✅Test: [Lab-2] 测试集下载测试

.gitignore

@@ -1,2 +1,3 @@
 .idea
-*/img
+*/img
+*/data

Lab-2/test/verify_env.py

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+import unittest
+
+import torch
+import torchvision
+from torchvision import transforms
+import matplotlib.pyplot as plt
+
+
+class MyTestCase(unittest.TestCase):
+    def test_verify_env(self):
+        self.assertIsNotNone(torch.__version__)
+        print("== Env test pass ==\n"
+              f"[torch] {torch.__version__}\n")
+    def test_using_dataset(selfs):
+        transform = transforms.Compose([
+            transforms.ToTensor(),
+            transforms.Normalize((0.5,), (0.5,))
+        ])
+        test_dataset = torchvision.datasets.MNIST(
+            root='../data',
+            train=False,
+            download=True,
+            transform=transform
+        )
+        test_loader = torch.utils.data.DataLoader(
+            test_dataset,
+            batch_size=64,
+            shuffle=False
+        )
+        images, labels = next(iter(test_loader))
+        fig, axes = plt.subplots(2, 5, figsize=(10, 4))
+        for i, ax in enumerate(axes.flat):
+            ax.imshow(images[i][0], cmap='gray')
+            ax.set_title(f'Label: {labels[i]}')
+            ax.axis('off')
+
+        plt.tight_layout
+        plt.show()
+
+        print(f"Successfully load MNIST dataset and show 10 images")
+        return images, labels
+
+if __name__ == '__main__':
+    unittest.main()