SYMBOL INDEX (1926 symbols across 189 files)

FILE: codes/config/BSRGAN/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/BSRGAN/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/BSRGAN/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/BSRGAN/archs/loss.py
  class GaussGuided (line 12) | class GaussGuided(nn.Module):
    method __init__ (line 13) | def __init__(self, ksize, sigma):
    method forward (line 24) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 29) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 30) | def __init__(self, net="alex", normalize=True):
    method forward (line 38) | def forward(self, res, ref):
  class MSELoss (line 43) | class MSELoss(nn.Module):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method forward (line 47) | def forward(self, res, ref):
  class L1Loss (line 52) | class L1Loss(nn.Module):
    method __init__ (line 53) | def __init__(self, *args, **kwargs):
    method forward (line 56) | def forward(self, res, ref):
  class GANLoss (line 61) | class GANLoss(nn.Module):
    method __init__ (line 69) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 88) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 98) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 112) | def get_target_label(self, input, target_is_real):
    method forward (line 127) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 152) | class PerceptualLoss(nn.Module):
    method __init__ (line 174) | def __init__(
    method forward (line 205) | def forward(self, x, gt):
    method _gram_mat (line 262) | def _gram_mat(self, x):
  class CharbonnierLoss (line 277) | class CharbonnierLoss(nn.Module):
    method __init__ (line 280) | def __init__(self, eps=1e-6):
    method forward (line 284) | def forward(self, x, y):
  class GradientPenaltyLoss (line 290) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 291) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 296) | def get_grad_outputs(self, input):
    method forward (line 301) | def forward(self, interp, interp_crit):

FILE: codes/config/BSRGAN/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/BSRGAN/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/BSRGAN/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/BSRGAN/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/BSRGAN/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/BSRGAN/archs/translator.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class BasicBlock (line 17) | class BasicBlock(nn.Sequential):
    method __init__ (line 18) | def __init__(
  class ResBlock (line 46) | class ResBlock(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 70) | def forward(self, x):
  class Upsampler (line 77) | class Upsampler(nn.Sequential):
    method __init__ (line 78) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  class Translator (line 105) | class Translator(nn.Module):
    method __init__ (line 106) | def __init__(self, in_nc, out_nc, nf, nb, scale=4, conv=default_conv):
    method forward (line 134) | def forward(self, x):

FILE: codes/config/BSRGAN/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/BSRGAN/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/BSRGAN/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/BSRGAN/models/sr_model.py
  class SRModel (line 15) | class SRModel(BaseModel):
    method __init__ (line 16) | def __init__(self, opt):
    method feed_data (line 42) | def feed_data(self, data):
    method forward (line 47) | def forward(self):
    method optimize_parameters (line 51) | def optimize_parameters(self, step):
    method calculate_rgan_loss_D (line 96) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 111) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 122) | def test(self, data, crop_size=None):
    method crop_test (line 132) | def crop_test(self, lr, crop_size):
    method get_current_visuals (line 180) | def get_current_visuals(self, need_GT=True):

FILE: codes/config/BSRGAN/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/BSRGAN/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/Bicubic/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/Bicubic/archs/bicubic.py
  class BicuBic (line 13) | class BicuBic(nn.Module):
    method __init__ (line 14) | def __init__(self, upscale=4):
    method forward (line 20) | def forward(self, x):

FILE: codes/config/Bicubic/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/Bicubic/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/Bicubic/archs/loss.py
  class GaussGuided (line 12) | class GaussGuided(nn.Module):
    method __init__ (line 13) | def __init__(self, ksize, sigma):
    method forward (line 24) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 29) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 30) | def __init__(self, net="alex", normalize=True):
    method forward (line 38) | def forward(self, res, ref):
  class MSELoss (line 43) | class MSELoss(nn.Module):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method forward (line 47) | def forward(self, res, ref):
  class L1Loss (line 52) | class L1Loss(nn.Module):
    method __init__ (line 53) | def __init__(self, *args, **kwargs):
    method forward (line 56) | def forward(self, res, ref):
  class GANLoss (line 61) | class GANLoss(nn.Module):
    method __init__ (line 69) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 88) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 98) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 112) | def get_target_label(self, input, target_is_real):
    method forward (line 127) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 152) | class PerceptualLoss(nn.Module):
    method __init__ (line 174) | def __init__(
    method forward (line 205) | def forward(self, x, gt):
    method _gram_mat (line 262) | def _gram_mat(self, x):
  class CharbonnierLoss (line 277) | class CharbonnierLoss(nn.Module):
    method __init__ (line 280) | def __init__(self, eps=1e-6):
    method forward (line 284) | def forward(self, x, y):
  class GradientPenaltyLoss (line 290) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 291) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 296) | def get_grad_outputs(self, input):
    method forward (line 301) | def forward(self, interp, interp_crit):

FILE: codes/config/Bicubic/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/Bicubic/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/Bicubic/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/Bicubic/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/Bicubic/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/Bicubic/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/Bicubic/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/Bicubic/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/Bicubic/models/sr_model.py
  class SRModel (line 15) | class SRModel(BaseModel):
    method __init__ (line 16) | def __init__(self, opt):
    method feed_data (line 42) | def feed_data(self, data):
    method forward (line 47) | def forward(self):
    method optimize_parameters (line 51) | def optimize_parameters(self, step):
    method calculate_rgan_loss_D (line 96) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 111) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 122) | def test(self, data, crop_size=None):
    method crop_test (line 132) | def crop_test(self, lr, crop_size):
    method get_current_visuals (line 180) | def get_current_visuals(self, need_GT=True):

FILE: codes/config/Bicubic/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/Bicubic/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/Bulat/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/Bulat/archs/deg_arch.py
  class DegModel (line 13) | class DegModel(nn.Module):
    method __init__ (line 14) | def __init__(self, nb, nf, scale=4, zero_tail=False, conv=default_conv):
    method forward (line 44) | def forward(self, x):

FILE: codes/config/Bulat/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=2, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/Bulat/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/Bulat/archs/loss.py
  class ColorLoss (line 11) | class ColorLoss(nn.Module):
    method __init__ (line 12) | def __init__(self, gauss_opt=None, pool_opt=None, stride=1, recursion=...
    method forward (line 38) | def forward(self, src, tgt):
  class GaussGuided (line 51) | class GaussGuided(nn.Module):
    method __init__ (line 52) | def __init__(self, ksize, sigma):
    method forward (line 63) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 68) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 69) | def __init__(self, net="alex", normalize=True):
    method forward (line 77) | def forward(self, res, ref):
  class MSELoss (line 82) | class MSELoss(nn.Module):
    method __init__ (line 83) | def __init__(self, *args, **kwargs):
    method forward (line 86) | def forward(self, res, ref):
  class L1Loss (line 91) | class L1Loss(nn.Module):
    method __init__ (line 92) | def __init__(self, *args, **kwargs):
    method forward (line 95) | def forward(self, res, ref):
  class GANLoss (line 100) | class GANLoss(nn.Module):
    method __init__ (line 108) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 127) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 137) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 151) | def get_target_label(self, input, target_is_real):
    method forward (line 166) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 191) | class PerceptualLoss(nn.Module):
    method __init__ (line 213) | def __init__(
    method forward (line 244) | def forward(self, x, gt):
    method _gram_mat (line 301) | def _gram_mat(self, x):
  class CharbonnierLoss (line 316) | class CharbonnierLoss(nn.Module):
    method __init__ (line 319) | def __init__(self, eps=1e-6):
    method forward (line 323) | def forward(self, x, y):
  class GradientPenaltyLoss (line 329) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 330) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 335) | def get_grad_outputs(self, input):
    method forward (line 340) | def forward(self, interp, interp_crit):

