(data_set, batch_size, shuffle=True, n_worker=0, train = True, add_noise=0)

(s=128, resize= None)

(s)

(self, in_channels)

(dist)

(self, ele)

(self,mod, x)

(L1, L2)

(A)

(self, latent_channels, out_classes, num_latent=4, num_embeddings=4)

(self, lam)

(self, X)

(self)

(self)

(self, PSNR)

(self, PSNR)

(self, X)

(self, mod, samples)

(self, features, former_shape)

(self, X)

(self, X)

(datal, model, mod, args)

(l, tar_str)

(path_to_image)

(s)

(imgs, n)

(args)

(self, z:torch.Tensor)

(X_imgs,device, N=1, t=None)

(self, samples)

(self, score, mod=None)

()

(s)

(dataloader, model, criterion, writer, epoch, mod, args)

(dataloader:Iterable, model:torch.nn.Module, optimizer:torch.optim.Optimizer, criterion:t

(self, idx)

(self, M, PSNR)

(self, M, PSNR)

(self, in_channels, latent_channels, out_classes, num_embeddings=400)

(self, lam)

(self, in_channels, out_channels)

(self, dim_dic, num_embeddings = 50)

(self, path:str, split:str, transforms: torchvision.transforms=None, targe

(self)

(s=148, p=0.8)

(self, X)

(L1,L2)

(self,X)

(self, X)

(gt_s, s)

(self, X, mod=None)

(self, X, mod=None)

(self, dist, outputs, targets)

(self, dist, outputs, targets)

(self, x)

(self, x)

(self, X, mod= None)

(s)

(self, z:torch.Tensor)

(p, d)