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deepcore/datasets/qmnist.py

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+from torchvision import datasets, transforms
+
+
+def QMNIST(data_path):
+    channel = 1
+    im_size = (28, 28)
+    num_classes = 10
+    mean = [0.1308]
+    std = [0.3088]
+    transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize(mean=mean, std=std)])
+    dst_train = datasets.QMNIST(data_path, train=True, download=True, transform=transform)
+    dst_test = datasets.QMNIST(data_path, train=False, download=True, transform=transform)
+    class_names = [str(c) for c in range(num_classes)]
+    dst_train.targets = dst_train.targets[:, 0]
+    dst_test.targets = dst_test.targets[:, 0]
+    dst_train.compat = False
+    dst_test.compat = False
+    return channel, im_size, num_classes, class_names, mean, std, dst_train, dst_test