diff --git a/python/paddle/fluid/tests/unittests/npu/test_reshape2_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_reshape2_op_npu.py
new file mode 100644
index 0000000000000..885c990c702bd
--- /dev/null
+++ b/python/paddle/fluid/tests/unittests/npu/test_reshape2_op_npu.py
@@ -0,0 +1,77 @@
+#  Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import numpy as np
+import unittest
+import sys
+sys.path.append("..")
+from op_test import OpTest
+import paddle
+import paddle.fluid as fluid
+
+paddle.enable_static()
+SEED = 2021
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestReshape2(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "reshape2"
+        self.place = paddle.NPUPlace(0)
+
+        self.init_data()
+        self.inputs = {"X": np.random.random(self.ori_shape).astype("float32")}
+        self.attrs = {"shape": self.new_shape}
+        self.outputs = {
+            "Out": self.inputs["X"].reshape(self.infered_shape),
+            'XShape': np.random.random(self.ori_shape).astype("float32")
+        }
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def init_data(self):
+        self.ori_shape = (2, 100)
+        self.new_shape = (20, 10)
+        self.infered_shape = (20, 10)
+
+    def test_check_output(self):
+        self.check_output_with_place(
+            self.place, check_dygraph=False, no_check_set=['XShape'])
+
+    def test_check_grad_normal(self):
+        self.check_grad_with_place(
+            self.place, ['X'], 'Out', check_dygraph=False)
+
+
+class TestReshape2_case2(TestReshape2):
+    def init_data(self):
+        self.ori_shape = (2, 100)
+        self.new_shape = (-1, 10)
+        self.infered_shape = (20, 10)
+
+
+class TestReshape2_case3(TestReshape2):
+    def init_data(self):
+        self.ori_shape = (100, 5, 6)
+        self.new_shape = (-1, 0, 3)
+        self.infered_shape = (200, 5, 3)
+
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/python/paddle/fluid/tests/unittests/npu/test_reshape_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_reshape_op_npu.py
deleted file mode 100644
index fe6eb6b5189cd..0000000000000
--- a/python/paddle/fluid/tests/unittests/npu/test_reshape_op_npu.py
+++ /dev/null
@@ -1,141 +0,0 @@
-#  Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#    http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from __future__ import print_function
-
-import numpy as np
-import unittest
-import sys
-sys.path.append("..")
-from op_test import OpTest
-import paddle
-import paddle.fluid as fluid
-
-paddle.enable_static()
-SEED = 2021
-
-
-@unittest.skipIf(not paddle.is_compiled_with_npu(),
-                 "core is not compiled with NPU")
-class TestReshape2(OpTest):
-    def setUp(self):
-        self.set_npu()
-        self.op_type = "reshape2"
-        self.place = paddle.NPUPlace(0)
-
-        self.init_data()
-        self.inputs = {"X": np.random.random(self.ori_shape).astype("float32")}
-        self.attrs = {"shape": self.new_shape}
-        self.outputs = {
-            "Out": self.inputs["X"].reshape(self.infered_shape),
-            'XShape': np.random.random(self.ori_shape).astype("float32")
-        }
-
-    def set_npu(self):
-        self.__class__.use_npu = True
-
-    def init_data(self):
-        self.ori_shape = (2, 60)
-        self.new_shape = (12, 10)
-        self.infered_shape = (12, 10)
-
-    def test_check_output(self):
-        self.check_output(
-            self.place, check_dygraph=False, no_check_set=['XShape'])
-
-
-class TestReshape2_case2(TestReshape2):
-    def init_data(self):
-        self.ori_shape = (2, 60)
-        self.new_shape = (-1, 10)
-        self.infered_shape = (12, 10)
-
-
-class TestReshape2_case3(TestReshape2):
-    def init_data(self):
-        self.ori_shape = (2, 5, 6)
-        self.new_shape = (-1, 0, 3)
-        self.infered_shape = (4, 5, 3)
-
-
-    # TODO(ascendrc): Add grad test
-    # def test_check_grad(self):
-    #     if self.dtype == np.float16:
-    #         return
-    #     self.check_grad(['X'], 'Out')
-    #
-@unittest.skipIf(not paddle.is_compiled_with_npu(),
-                 "core is not compiled with NPU")
-class TestReshapeNet(unittest.TestCase):
-    def _test(self, run_npu=True):
-        main_prog = paddle.static.Program()
-        startup_prog = paddle.static.Program()
-        main_prog.random_seed = SEED
-        startup_prog.random_seed = SEED
-        np.random.seed(SEED)
-
-        a_np = np.random.random(size=(32, 32)).astype('float32')
-        b_np = np.random.random(size=(32, 32)).astype('float32')
-        label_np = np.random.randint(2, size=(32, 1)).astype('int64')
-
-        with paddle.static.program_guard(main_prog, startup_prog):
-            a = paddle.static.data(name="a", shape=[32, 32], dtype='float32')
-            b = paddle.static.data(name="b", shape=[32, 32], dtype='float32')
-            label = paddle.static.data(
-                name="label", shape=[32, 1], dtype='int64')
-
-            sum = paddle.add(a, b)
-            z = paddle.reshape(sum, shape=[32, 32])
-
-            fc_1 = fluid.layers.fc(input=z, size=128)
-            prediction = fluid.layers.fc(input=fc_1, size=2, act='softmax')
-
-            cost = fluid.layers.cross_entropy(input=prediction, label=label)
-            loss = fluid.layers.reduce_mean(cost)
-            sgd = fluid.optimizer.SGD(learning_rate=0.01)
-            sgd.minimize(loss)
-
-        if run_npu:
-            place = paddle.NPUPlace(0)
-        else:
-            place = paddle.CPUPlace()
-
-        exe = paddle.static.Executor(place)
-        exe.run(startup_prog)
-
-        print("Start run on {}".format(place))
-        for epoch in range(100):
-
-            pred_res, loss_res = exe.run(
-                main_prog,
-                feed={"a": a_np,
-                      "b": b_np,
-                      "label": label_np},
-                fetch_list=[prediction, loss])
-            if epoch % 10 == 0:
-                print("Epoch {} | Prediction[0]: {}, Loss: {}".format(
-                    epoch, pred_res[0], loss_res))
-
-        return pred_res, loss_res
-
-    def test_npu(self):
-        cpu_pred, cpu_loss = self._test(False)
-        npu_pred, npu_loss = self._test(True)
-
-        self.assertTrue(np.allclose(npu_pred, cpu_pred))
-        self.assertTrue(np.allclose(npu_loss, cpu_loss))
-
-
-if __name__ == '__main__':
-    unittest.main()