (line 191) | def forward_train(self): # run forward pass
    method backward_train (line 202) | def backward_train(self):
    method compute_accuracy (line 205) | def compute_accuracy(self,d0,d1,judge):
    method get_current_errors (line 211) | def get_current_errors(self):
    method get_current_visuals (line 220) | def get_current_visuals(self):
    method save (line 235) | def save(self, path, label):
    method update_learning_rate (line 239) | def update_learning_rate(self,nepoch_decay):
  function score_2afc_dataset (line 251) | def score_2afc_dataset(data_loader,func):
  function score_jnd_dataset (line 288) | def score_jnd_dataset(data_loader,func):

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

FILE: third_part/PerceptualSimilarity/models/networks_basic.py
  class PNet (line 21) | class PNet(nn.Module):
    method __init__ (line 23) | def __init__(self, pnet_type='vgg', pnet_rand=False, use_gpu=True):
    method forward (line 50) | def forward(self, in0, in1, retPerLayer=False):
  class PNetLin (line 75) | class PNetLin(nn.Module):
    method __init__ (line 76) | def __init__(self, pnet_type='vgg', pnet_rand=False, pnet_tune=False, ...
    method forward (line 131) | def forward(self, in0, in1):
  class Dist2LogitLayer (line 180) | class Dist2LogitLayer(nn.Module):
    method __init__ (line 182) | def __init__(self, chn_mid=32,use_sigmoid=True):
    method forward (line 193) | def forward(self,d0,d1,eps=0.1):
  class BCERankingLoss (line 196) | class BCERankingLoss(nn.Module):
    method __init__ (line 197) | def __init__(self, use_gpu=True, chn_mid=32):
    method forward (line 208) | def forward(self, d0, d1, judge):
  class NetLinLayer (line 215) | class NetLinLayer(nn.Module):
    method __init__ (line 217) | def __init__(self, chn_in, chn_out=1, use_dropout=False):
  class FakeNet (line 226) | class FakeNet(nn.Module):
    method __init__ (line 227) | def __init__(self, use_gpu=True, colorspace='Lab'):
  class L2 (line 232) | class L2(FakeNet):
    method forward (line 234) | def forward(self, in0, in1):
  class DSSIM (line 249) | class DSSIM(FakeNet):
    method forward (line 251) | def forward(self, in0, in1):
  function print_network (line 264) | def print_network(net):

FILE: third_part/PerceptualSimilarity/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: third_part/PerceptualSimilarity/util/html.py
  class HTML (line 6) | class HTML:
    method __init__ (line 7) | def __init__(self, web_dir, title, image_subdir='', reflesh=0):
    method get_image_dir (line 24) | def get_image_dir(self):
    method add_header (line 27) | def add_header(self, str):
    method add_table (line 31) | def add_table(self, border=1):
    method add_images (line 35) | def add_images(self, ims, txts, links, width=400):
    method save (line 47) | def save(self,file='index'):