FILE: codes/config/Bulat/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/Bulat/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/Bulat/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/Bulat/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/Bulat/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/Bulat/archs/translator.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class BasicBlock (line 17) | class BasicBlock(nn.Sequential):
    method __init__ (line 18) | def __init__(
  class ResBlock (line 46) | class ResBlock(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 70) | def forward(self, x):
  class Upsampler (line 77) | class Upsampler(nn.Sequential):
    method __init__ (line 78) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  class Translator (line 105) | class Translator(nn.Module):
    method __init__ (line 106) | def __init__(self, nb, nf, scale=4, zero_tail=False, conv=default_conv):
    method forward (line 138) | def forward(self, x):

FILE: codes/config/Bulat/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/Bulat/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/Bulat/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/Bulat/models/deg_sr_model.py
  class DegSRModel (line 16) | class DegSRModel(BaseModel):
    method __init__ (line 17) | def __init__(self, opt):
    method feed_data (line 64) | def feed_data(self, data):
    method forward (line 69) | def forward(self):
    method optimize_parameters (line 75) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 169) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 179) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method test (line 186) | def test(self, data):
    method get_current_visuals (line 193) | def get_current_visuals(self, need_GT=True):
  class ShuffleBuffer (line 200) | class ShuffleBuffer():
    method __init__ (line 206) | def __init__(self, buffer_size):
    method choose (line 215) | def choose(self, images, prob=0.5):

FILE: codes/config/Bulat/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/Bulat/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/CinGAN/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/CinGAN/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/CinGAN/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/CinGAN/archs/loss.py
  class TVLoss (line 11) | class TVLoss(nn.Module):
    method __init__ (line 12) | def __init__(self, penealty="L1Loss"):
    method forward (line 16) | def forward(self, pred):
  class MSELoss (line 26) | class MSELoss(nn.Module):
    method __init__ (line 27) | def __init__(self, *args, **kwargs):
    method forward (line 30) | def forward(self, res, ref):
  class L1Loss (line 35) | class L1Loss(nn.Module):
    method __init__ (line 36) | def __init__(self, *args, **kwargs):
    method forward (line 39) | def forward(self, res, ref):
  class GANLoss (line 44) | class GANLoss(nn.Module):
    method __init__ (line 52) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 71) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 81) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 95) | def get_target_label(self, input, target_is_real):
    method forward (line 110) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 135) | class PerceptualLoss(nn.Module):
    method __init__ (line 157) | def __init__(
    method forward (line 188) | def forward(self, x, gt):
    method _gram_mat (line 245) | def _gram_mat(self, x):
  class CharbonnierLoss (line 260) | class CharbonnierLoss(nn.Module):
    method __init__ (line 263) | def __init__(self, eps=1e-6):
    method forward (line 267) | def forward(self, x, y):
  class GradientPenaltyLoss (line 273) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 274) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 279) | def get_grad_outputs(self, input):
    method forward (line 284) | def forward(self, interp, interp_crit):

FILE: codes/config/CinGAN/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/CinGAN/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/CinGAN/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/CinGAN/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/CinGAN/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/CinGAN/archs/translator.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class BasicBlock (line 17) | class BasicBlock(nn.Sequential):
    method __init__ (line 18) | def __init__(
  class ResBlock (line 46) | class ResBlock(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 70) | def forward(self, x):
  class Upsampler (line 77) | class Upsampler(nn.Sequential):
    method __init__ (line 78) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  class Translator (line 105) | class Translator(nn.Module):
    method __init__ (line 106) | def __init__(self, nb, nf, scale=4, zero_tail=False, conv=default_conv):
    method forward (line 137) | def forward(self, x):

FILE: codes/config/CinGAN/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/CinGAN/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/CinGAN/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/CinGAN/models/cingan_model.py
  class CinGANModel (line 16) | class CinGANModel(BaseModel):
    method __init__ (line 17) | def __init__(self, opt):
    method feed_data (line 60) | def feed_data(self, data):
    method foward_trans (line 66) | def foward_trans(self):
    method forward_sr (line 70) | def forward_sr(self):
    method optimize_parameters (line 76) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 164) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 174) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method calculate_rgan_loss_D (line 181) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 196) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 207) | def test(self, data):
    method get_current_visuals (line 215) | def get_current_visuals(self, need_GT=True):

FILE: codes/config/CinGAN/models/trans_model.py
  class TransModel (line 16) | class TransModel(BaseModel):
    method __init__ (line 17) | def __init__(self, opt):
    method feed_data (line 57) | def feed_data(self, data):
    method forward (line 62) | def forward(self):
    method optimize_parameters (line 67) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 120) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 130) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method calculate_rgan_loss_D (line 137) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 152) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 163) | def test(self, data):
    method get_current_visuals (line 170) | def get_current_visuals(self, need_GT=True):
  class ShuffleBuffer (line 176) | class ShuffleBuffer():
    method __init__ (line 182) | def __init__(self, buffer_size):
    method choose (line 191) | def choose(self, images, prob=0.5):

FILE: codes/config/CinGAN/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/CinGAN/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/CycleSR/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/CycleSR/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/CycleSR/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/CycleSR/archs/loss.py
  class GaussGuided (line 12) | class GaussGuided(nn.Module):
    method __init__ (line 13) | def __init__(self, ksize, sigma):
    method forward (line 24) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 29) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 30) | def __init__(self, net="alex", normalize=True):
    method forward (line 38) | def forward(self, res, ref):
  class MSELoss (line 43) | class MSELoss(nn.Module):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method forward (line 47) | def forward(self, res, ref):
  class L1Loss (line 52) | class L1Loss(nn.Module):
    method __init__ (line 53) | def __init__(self, *args, **kwargs):
    method forward (line 56) | def forward(self, res, ref):
  class GANLoss (line 61) | class GANLoss(nn.Module):
    method __init__ (line 69) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 88) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 98) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 112) | def get_target_label(self, input, target_is_real):
    method forward (line 127) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 152) | class PerceptualLoss(nn.Module):
    method __init__ (line 174) | def __init__(
    method forward (line 205) | def forward(self, x, gt):
    method _gram_mat (line 262) | def _gram_mat(self, x):
  class CharbonnierLoss (line 277) | class CharbonnierLoss(nn.Module):
    method __init__ (line 280) | def __init__(self, eps=1e-6):
    method forward (line 284) | def forward(self, x, y):
  class GradientPenaltyLoss (line 290) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 291) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 296) | def get_grad_outputs(self, input):
    method forward (line 301) | def forward(self, interp, interp_crit):

