| 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'] |
