SYMBOL INDEX (111 symbols across 18 files)

FILE: models/__init__.py
  function get_net (line 8) | def get_net(input_depth, NET_TYPE, pad, upsample_mode, n_channels=3, act...

FILE: models/common.py
  function add_module (line 6) | def add_module(self, module):
  class Concat (line 11) | class Concat(nn.Module):
    method __init__ (line 12) | def __init__(self, dim, *args):
    method forward (line 19) | def forward(self, input):
    method __len__ (line 41) | def __len__(self):
  class GenNoise (line 45) | class GenNoise(nn.Module):
    method __init__ (line 46) | def __init__(self, dim2):
    method forward (line 50) | def forward(self, input):
  class Swish (line 63) | class Swish(nn.Module):
    method __init__ (line 68) | def __init__(self):
    method forward (line 72) | def forward(self, x):
  function act (line 76) | def act(act_fun = 'LeakyReLU'):
  function bn (line 95) | def bn(num_features):
  function conv (line 99) | def conv(in_f, out_f, kernel_size, stride=1, bias=True, pad='zero', down...

FILE: models/dcgan.py
  function dcgan (line 4) | def dcgan(inp=2,

FILE: models/downsampler.py
  class Downsampler (line 5) | class Downsampler(nn.Module):
    method __init__ (line 9) | def __init__(self, n_planes, factor, kernel_type, phase=0, kernel_widt...
    method forward (line 65) | def forward(self, input):
  function get_kernel (line 73) | def get_kernel(factor, kernel_type, phase, kernel_width, support=None, s...

FILE: models/resnet.py
  class ResidualSequential (line 9) | class ResidualSequential(nn.Sequential):
    method __init__ (line 10) | def __init__(self, *args):
    method forward (line 13) | def forward(self, x):
    method eval (line 26) | def eval(self):
  function get_block (line 33) | def get_block(num_channels, norm_layer, act_fun):
  class ResNet (line 44) | class ResNet(nn.Module):
    method __init__ (line 45) | def __init__(self, num_input_channels, num_output_channels, num_blocks...
    method forward (line 92) | def forward(self, input):
    method eval (line 95) | def eval(self):

FILE: models/skip.py
  function skip (line 5) | def skip(

FILE: models/texture_nets.py
  function conv (line 9) | def conv(in_f, out_f, kernel_size, stride=1, bias=True, pad='zero'):
  function get_texture_nets (line 17) | def get_texture_nets(inp=3, ratios = [32, 16, 8, 4, 2, 1], fill_noise=Fa...

FILE: models/unet.py
  class ListModule (line 7) | class ListModule(nn.Module):
    method __init__ (line 8) | def __init__(self, *args):
    method __getitem__ (line 15) | def __getitem__(self, idx):
    method __iter__ (line 26) | def __iter__(self):
    method __len__ (line 29) | def __len__(self):
  class UNet (line 32) | class UNet(nn.Module):
    method __init__ (line 37) | def __init__(self, num_input_channels=3, num_output_channels=3,
    method forward (line 76) | def forward(self, inputs):
  class unetConv2 (line 130) | class unetConv2(nn.Module):
    method __init__ (line 131) | def __init__(self, in_size, out_size, norm_layer, need_bias, pad):
    method forward (line 147) | def forward(self, inputs):
  class unetDown (line 153) | class unetDown(nn.Module):
    method __init__ (line 154) | def __init__(self, in_size, out_size, norm_layer, need_bias, pad):
    method forward (line 159) | def forward(self, inputs):
  class unetUp (line 165) | class unetUp(nn.Module):
    method __init__ (line 166) | def __init__(self, out_size, upsample_mode, need_bias, pad, same_num_f...
    method forward (line 180) | def forward(self, inputs1, inputs2):

FILE: super-resolution_eval_script.py
  function rgb2ycbcr (line 4) | def rgb2ycbcr(im_rgb):
  function compare_psnr_y (line 12) | def compare_psnr_y(x, y):