FILE: third_part/PerceptualSimilarity/util/util.py
  function datetime_str (line 18) | def datetime_str():
  function read_text_file (line 22) | def read_text_file(in_path):
  function bootstrap (line 34) | def bootstrap(in_vec,num_samples=100,bootfunc=np.mean):
  function rand_flip (line 38) | def rand_flip(input1,input2):
  function l2 (line 44) | def l2(p0, p1, range=255.):
  function psnr (line 47) | def psnr(p0, p1, peak=255.):
  function dssim (line 50) | def dssim(p0, p1, range=255.):
  function rgb2lab (line 54) | def rgb2lab(in_img,mean_cent=False):
  function normalize_blob (line 61) | def normalize_blob(in_feat,eps=1e-10):
  function cos_sim_blob (line 65) | def cos_sim_blob(in0,in1):
  function normalize_tensor (line 72) | def normalize_tensor(in_feat,eps=1e-10):
  function cos_sim (line 77) | def cos_sim(in0,in1):
  function tensor2np (line 89) | def tensor2np(tensor_obj):
  function np2tensor (line 93) | def np2tensor(np_obj):
  function tensor2tensorlab (line 97) | def tensor2tensorlab(image_tensor,to_norm=True,mc_only=False):
  function tensorlab2tensor (line 113) | def tensorlab2tensor(lab_tensor,return_inbnd=False):
  function tensor2im (line 136) | def tensor2im(image_tensor, imtype=np.uint8, cent=1., factor=255./2.):
  function im2tensor (line 142) | def im2tensor(image, imtype=np.uint8, cent=1., factor=255./2.):
  function tensor2vec (line 147) | def tensor2vec(vector_tensor):
  function diagnose_network (line 150) | def diagnose_network(net, name='network'):
  function grab_patch (line 162) | def grab_patch(img_in, P, yy, xx):
  function load_image (line 165) | def load_image(path):
  function resize_image (line 180) | def resize_image(img, max_size=256):
  function resize_image_zoom (line 190) | def resize_image_zoom(img, zoom_factor=1., order=3):
  function save_image (line 196) | def save_image(image_numpy, image_path, ):
  function prep_display_image (line 201) | def prep_display_image(img, dtype='uint8'):
  function info (line 208) | def info(object, spacing=10, collapse=1):
  function varname (line 224) | def varname(p):
  function print_numpy (line 231) | def print_numpy(x, val=True, shp=False):
  function mkdirs (line 242) | def mkdirs(paths):
  function mkdir (line 250) | def mkdir(path):
  function rgb2lab (line 255) | def rgb2lab(input):
  function montage (line 260) | def montage(
  class zeroClipper (line 369) | class zeroClipper(object):
    method __init__ (line 370) | def __init__(self, frequency=1):
    method __call__ (line 373) | def __call__(self, module):
  function flatten_nested_list (line 379) | def flatten_nested_list(nested_list):
  function read_file (line 387) | def read_file(in_path,list_lines=False):
  function read_csv_file_as_text (line 405) | def read_csv_file_as_text(in_path):
  function random_swap (line 415) | def random_swap(obj0,obj1):
  function voc_ap (line 421) | def voc_ap(rec, prec, use_07_metric=False):

FILE: third_part/PerceptualSimilarity/util/visualizer.py
  function zoom_to_res (line 11) | def zoom_to_res(img,res=256,order=0,axis=0):
  class Visualizer (line 20) | class Visualizer():
    method __init__ (line 21) | def __init__(self, opt):
    method display_current_results (line 43) | def display_current_results(self, visuals, epoch, nrows=None, res=256):
    method plot_current_errors_save (line 94) | def plot_current_errors_save(self, epoch, counter_ratio, opt, errors,k...
    method plot_current_errors (line 126) | def plot_current_errors(self, epoch, counter_ratio, opt, errors):
    method print_current_errors (line 142) | def print_current_errors(self, epoch, i, errors, t, t2=-1, t2o=-1, fid...
    method save_images_simple (line 152) | def save_images_simple(self, webpage, images, names, in_txts, prefix='...
    method save_images (line 174) | def save_images(self, webpage, images, names, image_path, title=''):

FILE: train.py
  function parse_args (line 11) | def parse_args():