FILE: codes/config/CycleSR/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/CycleSR/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/CycleSR/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/CycleSR/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/CycleSR/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/CycleSR/archs/translator.py
  class Translator (line 13) | class Translator(nn.Module):
    method __init__ (line 14) | def __init__(self, nb, nf, scale=4, zero_tail=False, conv=default_conv):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/CycleSR/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/CycleSR/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/CycleSR/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/CycleSR/models/cyclegan_model.py
  class CycleGANModel (line 16) | class CycleGANModel(BaseModel):
    method __init__ (line 17) | def __init__(self, opt):
    method feed_data (line 61) | def feed_data(self, data):
    method forward (line 66) | def forward(self):
    method optimize_parameters (line 73) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 144) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 154) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method test (line 161) | def test(self, data):
    method get_current_visuals (line 168) | def get_current_visuals(self, need_GT=True):
  class ShuffleBuffer (line 174) | class ShuffleBuffer():
    method __init__ (line 180) | def __init__(self, buffer_size):
    method choose (line 189) | def choose(self, images, prob=0.5):

FILE: codes/config/CycleSR/models/cyclesr_model.py
  class CycleSRModel (line 16) | class CycleSRModel(BaseModel):
    method __init__ (line 17) | def __init__(self, opt):
    method feed_data (line 64) | def feed_data(self, data):
    method forward_trans (line 70) | def forward_trans(self):
    method forward_sr (line 79) | def forward_sr(self):
    method optimize_trans_models (line 84) | def optimize_trans_models(self, step, loss_dict):
    method optimize_sr_models (line 155) | def optimize_sr_models(self, step, loss_dict):
    method optimize_parameters (line 204) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 213) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 223) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method test (line 230) | def test(self, data):
    method get_current_visuals (line 237) | def get_current_visuals(self, need_GT=True):

FILE: codes/config/CycleSR/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/CycleSR/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/DSGANSR/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/DSGANSR/archs/deg_arch.py
  class ResBlock (line 9) | class ResBlock(nn.Module):
    method __init__ (line 10) | def __init__(self, nf, ksize, norm=nn.BatchNorm2d, act=nn.ReLU):
    method forward (line 20) | def forward(self, x):
  class DegModel (line 25) | class DegModel(nn.Module):
    method __init__ (line 26) | def __init__(
    method forward (line 93) | def forward(self, inp):

FILE: codes/config/DSGANSR/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/DSGANSR/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/DSGANSR/archs/loss.py
  class ColorLoss (line 11) | class ColorLoss(nn.Module):
    method __init__ (line 12) | def __init__(self, ksize=5, sigma=None, stride=1, recursion=1, loss_ty...
    method forward (line 31) | def forward(self, src, tgt):
  class GaussGuided (line 41) | class GaussGuided(nn.Module):
    method __init__ (line 42) | def __init__(self, ksize, sigma):
    method forward (line 53) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 58) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 59) | def __init__(self, net="alex", normalize=True):
    method forward (line 67) | def forward(self, res, ref):
  class MSELoss (line 72) | class MSELoss(nn.Module):
    method __init__ (line 73) | def __init__(self, *args, **kwargs):
    method forward (line 76) | def forward(self, res, ref):
  class L1Loss (line 81) | class L1Loss(nn.Module):
    method __init__ (line 82) | def __init__(self, *args, **kwargs):
    method forward (line 85) | def forward(self, res, ref):
  class GANLoss (line 90) | class GANLoss(nn.Module):
    method __init__ (line 98) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 117) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 127) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 141) | def get_target_label(self, input, target_is_real):
    method forward (line 156) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 181) | class PerceptualLoss(nn.Module):
    method __init__ (line 203) | def __init__(
    method forward (line 234) | def forward(self, x, gt):
    method _gram_mat (line 291) | def _gram_mat(self, x):
  class CharbonnierLoss (line 306) | class CharbonnierLoss(nn.Module):
    method __init__ (line 309) | def __init__(self, eps=1e-6):
    method forward (line 313) | def forward(self, x, y):
  class GradientPenaltyLoss (line 319) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 320) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 325) | def get_grad_outputs(self, input):
    method forward (line 330) | def forward(self, interp, interp_crit):

FILE: codes/config/DSGANSR/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/DSGANSR/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/DSGANSR/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/DSGANSR/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/DSGANSR/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/DSGANSR/archs/translator.py
  class Translator (line 13) | class Translator(nn.Module):
    method __init__ (line 14) | def __init__(self, nb, nf, scale=4, zero_tail=False, conv=default_conv):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/DSGANSR/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/DSGANSR/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/DSGANSR/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/DSGANSR/models/deg_sr_model.py
  class Quant (line 14) | class Quant(torch.autograd.Function):
    method forward (line 17) | def forward(ctx, input):
    method backward (line 23) | def backward(ctx, grad_output):
  class Quantization (line 26) | class Quantization(nn.Module):
    method __init__ (line 27) | def __init__(self):
    method forward (line 30) | def forward(self, input):
  class DegSRModel (line 35) | class DegSRModel(BaseModel):
    method __init__ (line 36) | def __init__(self, opt):
    method feed_data (line 86) | def feed_data(self, data):
    method encoder_forward (line 91) | def encoder_forward(self):
    method decoder_forward (line 94) | def decoder_forward(self):
    method optimize_trans_models (line 100) | def optimize_trans_models(self, loss_dict, step):
    method optimize_sr_models (line 158) | def optimize_sr_models(self, loss_dict, step):
    method optimize_parameters (line 214) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 227) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 237) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method test (line 244) | def test(self, test_data):
    method get_current_visuals (line 258) | def get_current_visuals(self, need_GT=True):
  class ShuffleBuffer (line 267) | class ShuffleBuffer():
    method __init__ (line 273) | def __init__(self, buffer_size):
    method choose (line 282) | def choose(self, images, prob=0.5):

FILE: codes/config/DSGANSR/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/DSGANSR/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/EDSR/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/EDSR/archs/bicubic.py
  class BicuBic (line 13) | class BicuBic(nn.Module):
    method __init__ (line 14) | def __init__(self, upscale=4):
    method forward (line 20) | def forward(self, x):

FILE: codes/config/EDSR/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/EDSR/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/EDSR/archs/loss.py
  class GaussGuided (line 12) | class GaussGuided(nn.Module):
    method __init__ (line 13) | def __init__(self, ksize, sigma):
    method forward (line 24) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 29) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 30) | def __init__(self, net="alex", normalize=True):
    method forward (line 38) | def forward(self, res, ref):
  class MSELoss (line 43) | class MSELoss(nn.Module):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method forward (line 47) | def forward(self, res, ref):
  class L1Loss (line 52) | class L1Loss(nn.Module):
    method __init__ (line 53) | def __init__(self, *args, **kwargs):
    method forward (line 56) | def forward(self, res, ref):
  class GANLoss (line 61) | class GANLoss(nn.Module):
    method __init__ (line 69) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 88) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 98) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 112) | def get_target_label(self, input, target_is_real):
    method forward (line 127) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 152) | class PerceptualLoss(nn.Module):
    method __init__ (line 174) | def __init__(
    method forward (line 205) | def forward(self, x, gt):
    method _gram_mat (line 262) | def _gram_mat(self, x):
  class CharbonnierLoss (line 277) | class CharbonnierLoss(nn.Module):
    method __init__ (line 280) | def __init__(self, eps=1e-6):
    method forward (line 284) | def forward(self, x, y):
  class GradientPenaltyLoss (line 290) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 291) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 296) | def get_grad_outputs(self, input):
    method forward (line 301) | def forward(self, interp, interp_crit):

