takedown testcases that are almost never failing as to save time on gate

tests/st/control/inner/test_011_if_in_while.py

@@ -57,7 +57,7 @@ class BackwardNet(nn.Cell):
         return grads
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -73,7 +73,7 @@ def test_forward():
     assert graph_mode_out == Tensor(21, mstype.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/control/inner/test_011_if_in_while_break.py

@@ -79,7 +79,7 @@ class BackwardNetReplaceBreak(nn.Cell):
         return grads
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -95,7 +95,7 @@ def test_forward():
 
 
 # Problem: Exceed function call depth limit 1000.
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/control/inner/test_110_if_after_if_in_if.py

@@ -156,7 +156,7 @@ def test_if_after_if_in_if():
     control_flow_if_after_if_in_if(IfAfterIfInIfNet, x, expect1, expect2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/control/inner/test_202_while_n_while.py

@@ -70,7 +70,7 @@ def test_forward():
     assert graph_out == Tensor(np.array(18), mstype.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/control/inner/test_220_while_after_while_in_if.py

@@ -75,7 +75,7 @@ def test_forward():
     assert graph_mode_out == (Tensor(np.array(9), mstype.int32), Tensor(np.array(4), mstype.int32))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/control/inner/test_222_for_while_while.py

@@ -71,7 +71,7 @@ def test_forward():
     assert graph_out == Tensor(np.array(36), mstype.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/control/inner/test_322_for_after_while_in_for.py

@@ -24,7 +24,7 @@ from mindspore.common import dtype as mstype
 grad_all = C.GradOperation(get_all=True)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/control/test_cont_grad.py

@@ -29,7 +29,7 @@ grad_by_list = C.GradOperation(get_by_list=True)
 grad_all = C.GradOperation(get_all=True)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard

tests/st/dump/test_data_dump.py

@@ -156,7 +156,7 @@ def test_cpu_e2e_dump():
     run_e2e_dump()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 @security_off_wrap
@@ -178,7 +178,7 @@ def test_gpu_e2e_dump():
     run_e2e_dump()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @security_off_wrap

tests/st/dynamic_shape/test_dynamic_shape_embedding.py

@@ -35,7 +35,7 @@ class NetWithEmbeddingLookUp(nn.Cell):
         return out
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training

tests/st/dynamic_shape/test_dynamic_shape_with_heterogeneity.py

@@ -74,7 +74,7 @@ class UniqueReshapeAdd(nn.Cell):
         return self.add(x, y)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -94,7 +94,7 @@ def test_unique():
     assert (output[1].asnumpy() == expect2).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -130,7 +130,7 @@ def test_unique_square_relu():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/dynamic_shape/test_getnext_dynamic_pipeline.py

@@ -112,7 +112,7 @@ def test_getnext_sink_size_dynamic_pipeline():
         for output, (_, last_input) in zip(outputs, last_inputs):
             assert output.shape == last_input.shape
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -125,7 +125,7 @@ def test_getnext_sink_size_dynamic_pipeline_ascend():
     context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
     test_getnext_sink_size_dynamic_pipeline()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_getnext_sink_size_dynamic_pipeline_gpu():

tests/st/fallback/test_graph_fallback.py

@@ -39,7 +39,7 @@ class ControlNet(nn.Cell):
         return self.inner_function_2(a, b)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -57,7 +57,7 @@ def test_fallback_control_sink_tensor():
     assert output == output_expect
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -84,7 +84,7 @@ def test_np_tensor_list():
     assert len(tensor_list) == 3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -103,7 +103,7 @@ def test_list_count():
     assert list_count() == 1
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -131,7 +131,7 @@ def np_fallback_func_tensor_index(x):
     return me_x[x]
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -148,7 +148,7 @@ def test_np_fallback_func_tensor_index():
     assert output == output_expect
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -168,7 +168,7 @@ def test_np_calculate():
     assert np.all(np_calculate().asnumpy() == np.array([1, 1, 0, 0, 1]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -186,7 +186,7 @@ def test_fallback_tensor_array_astype():
     print(foo())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -211,7 +211,7 @@ def test_fallback_tuple_with_mindspore_function():
     assert foo()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/fallback/test_graph_fallback_and_or.py

@@ -20,7 +20,7 @@ from mindspore import ms_function, context, Tensor
 context.set_context(mode=context.GRAPH_MODE)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -40,7 +40,7 @@ def test_and_int_tensor():
     assert ret == 0
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -62,7 +62,7 @@ def test_and_int_tensor_2():
     assert ret == 0
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -85,7 +85,7 @@ def test_and_multi_int_tensor():
     assert "can be converted to bool, but" in str(error_info.value)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -106,7 +106,7 @@ def test_and_multi_int_tensor_2():
     assert "can be converted to bool, but" in str(error_info.value)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -126,7 +126,7 @@ def test_and_bool_tensor():
     assert ret == 0
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -148,7 +148,7 @@ def test_and_bool_tensor_2():
     assert ret == 1
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -169,7 +169,7 @@ def test_and_different_type_variable_tensor():
     assert "Cannot join the return values of different branches" in str(error_info.value)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -191,7 +191,7 @@ def test_and_different_type_constant_tensor():
     assert res == 2.0
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -212,7 +212,7 @@ def test_and_constant_and_variable_tensor():
     assert res == 2
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -234,7 +234,7 @@ def test_and_constant_and_variable_tensor_2():
     assert "Cannot join the return values of different branches" in str(error_info.value)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -255,7 +255,7 @@ def test_and_constant_and_variable_tensor_3():
     assert res == 1
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/fallback/test_graph_fallback_class.py

@@ -23,7 +23,7 @@ from mindspore import Tensor, context, ms_class
 context.set_context(mode=context.GRAPH_MODE)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -53,7 +53,7 @@ def test_fallback_class_attr():
     assert out.asnumpy() == 1
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -88,7 +88,7 @@ def test_fallback_class_method():
     assert out.asnumpy() == 10
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -124,7 +124,7 @@ def test_fallback_class_call():
     assert out.asnumpy() == 14
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -155,7 +155,7 @@ def test_fallback_class_input_attr():
     assert np.all(out.asnumpy() == expect_res)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -188,7 +188,7 @@ def test_fallback_class_input_method():
     assert out.asnumpy() == 6
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -223,7 +223,7 @@ def test_fallback_class_class_nested():
     assert out.asnumpy() == 1
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -273,7 +273,7 @@ def test_fallback_class_cell_nested():
     assert out == 25
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -307,7 +307,7 @@ def test_fallback_class_type_attr():
     assert out == 2
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -337,7 +337,7 @@ def test_fallback_class_create_instance_attr():
     assert out == 5
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -373,7 +373,7 @@ def test_fallback_class_create_instance_method():
     assert out.asnumpy() == 10
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -410,7 +410,7 @@ def test_fallback_class_create_instance_call():
     assert out == 10
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -429,7 +429,7 @@ def test_fallback_raise_error_not_class_type():
         func(1, 2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/fallback/test_graph_fallback_issubclass.py