FILE: trainers/base.py
  class BaseTrainer (line 18) | class BaseTrainer(object):
    method __init__ (line 33) | def __init__(self,
    method _init_tensorboard (line 94) | def _init_tensorboard(self):
    method _init_hparams (line 113) | def _init_hparams(self):
    method _write_tensorboard (line 119) | def _write_tensorboard(self):
    method _write_loss_meters (line 137) | def _write_loss_meters(self):
    method test_everything (line 146) | def test_everything(self, train_dataset, val_dataset, current_epoch, c...
    method _set_custom_debug_parameter (line 168) | def _set_custom_debug_parameter(self):
    method _write_custom_meters (line 175) | def _write_custom_meters(self):
    method _write_to_meters (line 182) | def _write_to_meters(data, meters):
    method _flush_meters (line 187) | def _flush_meters(self, meters):
    method _pre_save_checkpoint (line 192) | def _pre_save_checkpoint(self):
    method save_checkpoint (line 199) | def save_checkpoint(self, current_epoch, current_iteration):
    method load_checkpoint (line 209) | def load_checkpoint(self, opt, which_iter=None):
    method _load_checkpoint (line 237) | def _load_checkpoint(self, checkpoint_path, resume=True):
    method start_of_epoch (line 260) | def start_of_epoch(self, current_epoch):
    method start_of_iteration (line 270) | def start_of_iteration(self, data, current_iteration):
    method end_of_iteration (line 285) | def end_of_iteration(self, data, current_epoch, current_iteration):
    method _print_current_errors (line 348) | def _print_current_errors(self):
    method end_of_epoch (line 360) | def end_of_epoch(self, data, val_dataset, current_epoch, current_itera...
    method write_data_tensorboard (line 403) | def write_data_tensorboard(self, data, epoch, iteration):
    method save_image (line 422) | def save_image(self, path, data):
    method write_metrics (line 442) | def write_metrics(self, data):
    method _get_save_path (line 458) | def _get_save_path(self, subdir, ext):
    method _compute_metrics (line 476) | def _compute_metrics(self, data, current_iteration):
    method _start_of_epoch (line 482) | def _start_of_epoch(self, current_epoch):
    method _start_of_iteration (line 490) | def _start_of_iteration(self, data, current_iteration):
    method _end_of_iteration (line 502) | def _end_of_iteration(self, data, current_epoch, current_iteration):
    method _end_of_epoch (line 513) | def _end_of_epoch(self, data, current_epoch, current_iteration):
    method _get_visualizations (line 523) | def _get_visualizations(self, data):
    method _init_loss (line 531) | def _init_loss(self, opt):
    method gen_forward (line 535) | def gen_forward(self, data):
    method test (line 540) | def test(self, data_loader, output_dir, current_iteration):
  function _save_checkpoint (line 643) | def _save_checkpoint(opt,

FILE: trainers/face_trainer.py
  class FaceTrainer (line 9) | class FaceTrainer(BaseTrainer):
    method __init__ (line 21) | def __init__(self, opt, net_G, opt_G, sch_G,
    method _init_loss (line 27) | def _init_loss(self, opt):
    method _assign_criteria (line 50) | def _assign_criteria(self, name, criterion, weight):
    method optimize_parameters (line 54) | def optimize_parameters(self, data):
    method _start_of_iteration (line 87) | def _start_of_iteration(self, data, current_iteration):
    method reset_trainer (line 93) | def reset_trainer(self):
    method _get_visualizations (line 96) | def _get_visualizations(self, data):
    method test (line 119) | def test(self, data_loader, output_dir, current_iteration=-1):
    method _compute_metrics (line 122) | def _compute_metrics(self, data, current_iteration):

FILE: util/cudnn.py
  function init_cudnn (line 6) | def init_cudnn(deterministic, benchmark):

FILE: util/distributed.py
  function init_dist (line 6) | def init_dist(local_rank, backend='nccl', **kwargs):
  function get_rank (line 15) | def get_rank():
  function get_world_size (line 24) | def get_world_size():
  function master_only (line 33) | def master_only(func):
  function is_master (line 45) | def is_master():
  function master_only_print (line 51) | def master_only_print(*args):
  function dist_reduce_tensor (line 56) | def dist_reduce_tensor(tensor):
  function dist_all_reduce_tensor (line 68) | def dist_all_reduce_tensor(tensor):
  function dist_all_gather_tensor (line 79) | def dist_all_gather_tensor(tensor):

FILE: util/flow_util.py
  function convert_flow_to_deformation (line 3) | def convert_flow_to_deformation(flow):
  function make_coordinate_grid (line 17) | def make_coordinate_grid(flow):
  function warp_image (line 41) | def warp_image(source_image, deformation):

