【NPU】Fix reshape test & add grad test (#31776)

* fix

* fix

python/paddle/fluid/tests/unittests/npu/test_reshape_op_npu.py → python/paddle/fluid/tests/unittests/npu/test_reshape2_op_npu.py

@@ -46,95 +46,31 @@ class TestReshape2(OpTest):
         self.__class__.use_npu = True
 
     def init_data(self):
-        self.ori_shape = (2, 60)
-        self.new_shape = (12, 10)
-        self.infered_shape = (12, 10)
+        self.ori_shape = (2, 100)
+        self.new_shape = (20, 10)
+        self.infered_shape = (20, 10)
 
     def test_check_output(self):
-        self.check_output(
+        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, 60)
+        self.ori_shape = (2, 100)
         self.new_shape = (-1, 10)
-        self.infered_shape = (12, 10)
+        self.infered_shape = (20, 10)
 
 
 class TestReshape2_case3(TestReshape2):
     def init_data(self):
-        self.ori_shape = (2, 5, 6)
+        self.ori_shape = (100, 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))
+        self.infered_shape = (200, 5, 3)
 
 
 if __name__ == '__main__':