SYMBOL INDEX (154 symbols across 19 files)

FILE: data/__init__.py
  class Data (line 4) | class Data:
    method __init__ (line 5) | def __init__(self, args):

FILE: data/benchmark.py
  class Benchmark (line 6) | class Benchmark(srdata.SRData):
    method __init__ (line 7) | def __init__(self, args, name='', train=True):
    method _set_filesystem (line 12) | def _set_filesystem(self, dir_data):

FILE: data/common.py
  function get_patch (line 7) | def get_patch(img, patch_size=48, scale=1):
  function set_channel (line 18) | def set_channel(img, n_channels=3):
  function np2Tensor (line 31) | def np2Tensor(img, rgb_range=255):
  function augment (line 39) | def augment(img, hflip=True, rot=True):

FILE: data/df2k.py
  class DF2K (line 5) | class DF2K(multiscalesrdata.SRData):
    method __init__ (line 6) | def __init__(self, args, name='DF2K', train=True, benchmark=False):
    method _scan (line 9) | def _scan(self):
    method _set_filesystem (line 15) | def _set_filesystem(self, dir_data):

FILE: data/multiscalesrdata.py
  class SRData (line 13) | class SRData(data.Dataset):
    method __init__ (line 14) | def __init__(self, args, name='', train=True, benchmark=False):
    method _scan (line 68) | def _scan(self):
    method _set_filesystem (line 76) | def _set_filesystem(self, dir_data):
    method _name_hrbin (line 82) | def _name_hrbin(self):
    method _name_lrbin (line 89) | def _name_lrbin(self, scale):
    method _check_and_load (line 96) | def _check_and_load(self, ext, l, f, verbose=True, load=True):
    method __getitem__ (line 119) | def __getitem__(self, idx):
    method __len__ (line 128) | def __len__(self):
    method _get_index (line 134) | def _get_index(self, idx):
    method _load_file (line 140) | def _load_file(self, idx):
    method get_patch (line 157) | def get_patch(self, hr):
    method set_scale (line 174) | def set_scale(self, idx_scale):

FILE: dataloader.py
  function _ms_loop (line 20) | def _ms_loop(dataset, index_queue, data_queue, collate_fn, scale, seed, ...
  class _MSDataLoaderIter (line 46) | class _MSDataLoaderIter(_DataLoaderIter):
    method __init__ (line 47) | def __init__(self, loader):
  class MSDataLoader (line 117) | class MSDataLoader(DataLoader):
    method __init__ (line 118) | def __init__(
    method __iter__ (line 133) | def __iter__(self):

FILE: loss/__init__.py
  class Loss (line 13) | class Loss(nn.modules.loss._Loss):
    method __init__ (line 14) | def __init__(self, args, ckp):
    method forward (line 70) | def forward(self, sr, hr):
    method step (line 87) | def step(self):
    method start_log (line 92) | def start_log(self):
    method end_log (line 95) | def end_log(self, n_batches):
    method display_loss (line 98) | def display_loss(self, batch):
    method plot_loss (line 106) | def plot_loss(self, apath, epoch):
    method get_loss_module (line 120) | def get_loss_module(self):
    method save (line 126) | def save(self, apath):
    method load (line 130) | def load(self, apath, cpu=False):

FILE: loss/adversarial.py
  class Adversarial (line 11) | class Adversarial(nn.Module):
    method __init__ (line 12) | def __init__(self, args, gan_type):
    method forward (line 26) | def forward(self, fake, real):
    method state_dict (line 78) | def state_dict(self, *args, **kwargs):

FILE: loss/discriminator.py
  class Discriminator (line 5) | class Discriminator(nn.Module):
    method __init__ (line 6) | def __init__(self, args, gan_type='GAN'):
    method forward (line 40) | def forward(self, x):