@@ -20,7 +20,7 @@ from mindspore import context, Tensor, Parameter
 context.set_context(mode=context.GRAPH_MODE)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -50,7 +50,7 @@ def test_issubclass_list():
     assert (res.asnumpy() == [2, 3, 4]).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/fallback/test_graph_fallback_numpy.py

@@ -20,7 +20,7 @@ from mindspore import ms_function, context, Tensor
 context.set_context(mode=context.GRAPH_MODE)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -47,7 +47,7 @@ def test_np_linspace():
     print("e:", e)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -76,7 +76,7 @@ def test_np_arange_slice_1():
     assert np.all(e.asnumpy() == np.array([2, 3, 4]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -102,7 +102,7 @@ def test_np_arange_slice_2():
     assert np.all(d.asnumpy() == np.array([[2, 3], [4, 5], [5, 6]]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -155,7 +155,7 @@ def test_np_array_advanced_index_2():
     assert np.all(c.asnumpy() == np.array([2. + 6.j, 3.5 + 5.j]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -181,7 +181,7 @@ def test_np_array_advanced_index_3():
     print("c:", c)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -200,7 +200,7 @@ def test_np_reshape():
     assert np.all(np_reshape().asnumpy() == np.array([[0, 1, 2, 3], [4, 5, 6, 7]]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -219,7 +219,7 @@ def test_np_ndarray_flatten():
     assert np.all(np_ndarray_flatten().asnumpy() == np.array([0, 1, 2, 3, 4, 5, 6, 7]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -238,7 +238,7 @@ def test_np_ravel():
     assert np.all(np_ravel().asnumpy() == np.array([0, 4, 1, 5, 2, 6, 3, 7]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -257,7 +257,7 @@ def test_np_transpose():
     assert np.all(np_transpose().asnumpy() == np.array([0, 1, 2, 3]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -279,7 +279,7 @@ def test_np_rollaxis():
     assert x == 6 and y == 5
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -301,7 +301,7 @@ def test_np_swapaxes():
     assert x == 6 and y == 3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -321,7 +321,7 @@ def test_np_broadcast():
     assert np.all(np_broadcast().asnumpy() == np.array([3, 3]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -340,7 +340,7 @@ def test_np_broadcast_to():
     assert np.all(np_broadcast_to().asnumpy() == np.array([[0, 1, 2, 3], [0, 1, 2, 3]]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -359,7 +359,7 @@ def test_np_expand_dims():
     assert np.all(np_expand_dims().asnumpy() == np.array([[[1, 2], [3, 4]]]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -378,7 +378,7 @@ def test_np_squeeze():
     assert np.all(np_squeeze().asnumpy() == np.array([[0, 1], [2, 3]]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -406,7 +406,7 @@ def test_np_concat():
     assert np.all(out_vstack.asnumpy() == np.array([[1, 2], [3, 4], [5, 6], [7, 8]]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -431,7 +431,7 @@ def test_np_split():
     assert np.all(out_vsplit.asnumpy() == np.array([[[0, 1]], [[2, 3]]]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -459,7 +459,7 @@ def test_np_element():
     assert np.all(out_unique.asnumpy() == np.array([2, 5, 6, 7, 8, 9]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -487,7 +487,7 @@ def test_np_bitwise():
     assert right_shift.asnumpy() == 10
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -520,7 +520,7 @@ def test_np_char_1():
     assert char_upper.asnumpy() == 'FALLBACK'
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -553,7 +553,7 @@ def test_np_char_2():
     assert char_decode.asnumpy() == 'runoob'
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -584,7 +584,7 @@ def test_np_degree():
     assert np.isclose(out_arctan.asnumpy(), 45)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -617,7 +617,7 @@ def test_np_math_1():
     assert np.all(out_remainder.asnumpy() == np.array([0, 2]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -646,7 +646,7 @@ def test_np_math_2():
     assert np.allclose(out_power.asnumpy(), np.array([1, 4, 9]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -684,7 +684,7 @@ def test_np_statistic():
     assert np.isclose(out_var.asnumpy(), 2.0)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -716,7 +716,7 @@ def test_np_sort():
     assert np.all(out_where.asnumpy() == np.array([4]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
@@ -738,7 +738,7 @@ def test_np_extract():
     assert np.all(out_extract.asnumpy() == np.array([2, 4]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training

tests/st/fallback/test_graph_fallback_print.py

@@ -424,7 +424,7 @@ def test_print_dict():
     check_output(cap.output, patterns)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/gradient/test_taylor_differentiation_graph.py

@@ -105,7 +105,7 @@ def test_jet_single_input_single_output_graph_mode():
     assert np.allclose(out_primals.asnumpy(), expected_primals, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -128,7 +128,7 @@ def test_jet_single_input_single_output_with_scalar_graph_mode():
     assert np.allclose(out_primals.asnumpy(), expected_primals, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -150,7 +150,7 @@ def test_derivative_single_input_single_output_graph_mode():
     assert np.allclose(out_series.asnumpy(), expected_series, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -172,7 +172,7 @@ def test_jet_multiple_input_single_output_graph_mode():
     assert np.allclose(out_series.asnumpy(), expected_series, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -194,7 +194,7 @@ def test_derivative_multiple_input_single_output_graph_mode():
     assert np.allclose(out_series.asnumpy(), expected_series, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -228,7 +228,7 @@ def test_jet_construct_graph_mode():
     assert np.allclose(out_series.asnumpy(), expected_series, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -266,7 +266,7 @@ def test_derivative_construct_graph_mode():
     assert np.allclose(out_series[1].asnumpy(), expected_series_y, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_jet_function_graph_mode():

tests/st/gradient/test_taylor_differentiation_pynative.py

@@ -76,7 +76,7 @@ def test_jet_multiple_input_single_output_pynative_mode():
     assert np.allclose(out_primals.asnumpy(), expected_primals, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -98,7 +98,7 @@ def test_derivative_multiple_input_single_output_pynative_mode():
     assert np.allclose(out_series.asnumpy(), expected_series, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -120,7 +120,7 @@ def test_jet_single_input_single_output_pynative_mode():
     assert np.allclose(out_series.asnumpy(), expected_series, atol=1.e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training

tests/st/hypermap/test_hypermap.py

@@ -48,7 +48,7 @@ class HyperMapNet(nn.Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
@@ -71,7 +71,7 @@ def test_single_element_hypermap_with_tensor_input():
     assert np.allclose(output[1].asnumpy(), expect_output_2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
@@ -95,7 +95,7 @@ def test_double_elements_hypermap_tensor_tuple_inputs():
     assert np.allclose(output[1].asnumpy(), expect_output_2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
@@ -119,7 +119,7 @@ def test_double_elements_hypermap_tensor_list_inputs():
     assert np.allclose(output[1].asnumpy(), expect_output_2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
@@ -145,7 +145,7 @@ def test_doubel_elements_hypermap_correct_mix_inputs():
 