FILE: codes/config/EDSR/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/EDSR/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/EDSR/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/EDSR/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/EDSR/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/EDSR/archs/translator.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class BasicBlock (line 17) | class BasicBlock(nn.Sequential):
    method __init__ (line 18) | def __init__(
  class ResBlock (line 46) | class ResBlock(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 70) | def forward(self, x):
  class Upsampler (line 77) | class Upsampler(nn.Sequential):
    method __init__ (line 78) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  class Translator (line 105) | class Translator(nn.Module):
    method __init__ (line 106) | def __init__(self, in_nc, out_nc, nf, nb, scale=4, conv=default_conv):
    method forward (line 134) | def forward(self, x):

FILE: codes/config/EDSR/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/EDSR/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/EDSR/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/EDSR/models/sr_model.py
  class SRModel (line 15) | class SRModel(BaseModel):
    method __init__ (line 16) | def __init__(self, opt):
    method feed_data (line 42) | def feed_data(self, data):
    method forward (line 47) | def forward(self):
    method optimize_parameters (line 51) | def optimize_parameters(self, step):
    method calculate_rgan_loss_D (line 96) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 111) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 122) | def test(self, data, crop_size=None):
    method crop_test (line 132) | def crop_test(self, lr, crop_size):
    method get_current_visuals (line 180) | def get_current_visuals(self, need_GT=True):

FILE: codes/config/EDSR/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/EDSR/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/Maeda/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/Maeda/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/Maeda/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/Maeda/archs/loss.py
  class TVLoss (line 11) | class TVLoss(nn.Module):
    method __init__ (line 12) | def __init__(self, penealty="L1Loss"):
    method forward (line 16) | def forward(self, pred):
  class MSELoss (line 26) | class MSELoss(nn.Module):
    method __init__ (line 27) | def __init__(self, *args, **kwargs):
    method forward (line 30) | def forward(self, res, ref):
  class L1Loss (line 35) | class L1Loss(nn.Module):
    method __init__ (line 36) | def __init__(self, *args, **kwargs):
    method forward (line 39) | def forward(self, res, ref):
  class GANLoss (line 44) | class GANLoss(nn.Module):
    method __init__ (line 52) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 71) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 81) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 95) | def get_target_label(self, input, target_is_real):
    method forward (line 110) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 135) | class PerceptualLoss(nn.Module):
    method __init__ (line 157) | def __init__(
    method forward (line 188) | def forward(self, x, gt):
    method _gram_mat (line 245) | def _gram_mat(self, x):
  class CharbonnierLoss (line 260) | class CharbonnierLoss(nn.Module):
    method __init__ (line 263) | def __init__(self, eps=1e-6):
    method forward (line 267) | def forward(self, x, y):
  class GradientPenaltyLoss (line 273) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 274) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 279) | def get_grad_outputs(self, input):
    method forward (line 284) | def forward(self, interp, interp_crit):

FILE: codes/config/Maeda/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/Maeda/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/Maeda/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/Maeda/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/Maeda/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/Maeda/archs/translator.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class BasicBlock (line 17) | class BasicBlock(nn.Sequential):
    method __init__ (line 18) | def __init__(
  class ResBlock (line 46) | class ResBlock(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 70) | def forward(self, x):
  class Upsampler (line 77) | class Upsampler(nn.Sequential):
    method __init__ (line 78) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  class Translator (line 105) | class Translator(nn.Module):
    method __init__ (line 106) | def __init__(self, nb, nf, noise_nf=0, scale=4, zero_tail=False, conv=...
    method forward (line 138) | def forward(self, x):

FILE: codes/config/Maeda/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/Maeda/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/Maeda/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/Maeda/models/pseudo_supervision_model.py
  class PseudoSupModel (line 15) | class PseudoSupModel(BaseModel):
    method __init__ (line 16) | def __init__(self, opt):
    method feed_data (line 58) | def feed_data(self, data):
    method forward (line 63) | def forward(self):
    method optimize_parameters (line 74) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 159) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 169) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method test (line 176) | def test(self, data):
    method get_current_visuals (line 184) | def get_current_visuals(self, need_GT=True):

FILE: codes/config/Maeda/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/Maeda/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/PDM-SR/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/PDM-SR/archs/deg_arch.py
  class ResBlock (line 9) | class ResBlock(nn.Module):
    method __init__ (line 10) | def __init__(self, nf, ksize, norm=nn.BatchNorm2d, act=nn.ReLU):
    method forward (line 20) | def forward(self, x):
  class Quantization (line 23) | class Quantization(nn.Module):
    method __init__ (line 24) | def __init__(self, n=5):
    method forward (line 28) | def forward(self, inp):
  class KernelModel (line 36) | class KernelModel(nn.Module):
    method __init__ (line 37) | def __init__(self, opt, scale):
    method forward (line 76) | def forward(self, x):
  class NoiseModel (line 110) | class NoiseModel(nn.Module):
    method __init__ (line 111) | def __init__(self, opt, scale):
    method forward (line 148) | def forward(self, x):
  class DegModel (line 172) | class DegModel(nn.Module):
    method __init__ (line 173) | def __init__(
    method forward (line 192) | def forward(self, inp):

FILE: codes/config/PDM-SR/archs/discriminator.py
  class DiscriminatorVGG128 (line 12) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 13) | def __init__(self, in_nc, nf):
    method forward (line 46) | def forward(self, x):
  class DiscriminatorVGG32 (line 69) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 70) | def __init__(self, in_nc, nf):
    method forward (line 103) | def forward(self, x):
  class PatchGANDiscriminator (line 126) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 129) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 190) | def forward(self, input):
  class UNetDiscriminatorSN (line 196) | class UNetDiscriminatorSN(nn.Module):
    method __init__ (line 199) | def __init__(self, nc, nf=64, skip_connection=True):
    method forward (line 220) | def forward(self, x):

