diff --git a/oneflow/user/kernels/cum_backward_kernel.cpp b/oneflow/user/kernels/cum_backward_kernel.cpp
index 6440c8f9e91..6e6967d1daa 100644
--- a/oneflow/user/kernels/cum_backward_kernel.cpp
+++ b/oneflow/user/kernels/cum_backward_kernel.cpp
@@ -45,11 +45,16 @@ void CumProdBackward(const T* dy_ptr, T* dx_ptr, const T* output_ptr, const T* i
     }
 
     for (size_t j = 0; j < down_space; j++) {
-      auto* cumsum_zeros_number_ptr = j + dx_ptr_base;
+      const auto* cur_output_ptr = output_ptr_base + j;
+      const auto* cur_input_ptr = input_ptr_base + j;
+      const auto* cur_dy_ptr = dy_ptr_base + j;
+      auto* cur_dx_ptr = dx_ptr_base + j;
+      const auto* cumsum_zeros_number_ptr = dx_ptr_base + j;
+
       size_t first_zero_index = space;
       // Find index of first zero in input.
       for (size_t k = 0; k < space; k++) {
-        if (cumsum_zeros_number_ptr[j + k * down_space] == 1) {
+        if (cumsum_zeros_number_ptr[k * down_space] == 1) {
           first_zero_index = k;
           break;
         }
@@ -58,24 +63,24 @@ void CumProdBackward(const T* dy_ptr, T* dx_ptr, const T* output_ptr, const T* i
       // for element which index is less than z grad is computed as below:
       T reverse_cumsum = 0;
       for (size_t k = 0; k < first_zero_index; k++) {
-        const size_t data_offset = j + (first_zero_index - k - 1) * down_space;
-        reverse_cumsum += output_ptr_base[data_offset] * dy_ptr_base[data_offset];
-        dx_ptr_base[data_offset] = reverse_cumsum / input_ptr_base[data_offset];
+        const size_t data_offset = (first_zero_index - k - 1) * down_space;
+        reverse_cumsum += cur_output_ptr[data_offset] * cur_dy_ptr[data_offset];
+        cur_dx_ptr[data_offset] = reverse_cumsum / cur_input_ptr[data_offset];
       }
       // For where index is z, its grad is computed as below:
       if (first_zero_index == space) { continue; }
       T cumprod = 1;
       T cumsum = 0;
       T cumprod_before_first_zero =
-          first_zero_index == 0 ? 1 : output_ptr_base[(first_zero_index - 1) * down_space];
+          first_zero_index == 0 ? 1 : cur_output_ptr[(first_zero_index - 1) * down_space];
       for (size_t k = first_zero_index; k < space; k++) {
-        const size_t data_offset = j + k * down_space;
+        const size_t data_offset = k * down_space;
         // Recover dx_ptr default value
-        if (dx_ptr_base[data_offset] >= 1) { dx_ptr_base[data_offset] = 0; }
-        if (k != first_zero_index) { cumprod *= input_ptr_base[data_offset]; }
-        cumsum += cumprod_before_first_zero * dy_ptr_base[data_offset] * cumprod;
+        if (cur_dx_ptr[data_offset] >= 1) { cur_dx_ptr[data_offset] = 0; }
+        if (k != first_zero_index) { cumprod *= cur_input_ptr[data_offset]; }
+        cumsum += cumprod_before_first_zero * cumprod * cur_dy_ptr[data_offset];
       }
-      dx_ptr_base[j + first_zero_index * down_space] = cumsum;
+      cur_dx_ptr[first_zero_index * down_space] = cumsum;
     }
   }
 }
diff --git a/python/oneflow/test/modules/test_cum_ops.py b/python/oneflow/test/modules/test_cum_ops.py
index 6f366e37259..2088440a292 100644
--- a/python/oneflow/test/modules/test_cum_ops.py
+++ b/python/oneflow/test/modules/test_cum_ops.py
@@ -15,9 +15,11 @@
 """
 import unittest
 from collections import OrderedDict
+import numpy as np
 
 import oneflow as flow
 import oneflow.unittest
+import torch as ori_torch
 
 from oneflow.test_utils.automated_test_util import *
 
@@ -64,6 +66,29 @@ def test_cumprod_with_user_dy(test_case):
         z = y * 2
         return z
 
+    def test_cumprod_with_zero(test_case):
+        np_arr = np.ones((5, 5))
+        np_arr_grad = np_arr
+        np_arr[2][3] = 0
+        np_arr[4][3] = 0
+        of_tensor = flow.tensor(np_arr, dtype=flow.float, requires_grad=True)
+        of_res = of_tensor.cumprod(dim=0)
+        of_res.backward(flow.tensor(np_arr_grad, dtype=flow.float))
+
+        torch_tensor = ori_torch.tensor(
+            np_arr, dtype=ori_torch.float, requires_grad=True
+        )
+        torch_res = torch_tensor.cumprod(dim=0)
+        torch_res.backward(ori_torch.tensor(np_arr_grad, dtype=ori_torch.float))
+        test_case.assertTrue(
+            np.allclose(
+                of_tensor.grad.numpy(),
+                torch_tensor.grad.numpy(),
+                rtol=0.0001,
+                atol=1e-05,
+            )
+        )
+
 
 if __name__ == "__main__":
     unittest.main()