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
@@ -162,7 +162,7 @@ def test_double_elements_hypermap_inputs_length_mismatch():
         common_map((x, y))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard

tests/st/numpy_native/test_array_creations.py

@@ -1102,7 +1102,7 @@ def pad_with_npfunc(vector, pad_width, iaxis, kwargs):
     vector[-pad_width[1]:] = pad_value
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_pad_gpu():

tests/st/numpy_native/test_logic_ops.py

@@ -203,7 +203,7 @@ def onp_isnan(x):
     return onp.isnan(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
@@ -219,7 +219,7 @@ def onp_isinf(x):
     return onp.isinf(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard

tests/st/numpy_native/test_math_ops.py

@@ -919,7 +919,7 @@ def onp_maximum(x1, x2):
     return onp.maximum(x1, x2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
@@ -1303,7 +1303,7 @@ def test_kron():
     match_res(mnp.kron, onp.kron, x, y)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -1952,7 +1952,7 @@ def onp_nanmean(x):
     return a, b, c
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
@@ -2034,7 +2034,7 @@ def test_multi_dot():
     match_all_arrays(mnp.multi_dot(mnp_arrays[1:-1]), onp.linalg.multi_dot(arrays[1:-1]))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -2148,7 +2148,7 @@ def test_bincount():
                      onp.bincount(x, weights, minlength=25), error=3)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -2472,7 +2472,7 @@ def test_result_type():
         assert actual == expected
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -2555,7 +2555,7 @@ def test_ravel_multi_index():
         match_array(actual.asnumpy(), expected, error=5)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training

tests/st/ops/ascend/test_index_add.py

@@ -61,7 +61,7 @@ def test_index_add_float32():
     index_add_forward(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -77,7 +77,7 @@ def test_index_add_float16():
     index_add_forward(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -181,7 +181,7 @@ def test_index_add_grad_float32():
     index_add_grad_with_type(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -245,7 +245,7 @@ def test_index_add_grad_uint8():
     index_add_grad_with_type(np.uint8)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -269,7 +269,7 @@ def test_index_add_dynamic_y():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/ops/ascend/test_scatter_add.py

@@ -48,7 +48,7 @@ def scattre_add_forward(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -64,7 +64,7 @@ def test_scattre_add_forward_float16():
     scattre_add_forward(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -94,7 +94,7 @@ def scattre_add_dynamic_indices():
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -123,7 +123,7 @@ def scattre_add_dynamic_updates():
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/ops/ascend/test_scatter_div.py

@@ -76,7 +76,7 @@ def scattre_div_dynamic_indices():
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -95,7 +95,7 @@ def test_scattre_div_forward_float16():
     scattre_div_forward(np.float16, expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -114,7 +114,7 @@ def test_scattre_div_forward_float32():
     scattre_div_forward(np.float32, expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -130,7 +130,7 @@ def test_scattre_div_dynamic_indices():
     scattre_div_dynamic_indices()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/ops/ascend/test_scatter_func_op.py

@@ -317,7 +317,7 @@ def scatter_func_updates_nest_vmap():
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -333,7 +333,7 @@ def test_scatter_func_forward_float16():
     scatter_func_forward(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -349,7 +349,7 @@ def test_scatter_func_forward_float32():
     scatter_func_forward(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -365,7 +365,7 @@ def test_scatter_func_forward_int32():
     scatter_func_forward(np.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -381,7 +381,7 @@ def test_scatter_func_dynamic_indices():
     scatter_func_dynamic_indices()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -397,7 +397,7 @@ def test_scatter_func_dynamic_updates():
     scatter_func_dynamic_updates()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -413,7 +413,7 @@ def test_scatter_func_grad_float16():
     scatter_func_grad(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -429,7 +429,7 @@ def test_scatter_func_grad_float32():
     scatter_func_grad(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -445,7 +445,7 @@ def test_scatter_func_grad_int32():
     scatter_func_grad(np.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -461,7 +461,7 @@ def test_scatter_func_indices_vmap():
     scatter_func_indices_vmap()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -477,7 +477,7 @@ def test_scatter_func_updates_vmap():
     scatter_func_updates_vmap()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/ops/ascend/test_scatter_mul.py

@@ -84,7 +84,7 @@ def scatter_mul_dynamic_indices():
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -100,7 +100,7 @@ def test_scatter_mul_forward_float16():
     scatter_mul_forward(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -116,7 +116,7 @@ def test_scatter_mul_forward_float32():
     scatter_mul_forward(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -132,7 +132,7 @@ def test_scatter_mul_forward_int32():
     scatter_mul_forward(np.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -148,7 +148,7 @@ def test_scatter_mul_dynamic_indices():
     scatter_mul_dynamic_indices()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -164,7 +164,7 @@ def test_scatter_mul_dynamic_updates():
     scatter_mul_dynamic_updates()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/ops/ascend/test_tensor_scatter_arithmetic.py

@@ -104,7 +104,7 @@ def test_tensor_scatter_arithmetic_small_float(func, data_type, index_type):
     compare_with_numpy(func, input_x, indices, updates)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -124,7 +124,7 @@ def test_tensor_scatter_arithmetic_small_int(func, data_type, index_type):
     compare_with_numpy(func, input_x, indices, updates)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -152,7 +152,7 @@ def test_tensor_scatter_arithmetic_multi_dims(func, data_type, index_type):
     compare_with_numpy(func, input_x, indices, updates)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -176,7 +176,7 @@ def test_tensor_scatter_arithmetic_function_op(func, data_type, index_type):
     np.testing.assert_allclose(output.asnumpy(), expected, rtol=1e-6)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -204,7 +204,7 @@ def test_tensor_scatter_arithmetic_tensor_op(func, data_type, index_type):
     np.testing.assert_allclose(output.asnumpy(), expected, rtol=1e-6)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/ops/cpu/test_random_shuffle.py