FILE: codes/config/PDM-SR/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/PDM-SR/archs/loss.py
  class TVLoss (line 12) | class TVLoss(nn.Module):
    method __init__ (line 13) | def __init__(self, penealty="L1Loss"):
    method forward (line 17) | def forward(self, pred):
  class GaussGuided (line 26) | class GaussGuided(nn.Module):
    method __init__ (line 27) | def __init__(self, ksize, sigma):
    method forward (line 38) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 43) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 44) | def __init__(self, net="alex", normalize=True):
    method forward (line 52) | def forward(self, res, ref):
  class MSELoss (line 57) | class MSELoss(nn.Module):
    method __init__ (line 58) | def __init__(self, *args, **kwargs):
    method forward (line 61) | def forward(self, res, ref):
  class L1Loss (line 66) | class L1Loss(nn.Module):
    method __init__ (line 67) | def __init__(self, *args, **kwargs):
    method forward (line 70) | def forward(self, res, ref):
  class GANLoss (line 75) | class GANLoss(nn.Module):
    method __init__ (line 83) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 102) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 112) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 126) | def get_target_label(self, input, target_is_real):
    method forward (line 141) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 166) | class PerceptualLoss(nn.Module):
    method __init__ (line 188) | def __init__(
    method forward (line 219) | def forward(self, x, gt):
    method _gram_mat (line 276) | def _gram_mat(self, x):
  class CharbonnierLoss (line 291) | class CharbonnierLoss(nn.Module):
    method __init__ (line 294) | def __init__(self, eps=1e-6):
    method forward (line 298) | def forward(self, x, y):
  class GradientPenaltyLoss (line 304) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 305) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 310) | def get_grad_outputs(self, input):
    method forward (line 315) | def forward(self, interp, interp_crit):

FILE: codes/config/PDM-SR/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 32) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 33) | def __init__(
    method get_lr (line 53) | def get_lr(self):
  class CosineAnnealingRestartLR (line 69) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 70) | def __init__(
    method get_lr (line 84) | def get_lr(self):

FILE: codes/config/PDM-SR/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/PDM-SR/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/PDM-SR/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/PDM-SR/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/PDM-SR/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/PDM-SR/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/PDM-SR/models/base_model.py
  class BaseModel (line 16) | class BaseModel:
    method __init__ (line 17) | def __init__(self, opt):
    method setup_train (line 37) | def setup_train(self, train_opt):
    method feed_data (line 53) | def feed_data(self, data):
    method optimize_parameters (line 56) | def optimize_parameters(self):
    method get_current_visuals (line 59) | def get_current_visuals(self):
    method get_current_losses (line 62) | def get_current_losses(self):
    method print_network (line 65) | def print_network(self):
    method save (line 68) | def save(self, label):
    method load (line 71) | def load(self):
    method build_network (line 74) | def build_network(self, net_opt):
    method build_losses (line 88) | def build_losses(self, loss_opt):
    method build_optimizers (line 102) | def build_optimizers(self, optim_opts):
    method build_schedulers (line 127) | def build_schedulers(self, scheduler_opts):
    method model_to_device (line 142) | def model_to_device(self, net):
    method print_network (line 155) | def print_network(self, net):
    method set_optimizer (line 172) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 176) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 182) | def set_network_state(self, names, state):
    method clip_grad_norm (line 187) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 191) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 198) | def _get_init_lr(self):
    method update_learning_rate (line 205) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 219) | def get_current_learning_rate(self):
    method get_network_description (line 223) | def get_network_description(self, network):
    method save_network (line 233) | def save_network(self, network, network_label, iter_label):
    method save (line 245) | def save(self, iter_label):
    method load_network (line 249) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 264) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 275) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 290) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 315) | def get_current_log(self):

FILE: codes/config/PDM-SR/models/deg_sr_model.py
  class Quant (line 15) | class Quant(torch.autograd.Function):
    method forward (line 18) | def forward(ctx, input):
    method backward (line 24) | def backward(ctx, grad_output):
  class Quantization (line 27) | class Quantization(nn.Module):
    method __init__ (line 28) | def __init__(self):
    method forward (line 31) | def forward(self, input):
  class DegSRModel (line 36) | class DegSRModel(BaseModel):
    method __init__ (line 37) | def __init__(self, opt):
    method feed_data (line 89) | def feed_data(self, data):
    method deg_forward (line 94) | def deg_forward(self):
    method sr_forward (line 104) | def sr_forward(self):
    method optimize_trans_models (line 115) | def optimize_trans_models(self, step, loss_dict):
    method optimize_sr_models (line 176) | def optimize_sr_models(self, step, loss_dict):
    method optimize_parameters (line 230) | def optimize_parameters(self, step):
    method calculate_gan_loss_D (line 243) | def calculate_gan_loss_D(self, netD, criterion, real, fake):
    method calculate_gan_loss_G (line 253) | def calculate_gan_loss_G(self, netD, criterion, real, fake):
    method test (line 260) | def test(self, test_data, crop_size=None):
    method get_current_visuals (line 280) | def get_current_visuals(self, need_GT=True):
    method crop_test (line 288) | def crop_test(self, lr, crop_size):
  class ShuffleBuffer (line 337) | class ShuffleBuffer():
    method __init__ (line 343) | def __init__(self, buffer_size):
    method choose (line 352) | def choose(self, images, prob=0.5):

FILE: codes/config/PDM-SR/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/PDM-SR/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/config/RealESRGAN/archs/__init__.py
  function build_network (line 19) | def build_network(net_opt):
  function build_loss (line 25) | def build_loss(loss_opt):
  function build_scheduler (line 30) | def build_scheduler(optimizer, scheduler_opt):

FILE: codes/config/RealESRGAN/archs/discriminator.py
  class DiscriminatorVGG128 (line 10) | class DiscriminatorVGG128(nn.Module):
    method __init__ (line 11) | def __init__(self, in_nc, nf):
    method forward (line 44) | def forward(self, x):
  class DiscriminatorVGG32 (line 67) | class DiscriminatorVGG32(nn.Module):
    method __init__ (line 68) | def __init__(self, in_nc, nf):
    method forward (line 101) | def forward(self, x):
  class PatchGANDiscriminator (line 124) | class PatchGANDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, in_c, nf, nb, stride=1, norm_layer=nn.InstanceNorm2d):
    method forward (line 188) | def forward(self, input):

FILE: codes/config/RealESRGAN/archs/edsr.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(
  class BasicBlock (line 34) | class BasicBlock(nn.Sequential):
    method __init__ (line 35) | def __init__(
  class ResBlock (line 63) | class ResBlock(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 87) | def forward(self, x):
  class Upsampler (line 94) | class Upsampler(nn.Sequential):
    method __init__ (line 95) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 121) | def make_model(args, parent=False):
  class EDSR (line 129) | class EDSR(nn.Module):
    method __init__ (line 130) | def __init__(self, nb, nf, res_scale=0.1, upscale=4, conv=default_conv):
    method forward (line 166) | def forward(self, x):

