PyTorch : Custom_DataLoader

import libraries import torch import torch.utils.data as data import torchvision.datasets as dset import torchvision.transforms as transforms set hyperparameters batch_size = 2 ImageFolder & dataloader img_dir = "./images" img_data = dset.ImageFolder(img_dir, transforms.Compose([ transforms.Resize(256), transforms.RandomResizedCrop(224), transforms.RandomHorizontalFlip(), transforms.ToTensor(), ])) img_batch = data.DataLoader(img_data, batch_size=batch_size, shuffle=True,drop_last=True) Test for...