@@ -53,7 +53,7 @@ def test_random_shuffle_op_dtype(mode, dtype):
     assert output.shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_cpu
 @pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
@@ -74,7 +74,7 @@ def test_random_shuffle_op_tensor(mode, shape):
     assert output.shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_cpu
 @pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
@@ -91,7 +91,7 @@ def test_random_shuffle_op_scalar(mode):
     assert output == x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_cpu
 @pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
@@ -112,7 +112,7 @@ def test_random_shuffle_op_dynamic_shape(mode):
     assert (output_dyn.asnumpy() == out.asnumpy()).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_cpu
 @pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])

tests/st/ops/gpu/test_acosh_grad_grad_op.py

@@ -44,7 +44,7 @@ class NetAcoshGradGrad(nn.Cell):
         return backward_net(y, grad, dout)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def acosh_grad_grad_base(dtype, loss):

tests/st/ops/gpu/test_ada_max_op.py

@@ -63,7 +63,7 @@ def main_test(var_numpy, m_numpy, v_numpy, beta1_power_numpy, lr_numpy, beta1_nu
     return (expect_m, res_m_mindspore), (expect_v, res_v_mindspore), (expect_var, res_var_mindspore)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_adamax_fff():
@@ -93,7 +93,7 @@ def test_apply_adamax_fff():
     assert numpy.all(var[0] - var[1] < eps_f32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_adamax_ddd():

tests/st/ops/gpu/test_adadelta_op.py

@@ -63,7 +63,7 @@ def main_test(var_np, accum_np, accum_update_np, lr_np, rho_np, epsilon_np, grid
            (expect_var_np, res_var_mindspore)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_adadelta_fff():
@@ -90,7 +90,7 @@ def test_apply_adadelta_fff():
     assert np.all(abs(var[0] - var[1]) < eps_f32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_adadelta_ddd():

tests/st/ops/gpu/test_adagrad_v2_op.py

@@ -58,7 +58,7 @@ def main_test(var_np, accum_np, lr_np, grident_np, epsilon_np, update_slots):
     return (expect_var_np, res_var_mindspore), (expect_accum_np, res_accum_mindspore)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_adagradv2_fff():
@@ -83,7 +83,7 @@ def test_apply_adagradv2_fff():
     assert np.all(abs(var[0] - var[1]) < eps_f32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_adagradv2_ddd():

tests/st/ops/gpu/test_adaptive_avg_pool1d_op.py

@@ -29,7 +29,7 @@ def adaptive_avg_pool1d_forward_functional(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_adaptive_avg_pool1d_forward_float32_functional():

tests/st/ops/gpu/test_adaptive_avg_pool2d_op.py

@@ -112,7 +112,7 @@ def test_net_value():
     assert (dx.asnumpy() == expect_dx).all
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_graph_mode():
@@ -144,7 +144,7 @@ def test_net_graph_mode():
     assert (dx.asnumpy() == expect_dx).all
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_graph_mode_fp64():
@@ -176,7 +176,7 @@ def test_net_graph_mode_fp64():
     assert (dx.asnumpy() == expect_dx).all
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_adaptive_avgpool_vmap():

tests/st/ops/gpu/test_adaptive_avg_pool3d_op.py

@@ -50,7 +50,7 @@ class GradNet(nn.Cell):
         return self.adaptive_avg_pool3d_grad(x, dy)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
@@ -74,7 +74,7 @@ def test_net_normal_with_functional(mode, shape):
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
@@ -99,7 +99,7 @@ def test_net_normal_with_nn(mode, shape):
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_normal():
@@ -115,7 +115,7 @@ def test_net_normal():
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_graph_mode_fp64():

tests/st/ops/gpu/test_adaptive_max_pool1d_op.py

@@ -27,7 +27,7 @@ def adaptive_max_pool1d_forward_functional(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_adaptive_max_pool1d_forward_float32_functional():

tests/st/ops/gpu/test_adaptive_max_pool2d_op.py

@@ -36,7 +36,7 @@ class NetP(nn.Cell):
         return self.adaptive_max_pool2d(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_normal():
@@ -52,7 +52,7 @@ def test_net_normal():
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_h_none():
@@ -68,7 +68,7 @@ def test_net_h_none():
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_hxh():
@@ -94,7 +94,7 @@ class NetWithIndices(nn.Cell):
         return self.adaptive_max_pool2d(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_with_indices():
@@ -110,7 +110,7 @@ def test_net_with_indices():
     assert output[1].asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_f():
@@ -135,7 +135,7 @@ class Netnn(nn.Cell):
         return self.adaptive_max_pool2d(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_nn():
@@ -176,7 +176,7 @@ def test_tensor_interface_graph():
     assert y.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dynamic_shape():

tests/st/ops/gpu/test_adaptive_max_pool3d_op.py

@@ -66,7 +66,7 @@ class RankDynamicNet(nn.Cell):
         return out, in_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_rank_dynamic():
@@ -86,7 +86,7 @@ def test_rank_dynamic():
     assert (dyn_output[1].asnumpy() == output[1].asnumpy()).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_4d():
@@ -103,7 +103,7 @@ def test_net_4d():
     assert output[0].asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_5d():
@@ -120,7 +120,7 @@ def test_net_5d():
     assert output[0].asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_dynamic_shape():
@@ -138,7 +138,7 @@ def test_net_dynamic_shape():
     assert output[0].asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_vmap():

tests/st/ops/gpu/test_add_op.py

@@ -227,14 +227,14 @@ def add_dynamic(nptype):
     assert (output2.asnumpy() == expect2).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_dynamic_float64():
     add_dynamic(np.float64)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_dynamic_float32():
@@ -275,7 +275,7 @@ def test_add_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_float32_tensor_api():

tests/st/ops/gpu/test_addcdiv_op.py

@@ -29,7 +29,7 @@ class NetAddcdiv(nn.Cell):
         return self.addcdiv(input_data, x1, x2, value)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_addcdiv_float32_graph(type_s=np.float32):
@@ -54,7 +54,7 @@ def test_addcdiv_float32_graph(type_s=np.float32):
     assert np.all(abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_addcdiv_float64_pynative_value(type_s=np.float64):

tests/st/ops/gpu/test_addcmul_op.py

@@ -29,7 +29,7 @@ class NetAddcmul(nn.Cell):
         return self.addcmul(input_data, x1, x2, value)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_addcmul_float32_graph(type_s=np.float32):
@@ -55,7 +55,7 @@ def test_addcmul_float32_graph(type_s=np.float32):
 
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_addcmul_float64_pynative_value(type_s=np.float64):

tests/st/ops/gpu/test_addmv_op.py

@@ -33,7 +33,7 @@ def test_addmv_forward_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_addmv_forward_float32_tensor_api():

tests/st/ops/gpu/test_addr_op.py

@@ -33,7 +33,7 @@ def test_addr_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_addr_float32_tensor_api():

tests/st/ops/gpu/test_affine_grid_op.py

@@ -97,7 +97,7 @@ def np_affine_grid_5d(theta, size, align_corners=False):
     return grid.reshape((n, d, h, w, 3))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("net", [AffineGridNet, AffineGridDynamicShapeNet])
@@ -130,7 +130,7 @@ def test_affine_grid_4d(net, align, dtype):
     assert np.allclose(np_grid, ms_grid.asnumpy(), atol=atol)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("net", [AffineGridNet, AffineGridDynamicShapeNet])