FILE: codes/config/RealESRGAN/archs/loss.py
  class GaussGuided (line 12) | class GaussGuided(nn.Module):
    method __init__ (line 13) | def __init__(self, ksize, sigma):
    method forward (line 24) | def forward(self, kernel):
  class PerceptualLossLPIPS (line 29) | class PerceptualLossLPIPS(nn.Module):
    method __init__ (line 30) | def __init__(self, net="alex", normalize=True):
    method forward (line 38) | def forward(self, res, ref):
  class MSELoss (line 43) | class MSELoss(nn.Module):
    method __init__ (line 44) | def __init__(self, *args, **kwargs):
    method forward (line 47) | def forward(self, res, ref):
  class L1Loss (line 52) | class L1Loss(nn.Module):
    method __init__ (line 53) | def __init__(self, *args, **kwargs):
    method forward (line 56) | def forward(self, res, ref):
  class GANLoss (line 61) | class GANLoss(nn.Module):
    method __init__ (line 69) | def __init__(self, gan_type, real_label_val=1.0, fake_label_val=0.0):
    method _wgan_loss (line 88) | def _wgan_loss(self, input, target):
    method _wgan_softplus_loss (line 98) | def _wgan_softplus_loss(self, input, target):
    method get_target_label (line 112) | def get_target_label(self, input, target_is_real):
    method forward (line 127) | def forward(self, input, target_is_real, is_disc=False):
  class PerceptualLoss (line 152) | class PerceptualLoss(nn.Module):
    method __init__ (line 174) | def __init__(
    method forward (line 205) | def forward(self, x, gt):
    method _gram_mat (line 262) | def _gram_mat(self, x):
  class CharbonnierLoss (line 277) | class CharbonnierLoss(nn.Module):
    method __init__ (line 280) | def __init__(self, eps=1e-6):
    method forward (line 284) | def forward(self, x, y):
  class GradientPenaltyLoss (line 290) | class GradientPenaltyLoss(nn.Module):
    method __init__ (line 291) | def __init__(self, device=torch.device("cpu")):
    method get_grad_outputs (line 296) | def get_grad_outputs(self, input):
    method forward (line 301) | def forward(self, interp, interp_crit):

FILE: codes/config/RealESRGAN/archs/lr_scheduler.py
  class LinearDecayLR (line 11) | class LinearDecayLR(_LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 24) | def get_lr(self):
  class MultiStepRestartLR (line 34) | class MultiStepRestartLR(_LRScheduler):
    method __init__ (line 35) | def __init__(
    method get_lr (line 55) | def get_lr(self):
  class CosineAnnealingRestartLR (line 72) | class CosineAnnealingRestartLR(_LRScheduler):
    method __init__ (line 73) | def __init__(
    method get_lr (line 87) | def get_lr(self):

FILE: codes/config/RealESRGAN/archs/module_util.py
  function initialize_weights (line 7) | def initialize_weights(net_l, scale=1):
  function make_layer (line 27) | def make_layer(block, n_layers):
  class ResidualBlock_noBN (line 34) | class ResidualBlock_noBN(nn.Module):
    method __init__ (line 40) | def __init__(self, nf=64):
    method forward (line 48) | def forward(self, x):
  function flow_warp (line 55) | def flow_warp(x, flow, interp_mode="bilinear", padding_mode="zeros"):

FILE: codes/config/RealESRGAN/archs/rcan.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 17) | class MeanShift(nn.Conv2d):
    method __init__ (line 18) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class BasicBlock (line 28) | class BasicBlock(nn.Sequential):
    method __init__ (line 29) | def __init__(
  class ResBlock (line 57) | class ResBlock(nn.Module):
    method __init__ (line 58) | def __init__(
    method forward (line 81) | def forward(self, x):
  class Upsampler (line 88) | class Upsampler(nn.Sequential):
    method __init__ (line 89) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  function make_model (line 113) | def make_model(args, parent=False):
  class CALayer (line 118) | class CALayer(nn.Module):
    method __init__ (line 119) | def __init__(self, channel, reduction=16):
    method forward (line 131) | def forward(self, x):
  class RCAB (line 138) | class RCAB(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 163) | def forward(self, x):
  class ResidualGroup (line 171) | class ResidualGroup(nn.Module):
    method __init__ (line 172) | def __init__(
    method forward (line 193) | def forward(self, x):
  class RCAN (line 201) | class RCAN(nn.Module):
    method __init__ (line 202) | def __init__(self, ng, nb, nf, reduction=16, upscale=4, conv=default_c...
    method forward (line 250) | def forward(self, x):
    method load_state_dict (line 262) | def load_state_dict(self, state_dict, strict=False):

FILE: codes/config/RealESRGAN/archs/rrdb.py
  class ResidualDenseBlock_5C (line 8) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 9) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 24) | def forward(self, x):
  class RRDB (line 33) | class RRDB(nn.Module):
    method __init__ (line 36) | def __init__(self, nf, gc=32):
    method forward (line 42) | def forward(self, x):
  class RRDBNet (line 50) | class RRDBNet(nn.Module):
    method __init__ (line 51) | def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4):
    method forward (line 68) | def forward(self, x):

FILE: codes/config/RealESRGAN/archs/srresnet.py
  class MSRResNet (line 9) | class MSRResNet(nn.Module):
    method __init__ (line 12) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=16, upscale=4):
    method forward (line 45) | def forward(self, x):

FILE: codes/config/RealESRGAN/archs/translator.py
  function default_conv (line 11) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class BasicBlock (line 17) | class BasicBlock(nn.Sequential):
    method __init__ (line 18) | def __init__(
  class ResBlock (line 46) | class ResBlock(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 70) | def forward(self, x):
  class Upsampler (line 77) | class Upsampler(nn.Sequential):
    method __init__ (line 78) | def __init__(self, conv, scale, n_feat, bn=False, act=False, bias=True):
  class Translator (line 105) | class Translator(nn.Module):
    method __init__ (line 106) | def __init__(self, in_nc, out_nc, nf, nb, scale=4, conv=default_conv):
    method forward (line 134) | def forward(self, x):

FILE: codes/config/RealESRGAN/archs/vgg.py
  function insert_bn (line 137) | def insert_bn(names):
  class VGGFeatureExtractor (line 154) | class VGGFeatureExtractor(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 246) | def forward(self, x):

FILE: codes/config/RealESRGAN/models/__init__.py
  function create_model (line 21) | def create_model(opt, **kwarg):

FILE: codes/config/RealESRGAN/models/base_model.py
  class BaseModel (line 18) | class BaseModel:
    method __init__ (line 19) | def __init__(self, opt):
    method feed_data (line 39) | def feed_data(self, data):
    method optimize_parameters (line 42) | def optimize_parameters(self):
    method get_current_visuals (line 45) | def get_current_visuals(self):
    method get_current_losses (line 48) | def get_current_losses(self):
    method print_network (line 51) | def print_network(self):
    method save (line 54) | def save(self, label):
    method load (line 57) | def load(self):
    method build_network (line 60) | def build_network(self, net_opt):
    method build_loss (line 72) | def build_loss(self, loss_config):
    method build_optimizer (line 78) | def build_optimizer(net, optim_config):
    method setup_schedulers (line 89) | def setup_schedulers(self, scheduler_opt):
    method model_to_device (line 107) | def model_to_device(self, net):
    method print_network (line 120) | def print_network(self, net):
    method set_optimizer (line 137) | def set_optimizer(self, names, operation):
    method set_requires_grad (line 141) | def set_requires_grad(self, names, requires_grad):
    method set_network_state (line 146) | def set_network_state(self, names, state):
    method clip_grad_norm (line 150) | def clip_grad_norm(self, names, norm):
    method _set_lr (line 154) | def _set_lr(self, lr_groups_l):
    method _get_init_lr (line 161) | def _get_init_lr(self):
    method update_learning_rate (line 168) | def update_learning_rate(self, cur_iter, warmup_iter=-1):
    method get_current_learning_rate (line 182) | def get_current_learning_rate(self):
    method get_network_description (line 186) | def get_network_description(self, network):
    method save_network (line 196) | def save_network(self, network, network_label, iter_label):
    method save (line 208) | def save(self, iter_label):
    method load_network (line 212) | def load_network(self, network, load_path, strict=True):
    method save_training_state (line 227) | def save_training_state(self, epoch, iter_step):
    method resume_training (line 238) | def resume_training(self, resume_state):
    method reduce_loss_dict (line 253) | def reduce_loss_dict(self, loss_dict):
    method get_current_log (line 278) | def get_current_log(self):

