mirror of https://github.com/hpcaitech/ColossalAI
38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
import os
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from pathlib import Path
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import torch
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from torchvision.datasets import CIFAR10
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from torchvision.models import resnet18
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from torchvision.transforms import transforms
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from colossalai.legacy.utils import get_dataloader
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from .registry import non_distributed_component_funcs
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def get_cifar10_dataloader(train):
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# build dataloaders
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dataset = CIFAR10(
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root=Path(os.environ["DATA"]),
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download=True,
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train=train,
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transform=transforms.Compose(
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[transforms.ToTensor(), transforms.Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))]
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),
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)
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dataloader = get_dataloader(dataset=dataset, shuffle=True, batch_size=16, drop_last=True)
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return dataloader
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@non_distributed_component_funcs.register(name="resnet18")
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def get_resnet_training_components():
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def model_builder(checkpoint=False):
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return resnet18(num_classes=10)
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trainloader = get_cifar10_dataloader(train=True)
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testloader = get_cifar10_dataloader(train=False)
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criterion = torch.nn.CrossEntropyLoss()
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return model_builder, trainloader, testloader, torch.optim.Adam, criterion
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