diff --git a/python/paddle/fluid/tests/unittests/mkldnn/test_matmul_v2_mkldnn_op.py b/python/paddle/fluid/tests/unittests/mkldnn/test_matmul_v2_mkldnn_op.py
index fe4044a9bb4dd..3b9d817522561 100644
--- a/python/paddle/fluid/tests/unittests/mkldnn/test_matmul_v2_mkldnn_op.py
+++ b/python/paddle/fluid/tests/unittests/mkldnn/test_matmul_v2_mkldnn_op.py
@@ -253,7 +253,15 @@ def set_dtype_attr(self):
         def test_check_output(self):
             self.check_output_with_place(core.CPUPlace())
 
-        def tmttml(self, x, transpose_x, y, transpose_y):
+        def test_check_grad(self):
+            self.calculate_grads()
+            self.check_grad_with_place(
+                core.CPUPlace(), ["X", "Y"],
+                "Out",
+                user_defined_grads=[self.dx, self.dy],
+                user_defined_grad_outputs=[convert_float_to_uint16(self.dout)])
+
+        def matmul_grad(self, x, transpose_x, y, transpose_y):
             x = np.transpose(
                 x, self.shape_transpose_axes[x.ndim]) if transpose_x else x
             y = np.transpose(
@@ -296,19 +304,19 @@ def calculate_grads(self):
                 is_broadcast = x.shape[0:-2] != y.shape[0:-2]
 
             if self.attrs['trans_x'] is True and self.attrs['trans_y'] is True:
-                self.dx = self.tmttml(self.y_fp32, True, dout, True)
-                self.dy = self.tmttml(dout, True, self.x_fp32, True)
+                self.dx = self.matmul_grad(self.y_fp32, True, dout, True)
+                self.dy = self.matmul_grad(dout, True, self.x_fp32, True)
             elif self.attrs['trans_x'] is True and self.attrs[
                     'trans_y'] is False:
-                self.dx = self.tmttml(self.y_fp32, False, dout, True)
-                self.dy = self.tmttml(self.x_fp32, False, dout, False)
+                self.dx = self.matmul_grad(self.y_fp32, False, dout, True)
+                self.dy = self.matmul_grad(self.x_fp32, False, dout, False)
             elif self.attrs['trans_x'] is False and self.attrs[
                     'trans_y'] is True:
-                self.dx = self.tmttml(dout, False, self.y_fp32, False)
-                self.dy = self.tmttml(dout, True, self.x_fp32, False)
+                self.dx = self.matmul_grad(dout, False, self.y_fp32, False)
+                self.dy = self.matmul_grad(dout, True, self.x_fp32, False)
             else:
-                self.dx = self.tmttml(dout, False, self.y_fp32, True)
-                self.dy = self.tmttml(self.x_fp32, True, dout, False)
+                self.dx = self.matmul_grad(dout, False, self.y_fp32, True)
+                self.dy = self.matmul_grad(self.x_fp32, True, dout, False)
 
             if is_broadcast:
                 x_reduce_axis = []
@@ -340,14 +348,6 @@ def calculate_grads(self):
 
             self.dout = dout
 
-        def test_check_grad(self):
-            self.calculate_grads()
-            self.check_grad_with_place(
-                core.CPUPlace(), ["X", "Y"],
-                "Out",
-                user_defined_grads=[self.dx, self.dy],
-                user_defined_grad_outputs=[convert_float_to_uint16(self.dout)])
-
     cls_name = "{0}_{1}".format(parent.__name__, "BF16")
     TestMatMulV2Bf16OneDNNOp.__name__ = cls_name
     globals()[cls_name] = TestMatMulV2Bf16OneDNNOp