mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
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28 lines
741 B
28 lines
741 B
#!/usr/bin/env python |
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# -*- encoding: utf-8 -*- |
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import os |
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from pathlib import Path |
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import pytest |
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from torchvision import transforms, datasets |
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from torch.utils.data import DataLoader |
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@pytest.mark.cpu |
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def test_cifar10_dataset(): |
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# build transform |
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transform_pipeline = [transforms.ToTensor()] |
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transform_pipeline = transforms.Compose(transform_pipeline) |
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# build dataset |
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dataset = datasets.CIFAR10(root=Path(os.environ['DATA']), train=True, download=True, transform=transform_pipeline) |
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# build dataloader |
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dataloader = DataLoader(dataset=dataset, batch_size=4, shuffle=True, num_workers=2) |
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data_iter = iter(dataloader) |
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img, label = data_iter.next() |
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if __name__ == '__main__': |
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test_cifar10_dataset()
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