reduce unittest time of test_datasets (#30275)

python/paddle/tests/test_datasets.py

@@ -94,7 +94,7 @@ class TestMNISTTest(unittest.TestCase):
         mnist = MNIST(mode='test', transform=transform)
         self.assertTrue(len(mnist) == 10000)
 
-        for i in range(len(mnist)):
+        i = np.random.randint(0, len(mnist) - 1)
         image, label = mnist[i]
         self.assertTrue(image.shape[0] == 1)
         self.assertTrue(image.shape[1] == 28)
@@ -109,7 +109,7 @@ class TestMNISTTrain(unittest.TestCase):
         mnist = MNIST(mode='train', transform=transform)
         self.assertTrue(len(mnist) == 60000)
 
-        for i in range(len(mnist)):
+        i = np.random.randint(0, len(mnist) - 1)
         image, label = mnist[i]
         self.assertTrue(image.shape[0] == 1)
         self.assertTrue(image.shape[1] == 28)
@@ -140,7 +140,7 @@ class TestFASHIONMNISTTest(unittest.TestCase):
         mnist = FashionMNIST(mode='test', transform=transform)
         self.assertTrue(len(mnist) == 10000)
 
-        for i in range(len(mnist)):
+        i = np.random.randint(0, len(mnist) - 1)
         image, label = mnist[i]
         self.assertTrue(image.shape[0] == 1)
         self.assertTrue(image.shape[1] == 28)
@@ -155,7 +155,7 @@ class TestFASHIONMNISTTrain(unittest.TestCase):
         mnist = FashionMNIST(mode='train', transform=transform)
         self.assertTrue(len(mnist) == 60000)
 
-        for i in range(len(mnist)):
+        i = np.random.randint(0, len(mnist) - 1)
         image, label = mnist[i]
         self.assertTrue(image.shape[0] == 1)
         self.assertTrue(image.shape[1] == 28)