fix code review alarms

mindspore/ccsrc/backend/kernel_compiler/cpu/minimum_grad_cpu_kernel.cc

@@ -83,10 +83,11 @@ bool MinimumGradCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs,
 }
 
 template <typename T>
-void MinimumGradRecTask(T *x, T *y, T *dout, T *dx, T *dy, size_t dim, size_t x_index, size_t y_index,
-                        size_t dout_index, const std::vector<size_t> &x_cargo, const std::vector<size_t> &y_cargo,
-                        const std::vector<size_t> &dout_cargo, const std::vector<size_t> &x_shape,
-                        const std::vector<size_t> &y_shape, const std::vector<size_t> &dout_shape) {
+void MinimumGradRecTask(const T *x, const T *y, const T *dout, T *dx, T *dy, const size_t dim, const size_t x_index,
+                        const size_t y_index, const size_t dout_index, const std::vector<size_t> &x_cargo,
+                        const std::vector<size_t> &y_cargo, const std::vector<size_t> &dout_cargo,
+                        const std::vector<size_t> &x_shape, const std::vector<size_t> &y_shape,
+                        const std::vector<size_t> &dout_shape) {
   for (size_t i = 0; i < dout_shape[dim]; i++) {
     size_t x_i = x_shape[dim] == dout_shape[dim] ? i * x_cargo[dim] : 0;
     size_t y_i = y_shape[dim] == dout_shape[dim] ? i * y_cargo[dim] : 0;

tests/st/ops/cpu/test_minimum_grad_op.py

@@ -64,7 +64,7 @@ def gen_data(inputA_np, inputB_np, grad_=None):
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_min_tensor_grad_4d():
     inputA_np = np.random.randn(1, 3, 2, 2).astype(np.float32)
@@ -76,7 +76,7 @@ def test_min_tensor_grad_4d():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_min_tensor_grad_result():
     inputA = np.array([[[[0.659578], [0.49113268], [0.75909054], [0.71681815], [0.30421826]]],

tests/st/ops/cpu/test_minimum_op.py

@@ -42,7 +42,7 @@ class TwoTensorsMinimum(Cell):
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_constScalar_tensor_int():
     x = Tensor(np.array([[2, 3, 4], [100, 200, 300]]).astype(np.int32))
@@ -55,7 +55,7 @@ def test_minimum_constScalar_tensor_int():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_Not_Broadcast_int():
     prop = 100 if np.random.random() > 0.5 else -100
@@ -70,7 +70,7 @@ def test_minimum_two_tensors_Not_Broadcast_int():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_Broadcast_int():
     prop = 100 if np.random.random() > 0.5 else -100
@@ -85,7 +85,7 @@ def test_minimum_two_tensors_Broadcast_int():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_Broadcast_oneDimension_int():
     prop = 100 if np.random.random() > 0.5 else -100
@@ -100,7 +100,7 @@ def test_minimum_two_tensors_Broadcast_oneDimension_int():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_notBroadcast_all_oneDimension_int():
     x = Tensor(np.array([[2]]).astype(np.int32))
@@ -114,7 +114,7 @@ def test_minimum_two_tensors_notBroadcast_all_oneDimension_int():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_notBroadcast_float32():
     prop = 100 if np.random.random() > 0.5 else -100
@@ -132,7 +132,7 @@ def test_minimum_two_tensors_notBroadcast_float32():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_notBroadcast_float16():
     prop = 100 if np.random.random() > 0.5 else -100
@@ -150,7 +150,7 @@ def test_minimum_two_tensors_notBroadcast_float16():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_Broadcast_float16():
     prop = 100 if np.random.random() > 0.5 else -100
@@ -168,7 +168,7 @@ def test_minimum_two_tensors_Broadcast_float16():
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_minimum_two_tensors_notBroadcast_float64():
     prop = 100 if np.random.random() > 0.5 else -100