tests/st/ops/gpu/test_apply_adagrad_a_d_op.py

@@ -141,7 +141,7 @@ def ms_forward_impl_vmap2(grad, np_lr, np_l1, np_l2, np_global_step, data_type):
     return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_adagrad_da_float():
@@ -170,7 +170,7 @@ def test_apply_adagrad_da_float():
         np.testing.assert_allclose(np_out[i], ms_out[i].asnumpy(), rtol=error, atol=error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_adagrad_da_float16():
@@ -201,7 +201,7 @@ def test_apply_adagrad_da_float16():
         np.testing.assert_allclose(np_out[i], ms_out[i].asnumpy(), rtol=error, atol=error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_adagrad_da_float16_vmap():
@@ -231,7 +231,7 @@ def test_apply_adagrad_da_float16_vmap():
         np.testing.assert_allclose(np_out[i], ms_out[i].asnumpy(), rtol=error, atol=error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_adagrad_da_float_vmap():
@@ -260,7 +260,7 @@ def test_apply_adagrad_da_float_vmap():
         np.testing.assert_allclose(np_out[i], ms_out[i].asnumpy(), rtol=error, atol=error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_adagrad_da_float16_vmap2():
@@ -290,7 +290,7 @@ def test_apply_adagrad_da_float16_vmap2():
         np.testing.assert_allclose(np_out[i], ms_out[i].asnumpy(), rtol=error, atol=error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_adagrad_da_float_vmap2():

tests/st/ops/gpu/test_apply_adam_with_amsgrad_op.py

@@ -52,7 +52,7 @@ def numpy_apply_adam_with_amsgrad(var, m, v, vhat, grad, beta1=0.9, beta2=0.999,
     return var
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("data_type", [np.float32, np.float16])
 def test_apply_adam_with_amsgrad_op(data_type):
@@ -98,7 +98,7 @@ class AmsgradNetVmap(nn.Cell):
         return self.vmap_amsgrad(self.var, self.m, self.v, self.vhat, beta1_power, beta2_power, lr, grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 def test_apply_adam_witm_amsgrad_op_vmap():
     """
@@ -144,7 +144,7 @@ class AmsgradNetVmap2(nn.Cell):
         return self.vmap_amsgrad(self.var, self.m, self.v, self.vhat, beta1_power, beta2_power, lr, grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 def test_apply_adam_with_amsgrad_grad_op_vmap2():
     """

tests/st/ops/gpu/test_apply_add_sign_op.py

@@ -35,7 +35,7 @@ class Net(nn.Cell):
         return z
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_addsign_graph_float32():

tests/st/ops/gpu/test_apply_proximal_adagrad_op.py

@@ -35,7 +35,7 @@ class ApplyProximalAdagradTEST(nn.Cell):
         return self.apply_proximal_adagrad(self.var, self.accum, lr, l1, l2, grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("data_type", [np.float32, np.float16])
@@ -86,7 +86,7 @@ class AdgradNetVmap(nn.Cell):
         return self.vmap_adagrad(self.var, self.accum, lr, l1, l2, grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_proximal_adagrad_op_vmap():
@@ -139,7 +139,7 @@ class AdgradNetVmap2(nn.Cell):
         return self.vmap_adagrad(self.var, self.accum, lr, l1, l2, grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_apply_proximal_adagrad_op_vmap2():

tests/st/ops/gpu/test_approximate_equal_op.py

@@ -41,7 +41,7 @@ class NetApproximateEqual(nn.Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_approximate_equal_fp16():
@@ -59,7 +59,7 @@ def test_approximate_equal_fp16():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_approximate_equal_fp32():

tests/st/ops/gpu/test_argmax_op.py

@@ -84,7 +84,7 @@ def test_argmax_2d():
         assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmax_high_dims():
@@ -109,7 +109,7 @@ def adaptive_argmax_functional(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmax_float32_functional():

tests/st/ops/gpu/test_argmin_op.py

@@ -34,7 +34,7 @@ class NetArgmin(nn.Cell):
         return self.argmin(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmin_1d():
@@ -54,7 +54,7 @@ def test_argmin_1d():
         assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmin_2d():
@@ -82,7 +82,7 @@ def test_argmin_2d():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmin_high_dims():

tests/st/ops/gpu/test_asin_op.py

@@ -52,7 +52,7 @@ def test_asin_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asin_float32_tensor_api():

tests/st/ops/gpu/test_asinh_grad_grad_op.py

@@ -44,7 +44,7 @@ class NetAsinhGradGrad(nn.Cell):
         return backward_net(y, grad, dout)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def asinh_grad_grad_base(dtype, loss):

tests/st/ops/gpu/test_asinh_grad_op.py

@@ -32,7 +32,7 @@ def test_asinhgrad_fp32():
     output_np = dout_np / np.cosh(y_np)
     assert np.allclose(output_ms.asnumpy(), output_np, 1e-4, 1e-4)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asinhgrad_fp16():

tests/st/ops/gpu/test_asinh_op.py

@@ -53,7 +53,7 @@ def test_asinh_forward_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asinh_forward_float32_tensor_api():

tests/st/ops/gpu/test_assert_op.py

@@ -31,7 +31,7 @@ class AssertTEST(nn.Cell):
         return self.assert1(cond, x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_assert_op():

tests/st/ops/gpu/test_assign_sub_op.py

@@ -33,7 +33,7 @@ class AssignSub(nn.Cell):
         return res
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_assign_sub():
@@ -76,7 +76,7 @@ def test_assign_sub():
     assert (output2.asnumpy() == expect2).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_assign_sub_float16():

tests/st/ops/gpu/test_atan_grad_grad_op.py

@@ -44,7 +44,7 @@ class NetAtanGradGrad(nn.Cell):
         return backward_net(x, grad, dout)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def atan_grad_grad_base(dtype, loss):

tests/st/ops/gpu/test_atan_op.py

@@ -53,7 +53,7 @@ def test_atan_forward_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atan_forward_float32_tensor_api():

tests/st/ops/gpu/test_atanh_op.py

@@ -26,7 +26,7 @@ def atanh(x):
     return 0.5 * np.log((1. + x) / (1. - x))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atanh_fp64():
@@ -43,7 +43,7 @@ def test_atanh_fp64():
     assert np.allclose(output_ms.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atanh_fp32():
@@ -60,7 +60,7 @@ def test_atanh_fp32():
     assert np.allclose(output_ms.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atanh_fp16():
@@ -77,7 +77,7 @@ def test_atanh_fp16():
     assert np.allclose(output_ms.asnumpy(), expect, 1e-3, 1e-3)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atanh_complex64():
@@ -94,7 +94,7 @@ def test_atanh_complex64():
     assert np.allclose(output_ms.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atanh_complex128():
@@ -123,7 +123,7 @@ def test_atanh_forward_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atanh_forward_float32_tensor_api():

