diff --git a/oneflow/python/test/modules/test_maxpool.py b/oneflow/python/test/modules/test_maxpool.py
index 8bb3d5da0cf1356aafb16de2d54a01813c01f576..08f23c6a7ae2c69adaf2c91098f60cf6f66f1228 100644
--- a/oneflow/python/test/modules/test_maxpool.py
+++ b/oneflow/python/test/modules/test_maxpool.py
@@ -340,27 +340,6 @@ def _test_maxpool3d_special_kernel_size_backward(test_case, device):
     test_case.assertTrue(np.allclose(x.grad.numpy(), numpy_grad, 1e-5, 1e-5))
 
 
-def _test_maxpool3d_diff_kernel_stride_backward(test_case, device):
-    dim = 3
-    input_arr = np.random.randn(9, 7, 48, 32, 20)
-    kernel_size, stride, padding = (6, 2, 3), (5, 4, 5), (4, 1, 2)
-
-    m_numpy = MaxPoolNumpy(dim, kernel_size, stride, padding)
-    numpy_output = m_numpy(input_arr)
-
-    m = flow.nn.MaxPool3d(kernel_size=kernel_size, stride=stride, padding=padding)
-    m.to(flow.device(device))
-    x = flow.Tensor(input_arr, requires_grad=True, device=flow.device(device))
-    output = m(x)
-    test_case.assertTrue(np.allclose(numpy_output, output.numpy(), 1e-4, 1e-4))
-
-    output = output.sum()
-    output.backward()
-    doutput = np.ones_like(numpy_output, dtype=np.float64)
-    numpy_grad = m_numpy.backward(doutput)
-    test_case.assertTrue(np.allclose(x.grad.numpy(), numpy_grad, 1e-5, 1e-5))
-
-
 def _test_maxpool3d_negative_input_backward(test_case, device):
     dim = 3
     input_arr = -1.23456 * np.ones((1, 1, 1, 1, 1), dtype=np.float)
@@ -408,7 +387,6 @@ class TestPoolingModule(flow.unittest.TestCase):
         arg_dict["test_fun"] = [
             _test_maxpool3d_backward,
             _test_maxpool3d_special_kernel_size_backward,
-            _test_maxpool3d_diff_kernel_stride_backward,
             _test_maxpool3d_negative_input_backward,
         ]
         arg_dict["device"] = ["cpu", "cuda"]