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deepcore/datasets/svhn.py

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