tests/st/ops/gpu/test_avgpool_op.py

@@ -51,7 +51,7 @@ class AvgPoolGrad(nn.Cell):
         return self.grad(self.forward)(x, sens)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool2d_valid():
@@ -85,7 +85,7 @@ def test_avgpool2d_valid():
     assert np.allclose(actual_grad[0].asnumpy(), expect_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool2d_same():
@@ -119,7 +119,7 @@ def test_avgpool2d_same():
     assert np.allclose(actual_grad[0].asnumpy(), expect_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool3d_1():
@@ -164,7 +164,7 @@ def test_avgpool3d_1():
     assert np.allclose(actual_grad[0].asnumpy(), expect_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool3d_2():
@@ -209,7 +209,7 @@ def test_avgpool3d_2():
     assert np.allclose(actual_grad[0].asnumpy(), expect_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool3d_3():
@@ -251,7 +251,7 @@ def test_avgpool3d_3():
     assert np.allclose(actual_grad[0].asnumpy(), expect_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool3d_4():
@@ -308,7 +308,7 @@ def test_avgpool3d_4():
     assert np.allclose(actual_grad[0].asnumpy(), expect_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool_vmap():
@@ -325,7 +325,7 @@ def test_avgpool_vmap():
     assert out.shape == (6, 3, 1, 1, 3, 3)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool_grad_vmap():
@@ -358,7 +358,7 @@ class DynamicShapeAvgPool3DGrad(nn.Cell):
         return self.net(x_shape, sens)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_avgpool3d_grad_dynamic_shape():

tests/st/ops/gpu/test_bartlett_window_op.py

@@ -75,7 +75,7 @@ def bartlett_window_pynative(periodic, dtype, loss):
     assert np.allclose(bartlett_window_output.asnumpy(), bartlett_window_expect.numpy().astype(nptype), loss, loss)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bartlett_window_graph_int32_true_float32():
@@ -87,7 +87,7 @@ def test_bartlett_window_graph_int32_true_float32():
     bartlett_window(periodic=True, dtype="float32", loss=1.0e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bartlett_window_pynative_int64_false_float64():

tests/st/ops/gpu/test_batch_matmul.py

@@ -253,7 +253,7 @@ def test_bmm_forward_tensor_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bmm_forward_float32_tensor_api():
@@ -281,7 +281,7 @@ def test_bmm_forward_functional_api(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bmm_forward_float32_functional_api():

tests/st/ops/gpu/test_batchnorm_grad_grad_op.py

@@ -92,7 +92,7 @@ def get_nc_inputs(np_type):
     return x, scale, dy, dout_dx, dout_dscale, dout_dbias
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nhwc():
@@ -121,7 +121,7 @@ def test_batchnorm_grad_grad_training_nhwc():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nchw():
@@ -150,7 +150,7 @@ def test_batchnorm_grad_grad_training_nchw():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_inference_nhwc():
@@ -179,7 +179,7 @@ def test_batchnorm_grad_grad_inference_nhwc():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_inference_nchw():
@@ -208,7 +208,7 @@ def test_batchnorm_grad_grad_inference_nchw():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nc():
@@ -233,7 +233,7 @@ def test_batchnorm_grad_grad_training_nc():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_inference_nc():
@@ -258,7 +258,7 @@ def test_batchnorm_grad_grad_inference_nc():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nchw_2():
@@ -311,7 +311,7 @@ def test_batchnorm_grad_grad_training_nchw_2():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nhwc_2():
@@ -356,7 +356,7 @@ def test_batchnorm_grad_grad_training_nhwc_2():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nchw_dynamic_shape():
@@ -415,7 +415,7 @@ def test_batchnorm_grad_grad_training_nchw_dynamic_shape():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nhwc_dynamic_shape():
@@ -466,7 +466,7 @@ def test_batchnorm_grad_grad_training_nhwc_dynamic_shape():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_training_nchw_vmap():
@@ -505,7 +505,7 @@ def test_batchnorm_grad_grad_training_nchw_vmap():
         assert np.allclose(dscale.asnumpy(), expect_dscale)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_grad_grad_inference_nhwc_vmap():

tests/st/ops/gpu/test_batchnorm_op.py

@@ -358,7 +358,7 @@ def test_batch_norm_forward_functional(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batch_norm_forward_float32_functional():

tests/st/ops/gpu/test_batchtospace_op.py

@@ -71,13 +71,13 @@ def BatchToSpace_pynative(nptype, block_size=2, input_shape=(4, 1, 2, 2)):
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchtospace_graph_float32():
     BatchToSpace(np.float32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchtospace_graph_float16():

tests/st/ops/gpu/test_bce_with_logits_loss.py

@@ -86,7 +86,7 @@ def test_reduction_mean_testcases():
     assert math.isclose(output.asnumpy().tolist(), expected, abs_tol=0.00001)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_reduction_sum_testcases():

tests/st/ops/gpu/test_bernoulli.py

@@ -31,7 +31,7 @@ class Net(nn.Cell):
         return self.bernoulli(x, p)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bernoulli():
@@ -65,7 +65,7 @@ class BernoulliDynamic(nn.Cell):
         return self.bernoulli(x, p)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bernoulli_dynamic():

tests/st/ops/gpu/test_bessel_op.py

@@ -266,7 +266,7 @@ class BesselY1GradNet(Cell):
         return gout
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_y0_fp32():
@@ -288,7 +288,7 @@ def test_bessel_y0_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_y0_fp16():
@@ -310,7 +310,7 @@ def test_bessel_y0_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_y1_fp32():
@@ -332,7 +332,7 @@ def test_bessel_y1_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_y1_fp16():
@@ -354,7 +354,7 @@ def test_bessel_y1_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_j0_fp32():
@@ -376,7 +376,7 @@ def test_bessel_j0_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_j0_fp16():
@@ -398,7 +398,7 @@ def test_bessel_j0_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_j1_fp32():
@@ -420,7 +420,7 @@ def test_bessel_j1_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_j1_fp16():
@@ -442,7 +442,7 @@ def test_bessel_j1_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k0_fp32():
@@ -463,7 +463,7 @@ def test_bessel_k0_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k0_fp16():
@@ -484,7 +484,7 @@ def test_bessel_k0_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k0e_fp32():
@@ -505,7 +505,7 @@ def test_bessel_k0e_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k0e_fp16():
@@ -526,7 +526,7 @@ def test_bessel_k0e_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k1_fp32():
@@ -547,7 +547,7 @@ def test_bessel_k1_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k1_fp16():
@@ -568,7 +568,7 @@ def test_bessel_k1_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k1e_fp32():
@@ -589,7 +589,7 @@ def test_bessel_k1e_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_k1e_fp16():
@@ -610,7 +610,7 @@ def test_bessel_k1e_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i0_fp32():
@@ -632,7 +632,7 @@ def test_bessel_i0_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i0_fp16():
@@ -654,7 +654,7 @@ def test_bessel_i0_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i0e_fp32():
@@ -676,7 +676,7 @@ def test_bessel_i0e_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i0e_fp16():
@@ -698,7 +698,7 @@ def test_bessel_i0e_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i1_fp32():
@@ -720,7 +720,7 @@ def test_bessel_i1_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i1_fp16():
@@ -742,7 +742,7 @@ def test_bessel_i1_fp16():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i1e_fp32():
@@ -764,7 +764,7 @@ def test_bessel_i1e_fp32():
     assert np.allclose(output_grad_ms[0].asnumpy(), expect_grad_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bessel_i1e_fp16():