FILE: loss/vgg.py
  class VGG (line 9) | class VGG(nn.Module):
    method __init__ (line 10) | def __init__(self, conv_index, rgb_range=1):
    method forward (line 24) | def forward(self, sr, hr):

FILE: moco/builder.py
  class MoCo (line 6) | class MoCo(nn.Module):
    method __init__ (line 11) | def __init__(self, base_encoder, dim=256, K=32*256, m=0.999, T=0.07, m...
    method _momentum_update_key_encoder (line 40) | def _momentum_update_key_encoder(self):
    method _dequeue_and_enqueue (line 48) | def _dequeue_and_enqueue(self, keys):
    method _batch_shuffle_ddp (line 63) | def _batch_shuffle_ddp(self, x):
    method _batch_unshuffle_ddp (line 91) | def _batch_unshuffle_ddp(self, x, idx_unshuffle):
    method forward (line 109) | def forward(self, im_q, im_k):
  function concat_all_gather (line 157) | def concat_all_gather(tensor):

FILE: model/__init__.py
  class Model (line 8) | class Model(nn.Module):
    method __init__ (line 9) | def __init__(self, args, ckp):
    method forward (line 38) | def forward(self, x):
    method get_model (line 51) | def get_model(self):
    method state_dict (line 57) | def state_dict(self, **kwargs):
    method save (line 61) | def save(self, apath, epoch, is_best=False):
    method load (line 79) | def load(self, apath, pre_train='.', resume=-1, cpu=False):
    method forward_chop (line 104) | def forward_chop(self, x, shave=10, min_size=160000):
    method forward_x8 (line 145) | def forward_x8(self, x, forward_function):

FILE: model/blindsr.py
  function make_model (line 8) | def make_model(args):
  class DA_conv (line 12) | class DA_conv(nn.Module):
    method __init__ (line 13) | def __init__(self, channels_in, channels_out, kernel_size, reduction):
    method forward (line 29) | def forward(self, x):
  class CA_layer (line 47) | class CA_layer(nn.Module):
    method __init__ (line 48) | def __init__(self, channels_in, channels_out, reduction):
    method forward (line 57) | def forward(self, x):
  class DAB (line 67) | class DAB(nn.Module):
    method __init__ (line 68) | def __init__(self, conv, n_feat, kernel_size, reduction):
    method forward (line 78) | def forward(self, x):
  class DAG (line 92) | class DAG(nn.Module):
    method __init__ (line 93) | def __init__(self, conv, n_feat, kernel_size, reduction, n_blocks):
    method forward (line 104) | def forward(self, x):
  class DASR (line 118) | class DASR(nn.Module):
    method __init__ (line 119) | def __init__(self, args, conv=common.default_conv):
    method forward (line 158) | def forward(self, x, k_v):
  class Encoder (line 183) | class Encoder(nn.Module):
    method __init__ (line 184) | def __init__(self):
    method forward (line 214) | def forward(self, x):
  class BlindSR (line 221) | class BlindSR(nn.Module):
    method __init__ (line 222) | def __init__(self, args):
    method forward (line 231) | def forward(self, x):

FILE: model/common.py
  function default_conv (line 7) | def default_conv(in_channels, out_channels, kernel_size, bias=True):
  class MeanShift (line 11) | class MeanShift(nn.Conv2d):
    method __init__ (line 12) | def __init__(self, rgb_range, rgb_mean, rgb_std, sign=-1):
  class Upsampler (line 23) | class Upsampler(nn.Sequential):
    method __init__ (line 24) | def __init__(self, conv, scale, n_feat, act=False, bias=True):

FILE: quick_test.py
  function parse_args (line 11) | def parse_args():
  function main (line 24) | def main():

FILE: template.py
  function set_template (line 1) | def set_template(args):

FILE: trainer.py
  class Trainer (line 9) | class Trainer():
    method __init__ (line 10) | def __init__(self, args, loader, my_model, my_loss, ckp):
    method train (line 30) | def train(self):
    method test (line 128) | def test(self):
    method crop_border (line 192) | def crop_border(self, img_hr, scale):
    method terminate (line 199) | def terminate(self):

