| import os | |
| import torch | |
| import torchvision.datasets as datasets | |
| class MNIST: | |
| def __init__(self, | |
| preprocess, | |
| location=os.path.expanduser('~/data'), | |
| batch_size=128, | |
| num_workers=16): | |
| self.train_dataset = datasets.MNIST( | |
| root=location, | |
| download=True, | |
| train=True, | |
| transform=preprocess | |
| ) | |
| self.train_loader = torch.utils.data.DataLoader( | |
| self.train_dataset, | |
| batch_size=batch_size, | |
| shuffle=True, | |
| num_workers=num_workers | |
| ) | |
| self.test_dataset = datasets.MNIST( | |
| root=location, | |
| download=True, | |
| train=False, | |
| transform=preprocess | |
| ) | |
| self.test_loader = torch.utils.data.DataLoader( | |
| self.test_dataset, | |
| batch_size=batch_size, | |
| shuffle=False, | |
| num_workers=num_workers | |
| ) | |
| self.classnames = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] |