diff --git a/python/paddle/tests/test_datasets.py b/python/paddle/tests/test_datasets.py
index 3aa21ae2db267d40d4483b27ed89b0da349ce0db..89fa01cbceb45c4812cbe6363c9ae0af9ed6ae7d 100644
--- a/python/paddle/tests/test_datasets.py
+++ b/python/paddle/tests/test_datasets.py
@@ -94,13 +94,13 @@ class TestMNISTTest(unittest.TestCase):
         mnist = MNIST(mode='test', transform=transform)
         self.assertTrue(len(mnist) == 10000)
 
-        for i in range(len(mnist)):
-            image, label = mnist[i]
-            self.assertTrue(image.shape[0] == 1)
-            self.assertTrue(image.shape[1] == 28)
-            self.assertTrue(image.shape[2] == 28)
-            self.assertTrue(label.shape[0] == 1)
-            self.assertTrue(0 <= int(label) <= 9)
+        i = np.random.randint(0, len(mnist) - 1)
+        image, label = mnist[i]
+        self.assertTrue(image.shape[0] == 1)
+        self.assertTrue(image.shape[1] == 28)
+        self.assertTrue(image.shape[2] == 28)
+        self.assertTrue(label.shape[0] == 1)
+        self.assertTrue(0 <= int(label) <= 9)
 
 
 class TestMNISTTrain(unittest.TestCase):
@@ -109,13 +109,13 @@ class TestMNISTTrain(unittest.TestCase):
         mnist = MNIST(mode='train', transform=transform)
         self.assertTrue(len(mnist) == 60000)
 
-        for i in range(len(mnist)):
-            image, label = mnist[i]
-            self.assertTrue(image.shape[0] == 1)
-            self.assertTrue(image.shape[1] == 28)
-            self.assertTrue(image.shape[2] == 28)
-            self.assertTrue(label.shape[0] == 1)
-            self.assertTrue(0 <= int(label) <= 9)
+        i = np.random.randint(0, len(mnist) - 1)
+        image, label = mnist[i]
+        self.assertTrue(image.shape[0] == 1)
+        self.assertTrue(image.shape[1] == 28)
+        self.assertTrue(image.shape[2] == 28)
+        self.assertTrue(label.shape[0] == 1)
+        self.assertTrue(0 <= int(label) <= 9)
 
         # test cv2 backend
         mnist = MNIST(mode='train', transform=transform, backend='cv2')
@@ -140,13 +140,13 @@ class TestFASHIONMNISTTest(unittest.TestCase):
         mnist = FashionMNIST(mode='test', transform=transform)
         self.assertTrue(len(mnist) == 10000)
 
-        for i in range(len(mnist)):
-            image, label = mnist[i]
-            self.assertTrue(image.shape[0] == 1)
-            self.assertTrue(image.shape[1] == 28)
-            self.assertTrue(image.shape[2] == 28)
-            self.assertTrue(label.shape[0] == 1)
-            self.assertTrue(0 <= int(label) <= 9)
+        i = np.random.randint(0, len(mnist) - 1)
+        image, label = mnist[i]
+        self.assertTrue(image.shape[0] == 1)
+        self.assertTrue(image.shape[1] == 28)
+        self.assertTrue(image.shape[2] == 28)
+        self.assertTrue(label.shape[0] == 1)
+        self.assertTrue(0 <= int(label) <= 9)
 
 
 class TestFASHIONMNISTTrain(unittest.TestCase):
@@ -155,13 +155,13 @@ class TestFASHIONMNISTTrain(unittest.TestCase):
         mnist = FashionMNIST(mode='train', transform=transform)
         self.assertTrue(len(mnist) == 60000)
 
-        for i in range(len(mnist)):
-            image, label = mnist[i]
-            self.assertTrue(image.shape[0] == 1)
-            self.assertTrue(image.shape[1] == 28)
-            self.assertTrue(image.shape[2] == 28)
-            self.assertTrue(label.shape[0] == 1)
-            self.assertTrue(0 <= int(label) <= 9)
+        i = np.random.randint(0, len(mnist) - 1)
+        image, label = mnist[i]
+        self.assertTrue(image.shape[0] == 1)
+        self.assertTrue(image.shape[1] == 28)
+        self.assertTrue(image.shape[2] == 28)
+        self.assertTrue(label.shape[0] == 1)
+        self.assertTrue(0 <= int(label) <= 9)
 
         # test cv2 backend
         mnist = FashionMNIST(mode='train', transform=transform, backend='cv2')