FILE: util/init_weight.py
  function weights_init (line 4) | def weights_init(init_type='normal', gain=0.02, bias=None):

FILE: util/io.py
  function save_pilimage_in_jpeg (line 10) | def save_pilimage_in_jpeg(fullname, output_img):
  function save_intermediate_training_results (line 22) | def save_intermediate_training_results(
  function download_file_from_google_drive (line 44) | def download_file_from_google_drive(file_id, destination):
  function get_confirm_token (line 64) | def get_confirm_token(response):
  function save_response_content (line 79) | def save_response_content(response, destination):
  function get_checkpoint (line 96) | def get_checkpoint(checkpoint_path, url=''):

FILE: util/logging.py
  function get_date_uid (line 8) | def get_date_uid():
  function init_logging (line 16) | def init_logging(opt):
  function make_logging_dir (line 26) | def make_logging_dir(logdir, date_uid):

FILE: util/lpips.py
  function get_image_list (line 10) | def get_image_list(flist):
  function preprocess_path_for_deform_task (line 29) | def preprocess_path_for_deform_task(gt_path, distorted_path):
  class LPIPS (line 45) | class LPIPS():
    method __init__ (line 46) | def __init__(self, use_gpu=True):
    method __call__ (line 51) | def __call__(self, image_1, image_2):
    method calculate_from_disk (line 59) | def calculate_from_disk(self, gt_path, distorted_path, batch_size=64, ...

FILE: util/meters.py
  function sn_reshape_weight_to_matrix (line 16) | def sn_reshape_weight_to_matrix(weight):
  function get_weight_stats (line 28) | def get_weight_stats(mod, cfg, loss_id):
  function set_summary_writer (line 51) | def set_summary_writer(log_dir):
  function write_summary (line 63) | def write_summary(name, summary, step, hist=False):
  function add_hparams (line 77) | def add_hparams(hparam_dict=None, metric_dict=None):
  class Meter (line 103) | class Meter(object):
    method __init__ (line 114) | def __init__(self, name):
    method reset (line 119) | def reset(self):
    method write (line 124) | def write(self, value):
    method flush (line 129) | def flush(self, step):
    method write_image (line 144) | def write_image(self, img_grid, step):

FILE: util/misc.py
  function split_labels (line 11) | def split_labels(labels, label_lengths):
  function requires_grad (line 36) | def requires_grad(model, require=True):
  function to_device (line 50) | def to_device(data, device):
  function to_cuda (line 70) | def to_cuda(data):
  function to_cpu (line 79) | def to_cpu(data):
  function to_half (line 88) | def to_half(data):
  function to_float (line 106) | def to_float(data):
  function get_and_setattr (line 124) | def get_and_setattr(cfg, name, default):
  function get_nested_attr (line 141) | def get_nested_attr(cfg, attr_name, default):
  function gradient_norm (line 162) | def gradient_norm(model):
  function random_shift (line 177) | def random_shift(x, offset=0.05, mode='bilinear', padding_mode='reflecti...
  function truncated_gaussian (line 200) | def truncated_gaussian(threshold, size, seed=None, device=None):
  function apply_imagenet_normalization (line 215) | def apply_imagenet_normalization(input):

FILE: util/trainer.py
  function accumulate (line 12) | def accumulate(model1, model2, decay=0.999):
  function set_random_seed (line 19) | def set_random_seed(seed):
  function get_trainer (line 34) | def get_trainer(opt, net_G, net_G_ema, opt_G, sch_G, train_dataset):
  function get_model_optimizer_and_scheduler (line 42) | def get_model_optimizer_and_scheduler(opt):
  function _calculate_model_size (line 77) | def _calculate_model_size(model):
  function get_scheduler (line 89) | def get_scheduler(opt_opt, opt):
  function get_optimizer (line 112) | def get_optimizer(opt_opt, net):
  function get_optimizer_for_params (line 116) | def get_optimizer_for_params(opt_opt, params):