FILE: codes/config/RealESRGAN/models/sr_model.py
  class SRModel (line 15) | class SRModel(BaseModel):
    method __init__ (line 16) | def __init__(self, opt):
    method __init__ (line 41) | def __init__(self, opt):
    method feed_data (line 67) | def feed_data(self, data):
    method forward (line 72) | def forward(self):
    method optimize_parameters (line 76) | def optimize_parameters(self, step):
    method calculate_rgan_loss_D (line 121) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 136) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 147) | def test(self, data, crop_size=None):
    method crop_test (line 157) | def crop_test(self, lr, crop_size):
    method get_current_visuals (line 205) | def get_current_visuals(self, need_GT=True):
    method feed_data (line 254) | def feed_data(self, data):
    method forward (line 259) | def forward(self):
    method optimize_parameters (line 263) | def optimize_parameters(self, step):
    method calculate_rgan_loss_D (line 308) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 323) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 334) | def test(self, data, crop_size=None):
    method crop_test (line 344) | def crop_test(self, lr, crop_size):
    method get_current_visuals (line 392) | def get_current_visuals(self, need_GT=True):
  class SRModel (line 40) | class SRModel(BaseModel):
    method __init__ (line 16) | def __init__(self, opt):
    method __init__ (line 41) | def __init__(self, opt):
    method feed_data (line 67) | def feed_data(self, data):
    method forward (line 72) | def forward(self):
    method optimize_parameters (line 76) | def optimize_parameters(self, step):
    method calculate_rgan_loss_D (line 121) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 136) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 147) | def test(self, data, crop_size=None):
    method crop_test (line 157) | def crop_test(self, lr, crop_size):
    method get_current_visuals (line 205) | def get_current_visuals(self, need_GT=True):
    method feed_data (line 254) | def feed_data(self, data):
    method forward (line 259) | def forward(self):
    method optimize_parameters (line 263) | def optimize_parameters(self, step):
    method calculate_rgan_loss_D (line 308) | def calculate_rgan_loss_D(self, netD, criterion, real, fake):
    method calculate_rgan_loss_G (line 323) | def calculate_rgan_loss_G(self, netD, criterion, real, fake):
    method test (line 334) | def test(self, data, crop_size=None):
    method crop_test (line 344) | def crop_test(self, lr, crop_size):
    method get_current_visuals (line 392) | def get_current_visuals(self, need_GT=True):

FILE: codes/config/RealESRGAN/test.py
  function parse_args (line 22) | def parse_args():
  function main (line 57) | def main():
  function main_worker (line 85) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 166) | def validate(

FILE: codes/config/RealESRGAN/train.py
  function parse_args (line 25) | def parse_args():
  function setup_dataloaer (line 60) | def setup_dataloaer(opt, logger):
  function main (line 105) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, opt, args):
  function validate (line 307) | def validate(model, dataset, dist_loader, opt, measure, epoch, current_s...

FILE: codes/data/__init__.py
  class DataLoaderX (line 28) | class DataLoaderX(DataLoader):
    method __iter__ (line 30) | def __iter__(self):
  function create_dataloader (line 33) | def create_dataloader(dataset, dataset_opt, dist=False):
  function create_dataset (line 77) | def create_dataset(dataset_opt, **kwarg):
  function worker_init_fn (line 88) | def worker_init_fn(worker_id, num_workers, rank, seed):

FILE: codes/data/data_sampler.py
  class DistIterSampler (line 13) | class DistIterSampler(Sampler):
    method __init__ (line 31) | def __init__(self, dataset, num_replicas=None, rank=None):
    method __iter__ (line 47) | def __iter__(self):
    method __len__ (line 64) | def __len__(self):
    method set_epoch (line 67) | def set_epoch(self, epoch):

FILE: codes/data/debug_dataset.py
  class DebugDataset (line 16) | class DebugDataset(data.Dataset):
    method __init__ (line 21) | def __init__(self, opt):
    method _init_lmdb (line 44) | def _init_lmdb(self, dataroots):
    method __getitem__ (line 55) | def __getitem__(self, index):
    method __len__ (line 151) | def __len__(self):

FILE: codes/data/fixed_image_dataset.py
  class FixedImageDataset (line 16) | class FixedImageDataset(data.Dataset):
    method __init__ (line 21) | def __init__(self, opt, img_path):
    method _init_lmdb (line 37) | def _init_lmdb(self, dataroots):
    method __getitem__ (line 48) | def __getitem__(self, index):
    method __len__ (line 132) | def __len__(self):

FILE: codes/data/paired_ref_dataset.py
  class PairedRefDataset (line 16) | class PairedRefDataset(data.Dataset):
    method __init__ (line 22) | def __init__(self, opt):
    method _init_lmdb (line 59) | def _init_lmdb(self, dataroots):
    method __getitem__ (line 70) | def __getitem__(self, index):
    method __len__ (line 187) | def __len__(self):

FILE: codes/data/paried_dataset.py
  class PairedDataset (line 16) | class PairedDataset(data.Dataset):
    method __init__ (line 22) | def __init__(self, opt):
    method _init_lmdb (line 43) | def _init_lmdb(self, dataroots):
    method __getitem__ (line 54) | def __getitem__(self, index):
    method __len__ (line 141) | def __len__(self):

FILE: codes/data/single_dataset.py
  class SingleImageDataset (line 16) | class SingleImageDataset(data.Dataset):
    method __init__ (line 22) | def __init__(self, opt):
    method _init_lmdb (line 33) | def _init_lmdb(self, dataroots):
    method __getitem__ (line 44) | def __getitem__(self, index):
    method __len__ (line 97) | def __len__(self):

FILE: codes/data/single_image_dataset.py
  class SingleDataset (line 16) | class SingleDataset(data.Dataset):
    method __init__ (line 22) | def __init__(self, opt):
    method _init_lmdb (line 33) | def _init_lmdb(self, dataroots):
    method __getitem__ (line 44) | def __getitem__(self, index):
    method __len__ (line 97) | def __len__(self):

FILE: codes/data/unpaired_dataset.py
  class UnPairedDataset (line 16) | class UnPairedDataset(data.Dataset):
    method __init__ (line 21) | def __init__(self, opt):
    method _init_lmdb (line 44) | def _init_lmdb(self, dataroots):
    method __getitem__ (line 55) | def __getitem__(self, index):
    method __len__ (line 149) | def __len__(self):

