20 lines
858 B
Python
20 lines
858 B
Python
from torchvision import datasets, transforms
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from torch import tensor, long
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def SVHN(data_path):
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channel = 3
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im_size = (32, 32)
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num_classes = 10
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mean = [0.4377, 0.4438, 0.4728]
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std = [0.1980, 0.2010, 0.1970]
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transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize(mean=mean, std=std)])
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dst_train = datasets.SVHN(data_path, split='train', download=True, transform=transform)
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dst_test = datasets.SVHN(data_path, split='test', download=True, transform=transform)
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class_names = [str(c) for c in range(num_classes)]
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dst_train.classes = list(class_names)
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dst_test.classes = list(class_names)
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dst_train.targets = tensor(dst_train.labels, dtype=long)
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dst_test.targets = tensor(dst_test.labels, dtype=long)
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return channel, im_size, num_classes, class_names, mean, std, dst_train, dst_test
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