tests/st/ops/gpu/test_bias_add_op.py

@@ -33,7 +33,7 @@ def test_bias_add_forward_functional(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bias_add_forward_float32_functional():

tests/st/ops/gpu/test_bidense.py

@@ -33,7 +33,7 @@ class Net(nn.Cell):
         return self.bidense(x1, x2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net():
@@ -50,7 +50,7 @@ def test_net():
     assert output.shape == (128, 40)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_nd():
@@ -67,7 +67,7 @@ def test_net_nd():
     assert output.shape == (128, 4, 40)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_1d():

tests/st/ops/gpu/test_binary_cross_entropy_op.py

@@ -109,7 +109,7 @@ def test_binary_cross_entropy_forward_functional(nptype):
     np.testing.assert_array_almost_equal(output.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_binary_cross_entropy_forward_float32_functional():

tests/st/ops/gpu/test_bitwiseand_op.py

@@ -30,7 +30,7 @@ class NetBitwiseAnd(nn.Cell):
         return self.bitwiseand(x1, x2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwiseand_graph():
@@ -50,7 +50,7 @@ def test_bitwiseand_graph():
         assert np.all(abs(result_expect - result) < eps)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwiseand_graph1():
@@ -71,7 +71,7 @@ def test_bitwiseand_graph1():
         assert np.all(abs(result_expect - result) < eps)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwiseand_graph2():

tests/st/ops/gpu/test_bitwiseor_op.py

@@ -30,7 +30,7 @@ class NetBitwiseOr(nn.Cell):
         return self.bitwiseor(x1, x2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwiseor_graph():
@@ -51,7 +51,7 @@ def test_bitwiseor_graph():
         assert np.all(abs(result_expect - result) < eps)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwiseor_graph2():
@@ -72,7 +72,7 @@ def test_bitwiseor_graph2():
         assert np.all(abs(result_expect - result) < eps)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwiseor_graph3():

tests/st/ops/gpu/test_bitwisexor_op.py

@@ -30,7 +30,7 @@ class NetBitwiseXor(nn.Cell):
         return self.bitwisexor(x1, x2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwisexor_graph():
@@ -51,7 +51,7 @@ def test_bitwisexor_graph():
         assert np.all(abs(result_expect - result) < eps)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwisexor_graph1():
@@ -72,7 +72,7 @@ def test_bitwisexor_graph1():
         assert np.all(abs(result_expect - result) < eps)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bitwisexor_graph2():

tests/st/ops/gpu/test_blackman_window_op.py

@@ -76,7 +76,7 @@ def blackman_window_pynative(periodic, dtype, loss):
     assert np.allclose(blackman_window_output.asnumpy(), blackman_window_expect.numpy().astype(nptype), loss, loss)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_blackman_window_graph_int32_true_float32():
@@ -88,7 +88,7 @@ def test_blackman_window_graph_int32_true_float32():
     blackman_window(periodic=True, dtype="float32", loss=1.0e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_blackman_window_pynative_int64_false_float64():

tests/st/ops/gpu/test_broadcast_op.py

@@ -297,7 +297,7 @@ def test_broadcast_diff_dims():
     assert np.allclose(output_ms.asnumpy(), output_np)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_broadcast_diff_dims_float64():

tests/st/ops/gpu/test_broadcast_to_ops.py

@@ -125,7 +125,7 @@ def test_broadcast_dyn_init():
     assert np.allclose(output.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_broadcast_dyn_invalid_init():

tests/st/ops/gpu/test_bucketize_op.py

@@ -32,7 +32,7 @@ class BucketizeNet(Cell):
         return self.bucketize(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bucketize_4x5_float64():
@@ -55,7 +55,7 @@ def test_bucketize_4x5_float64():
     assert np.allclose(output_ms.asnumpy(), expect_output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bucketize_4x5x6_int32():

tests/st/ops/gpu/test_ceil_op.py

@@ -36,7 +36,7 @@ class NetCeil(nn.Cell):
         return self.ceil(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_ceil_fp32():
@@ -52,7 +52,7 @@ def test_ceil_fp32():
     assert np.allclose(output.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_ceil_fp16():
@@ -68,7 +68,7 @@ def test_ceil_fp16():
     assert np.allclose(output.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_tensor_ceil():
@@ -85,7 +85,7 @@ def test_tensor_ceil():
     assert np.allclose(output.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_func_ceil():
@@ -103,7 +103,7 @@ def test_func_ceil():
 
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_vmap():
@@ -129,7 +129,7 @@ def test_vmap():
 
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_vmap2():

tests/st/ops/gpu/test_celu_op.py

@@ -33,7 +33,7 @@ class CeluTEST(nn.Cell):
         return self.celu(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("data_type", [np.float32, np.float16])
@@ -57,7 +57,7 @@ def test_celu_op(data_type):
     np.testing.assert_allclose(output.asnumpy(), expect, rtol=error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("data_type", [np.float32, np.float16])
@@ -80,7 +80,7 @@ def test_celu_func(data_type):
     np.testing.assert_allclose(output.asnumpy(), expect, rtol=error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 def test_celu_vmap():

tests/st/ops/gpu/test_col2im_op.py

@@ -35,7 +35,7 @@ class Col2ImTest(nn.Cell):
         return self.c2i(x, output_size)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("mode, input_type",

tests/st/ops/gpu/test_complex_abs_op.py

@@ -19,7 +19,7 @@ from mindspore.ops.operations import math_ops as P
 import mindspore.common.dtype as ms
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_complex_abs_complex64_3x3():

tests/st/ops/gpu/test_complex_op.py

@@ -47,7 +47,7 @@ def complex_compare(complex1, complex2):
     return np.allclose(real1, real2, rtol=5e-03, atol=5e-03) and np.allclose(imag1, imag2, rtol=5e-03, atol=5e-03)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_complex_elemwise():
@@ -89,7 +89,7 @@ def test_complex_elemwise():
     assert complex_compare(res_ms, res_to)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_complex_broadcast():

tests/st/ops/gpu/test_conv3d_op.py

@@ -44,7 +44,7 @@ class NetConv3d(nn.Cell):
         return self.conv(x, w)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv3d_dshape_1():
@@ -65,7 +65,7 @@ def test_conv3d_dshape_1():
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv3d_dshape_2():
@@ -86,7 +86,7 @@ def test_conv3d_dshape_2():
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv3d():
@@ -153,7 +153,7 @@ class MSGradNet(nn.Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv3d_grad():

