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37 lines
1.2 KiB
37 lines
1.2 KiB
from torchvision.models import resnet18
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from .registry import non_distributed_component_funcs
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from pathlib import Path
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import os
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import torch
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from torchvision.transforms import transforms
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from torchvision.datasets import CIFAR10
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from colossalai.utils import get_dataloader
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def get_cifar10_dataloader(train):
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# build dataloaders
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dataset = CIFAR10(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(),
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transforms.Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))]))
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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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def optim_builder(model):
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return torch.optim.Adam(model.parameters(), lr=0.001)
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criterion = torch.nn.CrossEntropyLoss()
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return model_builder, trainloader, testloader, optim_builder, criterion
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