FILE: utils/common_utils.py
  function crop_image (line 13) | def crop_image(img, d=32):
  function get_params (line 29) | def get_params(opt_over, net, net_input, downsampler=None):
  function get_image_grid (line 55) | def get_image_grid(images_np, nrow=8):
  function plot_image_grid (line 62) | def plot_image_grid(images_np, nrow =8, factor=1, interpolation='lanczos'):
  function load (line 89) | def load(path):
  function get_image (line 94) | def get_image(path, imsize=-1):
  function fill_noise (line 118) | def fill_noise(x, noise_type):
  function get_noise (line 127) | def get_noise(input_depth, method, spatial_size, noise_type='u', var=1./...
  function pil_to_np (line 155) | def pil_to_np(img_PIL):
  function np_to_pil (line 169) | def np_to_pil(img_np):
  function np_to_torch (line 183) | def np_to_torch(img_np):
  function torch_to_np (line 190) | def torch_to_np(img_var):
  function optimize (line 198) | def optimize(optimizer_type, parameters, closure, LR, num_iter):

FILE: utils/denoising_utils.py
  function get_noisy_image (line 6) | def get_noisy_image(img_np, sigma):

FILE: utils/feature_inversion_utils.py
  class View (line 9) | class View(nn.Module):
    method __init__ (line 10) | def __init__(self):
    method forward (line 13) | def forward(self, x):
  function get_vanilla_vgg_features (line 16) | def get_vanilla_vgg_features(cut_idx=-1):
  function get_matcher (line 46) | def get_matcher(net, opt):
  function get_vgg (line 60) | def get_vgg(cut_idx=-1):
  function vgg_preprocess_var (line 71) | def vgg_preprocess_var(var):
  function get_preprocessor (line 81) | def get_preprocessor(imsize):
  function get_deprocessor (line 96) | def get_deprocessor():

FILE: utils/inpainting_utils.py
  function get_text_mask (line 7) | def get_text_mask(for_image, sz=20):
  function get_bernoulli_mask (line 18) | def get_bernoulli_mask(for_image, zero_fraction=0.95):

FILE: utils/matcher.py
  class Matcher (line 4) | class Matcher:
    method __init__ (line 5) | def __init__(self, how='gram_matrix', loss='mse'):
    method __call__ (line 21) | def __call__(self, module, features):
    method clean (line 30) | def clean(self):
  function gram_matrix (line 33) | def gram_matrix(x):
  function features (line 41) | def features(x):

FILE: utils/perceptual_loss/matcher.py
  class Matcher (line 5) | class Matcher:
    method __init__ (line 6) | def __init__(self, how='gram_matrix', loss='mse', map_index=933):
    method __call__ (line 26) | def __call__(self, module, features):
    method clean (line 57) | def clean(self):
  function gram_matrix (line 60) | def gram_matrix(x):
  function features (line 68) | def features(x):

FILE: utils/perceptual_loss/perceptual_loss.py
  function get_pretrained_net (line 15) | def get_pretrained_net(name):
  class PerceputalLoss (line 49) | class PerceputalLoss(nn.modules.loss._Loss):
    method __init__ (line 53) | def __init__(self, input_range='sigmoid',
    method preprocess_input (line 77) | def preprocess_input(self, x):
    method __call__ (line 83) | def __call__(self, x, y):
  function get_vgg19_caffe (line 95) | def get_vgg19_caffe():
  function get_vgg16_caffe (line 116) | def get_vgg16_caffe():
  class View (line 135) | class View(nn.Module):
    method __init__ (line 136) | def __init__(self):
    method forward (line 139) | def forward(self, x):
  function get_matcher (line 143) | def get_matcher(vgg, opt):
  function get_vgg (line 156) | def get_vgg(cut_idx=-1, vgg_type='pytorch'):
  function vgg_preprocess_caffe (line 167) | def vgg_preprocess_caffe(var):
  function vgg_preprocess_pytorch (line 178) | def vgg_preprocess_pytorch(var):
  function get_preprocessor (line 183) | def get_preprocessor(imsize):
  function get_deprocessor (line 198) | def get_deprocessor():

FILE: utils/perceptual_loss/vgg_modified.py
  class VGGModified (line 3) | class VGGModified(nn.Module):
    method __init__ (line 4) | def __init__(self, vgg19_orig, slope=0.01):
    method forward (line 60) | def forward(self, x):

FILE: utils/sr_utils.py
  function put_in_center (line 3) | def put_in_center(img_np, target_size):
  function load_LR_HR_imgs_sr (line 18) | def load_LR_HR_imgs_sr(fname, imsize, factor, enforse_div32=None):
  function get_baselines (line 69) | def get_baselines(img_LR_pil, img_HR_pil):
  function tv_loss (line 84) | def tv_loss(x, beta = 0.5):