tests/st/ops/gpu/test_conv3dtranspose_op.py

@@ -42,7 +42,7 @@ class NetConv3dTranspose(nn.Cell):
         return self.conv_trans(x, w)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv3dtranspose_dshape_1():
@@ -63,7 +63,7 @@ def test_conv3dtranspose_dshape_1():
     assert output.asnumpy().shape == expect_shape
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv3dtranspose_dshape_2():

tests/st/ops/gpu/test_cosh_op.py

@@ -29,7 +29,7 @@ class NetCosh(nn.Cell):
         return ops.cosh(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype, tol', [(np.float16, 1.e-3), (np.float32, 1.e-5), (np.float64, 1.e-8),
@@ -49,7 +49,7 @@ def test_cosh_graph(dtype, tol):
     assert np.allclose(output.asnumpy(), expect, atol=tol, rtol=tol)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype, tol', [(np.float16, 1.e-3), (np.float32, 1.e-5), (np.float64, 1.e-8),
@@ -68,7 +68,7 @@ def test_cosh_py(dtype, tol):
     assert np.allclose(output.asnumpy(), expect, atol=tol, rtol=tol)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cosh_dynamic_shape():
@@ -92,7 +92,7 @@ def test_cosh_dynamic_shape():
     assert np.allclose(output.asnumpy(), expect, atol=tol, rtol=tol)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype, tol', [(np.float16, 1.e-3), (np.float32, 1.e-5), (np.float64, 1.e-8)])

tests/st/ops/gpu/test_crop_and_resize_grad_boxes_op.py

@@ -28,7 +28,7 @@ class NetCropAndResizeGradBoxes(nn.Cell):
         return self.op(grads, images, boxes, box_index)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("image_type", [np.uint8, np.uint16, np.int8, np.int16, np.int32, np.int64, np.float16,
@@ -74,7 +74,7 @@ def test_crop_and_resize_grad_boxes_float32(image_type):
     assert np.all(abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("image_type", [np.uint8, np.uint16, np.int8, np.int16, np.int32, np.int64, np.float16,

tests/st/ops/gpu/test_crop_and_resize_grad_image_op.py

@@ -29,7 +29,7 @@ class NetCropAndResizeGradImage(nn.Cell):
         return self.op(grads, boxes, box_index, image_size)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("input_type", [np.float32, np.float64])
@@ -68,7 +68,7 @@ def test_crop_and_resize_grad_image_bilinear(input_type, output_type):
     assert np.all(abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("input_type", [np.float32, np.float64])

tests/st/ops/gpu/test_ctclossv2_op.py

@@ -118,7 +118,7 @@ def compare_to_numpy(method, input_matrix, target, input_lengths, target_lengths
     assert np.allclose(loss.asnumpy(), expected)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("batch", [1, 10])
@@ -242,7 +242,7 @@ def test_ctc_loss_v2_un_padded_grad():
     np.allclose(grad.asnumpy(), expected_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("batch", [1, 10])

tests/st/ops/gpu/test_cum_minmax_op.py

@@ -60,7 +60,7 @@ def cum_minmax_compare(op, x, expected, axis, data_type, is_vmap=False):
     assert np.allclose(output[1].asnumpy(), expected[1])
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("data_type", [np.uint8, np.int8, np.int32, np.float16])
@@ -86,7 +86,7 @@ def test_cummin_multi_dims(data_type):
     cum_minmax_compare(op, x, cummin_output, axis, data_type)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("data_type", [np.uint8, np.uint32, np.int8, np.int32, np.int64, np.float16, np.float32])
@@ -114,7 +114,7 @@ def test_cummax_multi_dims(data_type):
     cum_minmax_compare(op, x, cummax_output, axis, data_type)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.env_onecard
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.parametrize("data_type", [np.float16, np.float32])
@@ -145,7 +145,7 @@ class VmapNet(nn.Cell):
         return self.ops(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cummin_vmap_net():
@@ -170,7 +170,7 @@ def test_cummin_vmap_net():
     cum_minmax_compare(op, x, cummin_output, axis, np.float32, is_vmap=True)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cummax_vmap_net():

tests/st/ops/gpu/test_cumprod_op.py

@@ -172,7 +172,7 @@ class Net(nn.Cell):
         return self.op(x, 0)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cumprod_dshape():

tests/st/ops/gpu/test_data_format_vec_permute.py

@@ -31,7 +31,7 @@ class DataFormatVecPermuteNet(nn.Cell):
         return self.op(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_data_format_vec_permute_1d_input_int32():
@@ -50,7 +50,7 @@ def test_data_format_vec_permute_1d_input_int32():
     assert (z_ms.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_data_format_vec_permute_2d_input_int64():

tests/st/ops/gpu/test_dataformatdimmap_op.py

@@ -30,7 +30,7 @@ def np_all_close_with_loss(out, expect):
     return np.allclose(out, expect, 0.0005, 0.0005, equal_nan=True)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("data_type", [np.int32, np.int64])
@@ -54,7 +54,7 @@ def test_data_formata_dim_map_gpu(data_type):
     assert np.allclose(output_3_gpu.asnumpy(), output_3_expect_gpu)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("data_type", [np.int32, np.int64])

tests/st/ops/gpu/test_deformable_conv.py

@@ -23,7 +23,7 @@ from mindspore import Tensor
 context.set_context(device_target="GPU")
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_deformable_conv2d():

tests/st/ops/gpu/test_deformable_offsets_grad_op.py

@@ -34,7 +34,7 @@ class NetDeformableOffsetsGrad(nn.Cell):
         return self.grad_op(grad, input_x, offsets)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype', [np.float16, np.float32])
@@ -68,7 +68,7 @@ def test_deformable_offsets_grad_nchw(dtype):
     assert np.allclose(output[1].asnumpy(), expect_grad_offset, rtol)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype', [np.float16, np.float32])

tests/st/ops/gpu/test_determinant_triangle.py

@@ -1,44 +0,0 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
-#
-# 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.
-# ============================================================================
-
-import numpy as np
-import pytest
-import mindspore.context as context
-import mindspore.nn as nn
-from mindspore import Tensor
-from mindspore.ops import operations as P
-from mindspore.common import dtype as mstype
-
-context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
-
-
-class Net(nn.Cell):
-    def __init__(self, fill_mode=0):
-        super(Net, self).__init__()
-        self.det_triangle = P.DetTriangle(fill_mode=fill_mode)
-
-    def construct(self, x):
-        return self.det_triangle(x)
-
-@pytest.mark.level2
-@pytest.mark.platform_x86_gpu_training
-@pytest.mark.env_onecard
-def test_net_1D():
-    fill_mode = 0
-    input_x = np.array([[1, 0, 0], [2, 3, 0], [4, 5, 6]]).astype(np.float32)
-    net = Net(fill_mode=fill_mode)
-    tx = Tensor(input_x, mstype.float32)
-    output = net(tx)
-    assert output == 18