FILE: codes/metrics/best_psnr.py
  function ignore_boundary (line 6) | def ignore_boundary(img, SCALE):
  function best_psnr (line 13) | def best_psnr(img_orig, img_out):

FILE: codes/metrics/measure.py
  class IQA (line 12) | class IQA:
    method __init__ (line 18) | def __init__(self, metrics, lpips_type="alex", cuda=True):
    method __call__ (line 38) | def __call__(self, res, ref=None, metrics=["niqe"]):
    method calculate_lpips (line 67) | def calculate_lpips(self, res, ref):
    method calculate_niqe (line 78) | def calculate_niqe(self, res):
    method calculate_brisque (line 81) | def calculate_brisque(self, res):
    method calculate_piqe (line 84) | def calculate_piqe(self, piqe):
    method calculate_best_psnr (line 87) | def calculate_best_psnr(self, res, ref):
    method calculate_best_ssim (line 92) | def calculate_best_ssim(self, res, ref):
    method calculate_psnr (line 97) | def calculate_psnr(res, ref):
    method calculate_ssim (line 101) | def calculate_ssim(res, ref):

FILE: codes/metrics/psnr.py
  function psnr (line 6) | def psnr(img1, img2):

FILE: codes/metrics/ssim.py
  function ssim (line 7) | def ssim(img1, img2):
  function calculate_ssim (line 31) | def calculate_ssim(img1, img2):

FILE: codes/scripts/extract_subimgs_single.py
  function main (line 16) | def main():
  function worker (line 59) | def worker(path, save_folder, crop_sz, step, thres_sz, compression_level):

FILE: codes/scripts/generate_mod_LR_bic.py
  function generate_mod_LR_bic (line 14) | def generate_mod_LR_bic():

FILE: codes/scripts/generate_mod_blur_LR_bic.py
  function generate_mod_LR_bic (line 16) | def generate_mod_LR_bic():

FILE: codes/scripts/test_imgs.py
  function parse_argumnets (line 16) | def parse_argumnets():
  function bgr2ycbcr (line 34) | def bgr2ycbcr(img, only_y=True):
  function main (line 68) | def main():

FILE: codes/utils/data_utils.py
  function is_image_file (line 26) | def is_image_file(filename):
  function _get_paths_from_images (line 30) | def _get_paths_from_images(path):
  function _get_paths_from_lmdb (line 43) | def _get_paths_from_lmdb(dataroot):
  function get_image_paths (line 53) | def get_image_paths(data_type, dataroot):
  function _read_img_lmdb (line 72) | def _read_img_lmdb(env, key, size):
  function read_img (line 83) | def read_img(env, path, size=None):
  function augment (line 103) | def augment(img, hflip=True, rot=True, mode=None):
  function augment_flow (line 124) | def augment_flow(img_list, flow_list, hflip=True, rot=True):

FILE: codes/utils/deg_utils.py
  function DUF_downsample (line 12) | def DUF_downsample(x, scale=4):
  function PCA (line 49) | def PCA(data, k=2):
  function random_batch_kernel (line 57) | def random_batch_kernel(
  function stable_batch_kernel (line 117) | def stable_batch_kernel(batch, l=21, sig=2.6, tensor=True):
  function b_Bicubic (line 128) | def b_Bicubic(variable, scale):
  function random_batch_noise (line 137) | def random_batch_noise(batch, high, rate_cln=1.0):
  function b_GaussianNoising (line 145) | def b_GaussianNoising(tensor, sigma, mean=0.0, noise_size=None, min=0.0,...
  function b_GaussianNoising (line 157) | def b_GaussianNoising(tensor, noise_high, mean=0.0, noise_size=None, min...
  class BatchSRKernel (line 168) | class BatchSRKernel(object):
    method __init__ (line 169) | def __init__(
    method __call__ (line 185) | def __call__(self, random, batch, tensor=False):
  class BatchBlurKernel (line 200) | class BatchBlurKernel(object):
    method __init__ (line 201) | def __init__(self, kernels_path):
    method __call__ (line 206) | def __call__(self, random, batch, tensor=False):
  class PCAEncoder (line 212) | class PCAEncoder(nn.Module):
    method __init__ (line 213) | def __init__(self, weight):
    method forward (line 218) | def forward(self, batch_kernel):
  class BatchBlur (line 225) | class BatchBlur(object):
    method __init__ (line 226) | def __init__(self, l=15):
    method __call__ (line 234) | def __call__(self, input, kernel):
  class SRMDPreprocessing (line 254) | class SRMDPreprocessing(object):
    method __init__ (line 255) | def __init__(
    method __call__ (line 299) | def __call__(self, hr_tensor, kernel=False):

FILE: codes/utils/file_utils.py
  function get_timestamp (line 18) | def get_timestamp():
  function mkdir (line 22) | def mkdir(path):
  function mkdirs (line 27) | def mkdirs(paths):
  function mkdir_and_rename (line 35) | def mkdir_and_rename(path):
  function set_random_seed (line 45) | def set_random_seed(seed):
  function setup_logger (line 52) | def setup_logger(
  class ProgressBar (line 74) | class ProgressBar(object):
    method __init__ (line 79) | def __init__(self, task_num=0, bar_width=50, start=True):
    method _get_max_bar_width (line 87) | def _get_max_bar_width(self):
    method start (line 98) | def start(self):
    method update (line 110) | def update(self, msg="In progress..."):

FILE: codes/utils/img_utils.py
  function tensor2img (line 12) | def tensor2img(tensor, out_type=np.uint8, min_max=(0, 1)):
  function save_img (line 42) | def save_img(img, img_path, mode="BGR"):
  function img2tensor (line 46) | def img2tensor(img):
  function channel_convert (line 58) | def channel_convert(tar_type, img_list):
  function rgb2ycbcr (line 92) | def rgb2ycbcr(img, only_y=True):
  function bgr2ycbcr (line 126) | def bgr2ycbcr(img, only_y=True):
  function ycbcr2rgb (line 160) | def ycbcr2rgb(img):
  function modcrop (line 190) | def modcrop(img_in, scale):

FILE: codes/utils/option.py
  function ordered_yaml (line 10) | def ordered_yaml():
  function parse (line 34) | def parse(opt_path, root_path=".", is_train=True):
  function dict2str (line 82) | def dict2str(opt, indent_l=1):
  class NoneDict (line 95) | class NoneDict(dict):
    method __missing__ (line 96) | def __missing__(self, key):
  function dict_to_nonedict (line 101) | def dict_to_nonedict(opt):

FILE: codes/utils/registry.py
  class Registry (line 2) | class Registry:
    method __init__ (line 19) | def __init__(self, name):
    method _do_register (line 27) | def _do_register(self, name, obj):
    method register (line 34) | def register(self, obj=None):
    method get (line 53) | def get(self, name):
    method __contains__ (line 61) | def __contains__(self, name):
    method __iter__ (line 64) | def __iter__(self):
    method keys (line 67) | def keys(self):

FILE: codes/utils/resize_utils.py
  function cubic (line 8) | def cubic(x):
  function calculate_weights_indices (line 19) | def calculate_weights_indices(
  function imresize (line 77) | def imresize(img, scale, antialiasing=True):