| import os | |
| import torch | |
| import torchvision.datasets as datasets | |
| class OxfordIIITPet: | |
| def __init__( | |
| self, | |
| preprocess, | |
| location=os.path.expanduser("~/data"), | |
| batch_size=128, | |
| num_workers=6, | |
| ): | |
| location = os.path.join(location, "OxfordIIITPet") | |
| self.train_dataset = datasets.OxfordIIITPet( | |
| root=location, download=True, split="trainval", 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.OxfordIIITPet( | |
| root=location, download=True, split="test", transform=preprocess | |
| ) | |
| self.test_loader = torch.utils.data.DataLoader( | |
| self.test_dataset, | |
| batch_size=batch_size, | |
| shuffle=False, | |
| num_workers=num_workers, | |
| ) | |
| self.classnames = self.train_dataset.classes | |