FILE: utility.py
  class AverageMeter (line 14) | class AverageMeter(object):
    method __init__ (line 16) | def __init__(self):
    method reset (line 19) | def reset(self):
    method update (line 25) | def update(self, val, n=1):
  class timer (line 32) | class timer():
    method __init__ (line 33) | def __init__(self):
    method tic (line 37) | def tic(self):
    method toc (line 40) | def toc(self):
    method hold (line 43) | def hold(self):
    method release (line 46) | def release(self):
    method reset (line 52) | def reset(self):
  class checkpoint (line 56) | class checkpoint():
    method __init__ (line 57) | def __init__(self, args):
    method save (line 83) | def save(self, trainer, epoch, is_best=False):
    method add_log (line 95) | def add_log(self, log):
    method write_log (line 98) | def write_log(self, log, refresh=False):
    method done (line 105) | def done(self):
    method plot_psnr (line 108) | def plot_psnr(self, epoch):
    method save_results (line 126) | def save_results(self, filename, save_list, scale):
  function quantize (line 134) | def quantize(img, rgb_range):
  function calc_psnr (line 139) | def calc_psnr(sr, hr, scale, rgb_range, benchmark=False):
  function calc_ssim (line 160) | def calc_ssim(img1, img2, scale=2, benchmark=False):
  function ssim (line 197) | def ssim(img1, img2):
  function make_optimizer (line 220) | def make_optimizer(args, my_model):
  function make_scheduler (line 241) | def make_scheduler(args, my_optimizer):

FILE: utils/util.py
  function cal_sigma (line 8) | def cal_sigma(sig_x, sig_y, radians):
  function anisotropic_gaussian_kernel (line 21) | def anisotropic_gaussian_kernel(batch, kernel_size, covar):
  function isotropic_gaussian_kernel (line 34) | def isotropic_gaussian_kernel(batch, kernel_size, sigma):
  function random_anisotropic_gaussian_kernel (line 43) | def random_anisotropic_gaussian_kernel(batch=1, kernel_size=21, lambda_m...
  function stable_anisotropic_gaussian_kernel (line 53) | def stable_anisotropic_gaussian_kernel(kernel_size=21, theta=0, lambda_1...
  function random_isotropic_gaussian_kernel (line 63) | def random_isotropic_gaussian_kernel(batch=1, kernel_size=21, sig_min=0....
  function stable_isotropic_gaussian_kernel (line 69) | def stable_isotropic_gaussian_kernel(kernel_size=21, sig=4.0):
  function random_gaussian_kernel (line 75) | def random_gaussian_kernel(batch, kernel_size=21, blur_type='iso_gaussia...
  function stable_gaussian_kernel (line 82) | def stable_gaussian_kernel(kernel_size=21, blur_type='iso_gaussian', sig...
  class bicubic (line 90) | class bicubic(nn.Module):
    method __init__ (line 91) | def __init__(self):
    method cubic (line 94) | def cubic(self, x):
    method contribute (line 105) | def contribute(self, in_size, out_size, scale):
    method forward (line 150) | def forward(self, input, scale=1/4):
  class Gaussin_Kernel (line 170) | class Gaussin_Kernel(object):
    method __init__ (line 171) | def __init__(self, kernel_size=21, blur_type='iso_gaussian',
    method __call__ (line 187) | def __call__(self, batch, random):
  class BatchBlur (line 200) | class BatchBlur(nn.Module):
    method __init__ (line 201) | def __init__(self, kernel_size=21):
    method forward (line 209) | def forward(self, input, kernel):
  class SRMDPreprocessing (line 227) | class SRMDPreprocessing(object):
    method __init__ (line 228) | def __init__(self,
    method __call__ (line 271) | def __call__(self, hr_tensor, random=True):