!35316 gpu_testcase_level_adjust

Merge pull request !35316 from LLLRT/master

tests/st/data_transfer/test_tdt_data_transfer_enable_rdr.py

@@ -44,7 +44,7 @@ def test_train_with_Ascend():
     test_train("Ascend")
 
 @security_off_wrap
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_train_with_GPU():

tests/st/export_and_load/test_lite_mindir.py

@@ -29,7 +29,7 @@ from tests.models.official.cv.mobilenetv2.src.mobilenetV2 import MobileNetV2Back
 context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
 ckpt_path = '/home/workspace/mindspore_dataset/checkpoint/mobilenetv2/mobilenetv2_gpu.ckpt'
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_export_mobilenetv2_gpu_mindir():

tests/st/networks/test_gpu_alexnet.py

@@ -68,7 +68,7 @@ class AlexNet(nn.Cell):
         return x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_trainTensor(num_classes=10, epoch=15, batch_size=32):

tests/st/networks/test_gpu_lenet.py

@@ -127,7 +127,7 @@ def multisteplr(total_steps, gap, base_lr=0.9, gamma=0.1, dtype=mstype.float32):
     return Tensor(np.array(lr), dtype)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_train_lenet():

tests/st/networks/test_gpu_lenet_enable_rdr.py

@@ -31,7 +31,7 @@ def test_train_and_eval():
         test_train_and_eval_lenet()
 
 @security_off_wrap
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_train_with_GPU():

tests/st/networks/test_gpu_lstm.py

@@ -105,7 +105,7 @@ class SentimentNet(nn.Cell):
 batch_size = 64
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_LSTM():

tests/st/networks/test_gpu_resnet.py

@@ -328,7 +328,7 @@ def resnet50(num_classes):
     return ResNet(ResidualBlock, [3, 4, 6, 3], num_classes)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_trainTensor(num_classes=10, epoch=8, batch_size=1):

tests/st/numpy_native/test_array_ops.py

@@ -1252,7 +1252,7 @@ def test_select():
     match_res(mnp.select, onp.select, condlist, choicelist, default=10)
 
 
-@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_logic_ops.py

@@ -274,7 +274,7 @@ def test_isscalar():
     assert mnp.isscalar('numpy') == onp.isscalar('numpy')
 
 
-@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

@@ -1733,7 +1733,7 @@ def onp_convolve(mode):
     return a, b, c, d, e
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_convolve():
@@ -2659,7 +2659,7 @@ def onp_correlate(a, v):
     return a, b, c, d
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_correlate():

tests/st/ops/ascend/test_aicpu_ops/test_tensor_copy_slices.py

@@ -75,7 +75,7 @@ def test_tensor_copy_slices():
     test_tensor_copy_slices_net_many_dtype((10, 10, 10), (5, 10), (9, 5,), (10, 10,), (1, 1,), support_dtype)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_tensor_copy_slices_bprop():
@@ -105,14 +105,14 @@ def test_tensor_copy_slices_ascend_pynative():
     context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
     test_tensor_copy_slices()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_tensor_copy_slices_gpu_graph():
     context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
     test_tensor_copy_slices()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_tensor_copy_slices_gpu_pynative():

tests/st/ops/gpu/test_acos_grad_grad_op.py

@@ -45,7 +45,7 @@ class Grad(nn.Cell):
         return self.grad(self.network)(x, grad, dout)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("fp_type, error_magnitude, mode", [

tests/st/ops/gpu/test_acos_grad_op.py

@@ -21,7 +21,7 @@ from mindspore import Tensor
 import mindspore.ops.operations._grad_ops as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_acosgrad_fp32():
@@ -33,7 +33,7 @@ def test_acosgrad_fp32():
     diff = output_ms.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_acosgrad_fp16():

tests/st/ops/gpu/test_acos_op.py

@@ -21,7 +21,7 @@ from mindspore import Tensor
 from mindspore.ops import operations as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_acos_fp32():
@@ -30,7 +30,7 @@ def test_acos_fp32():
     output_np = np.arccos(x_np)
     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_acos_fp16():

tests/st/ops/gpu/test_acosh_grad_grad_op.py

@@ -72,14 +72,14 @@ def acosh_grad_grad_base(dtype, loss):
     assert np.allclose(dgrad_ms.asnumpy(), dgrad_np, loss, loss)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_acosh_grad_grad_float16():
     acosh_grad_grad_base(np.float16, 2e-3)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_acosh_grad_grad_float32():

tests/st/ops/gpu/test_acosh_grad_op.py

@@ -22,7 +22,7 @@ import mindspore.ops.operations._grad_ops as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 np.random.seed(1)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_acoshgrad_fp32():
@@ -32,7 +32,7 @@ def test_acoshgrad_fp32():
     output_np = dout_np / np.sinh(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_acoshgrad_fp16():

tests/st/ops/gpu/test_acosh_op.py

@@ -22,7 +22,7 @@ from mindspore.ops import operations as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 np.random.seed(1)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_acosh_fp32():
@@ -31,7 +31,7 @@ def test_acosh_fp32():
     output_np = np.arccosh(x_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_acosh_fp16():

tests/st/ops/gpu/test_adagrad_op.py

@@ -40,7 +40,7 @@ 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_adagrad():

tests/st/ops/gpu/test_adam_fusion.py

@@ -65,7 +65,7 @@ class Net(nn.Cell):
         return next_v
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_adam_fusion():

tests/st/ops/gpu/test_adam_op.py

@@ -41,7 +41,7 @@ class NetAdam(nn.Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_adam():

tests/st/ops/gpu/test_adaptive_avg_pool2d_op.py

@@ -47,7 +47,7 @@ class GradNet(nn.Cell):
         return self.adaptive_avg_pool2d_grad(x, dy)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_normal():
@@ -58,7 +58,7 @@ 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_single():
@@ -69,7 +69,7 @@ def test_net_single():
     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_none():
@@ -80,7 +80,7 @@ def test_net_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_value():

tests/st/ops/gpu/test_add_op.py

@@ -129,7 +129,7 @@ def add(nptype):
 
 
 @pytest.mark.skip(reason='0 in shape is not support')
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_float64():
@@ -137,7 +137,7 @@ def test_add_float64():
 
 
 @pytest.mark.skip(reason='0 in shape is not support')
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_float32():

tests/st/ops/gpu/test_addn_op.py

@@ -33,7 +33,7 @@ class Net(nn.Cell):
         return self.add((x, y, z))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net():
@@ -56,7 +56,7 @@ def test_net():
     assert (output.asnumpy() == expect_result).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_float64():
@@ -95,7 +95,7 @@ def test_net_float64():
     assert (output.asnumpy() == expect_result).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_int64():

tests/st/ops/gpu/test_apply_gradient_descent_op.py

@@ -32,7 +32,7 @@ class Net(nn.Cell):
         return self.apply_gradient_descent(self.var, alpha, delta)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_gradient_descent_float32():
@@ -59,7 +59,7 @@ def test_apply_gradient_descent_float32():
     np.testing.assert_almost_equal(net.var.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_apply_gradient_descent_float16():

tests/st/ops/gpu/test_argmax_op.py

@@ -34,7 +34,7 @@ class NetArgmax(nn.Cell):
         return self.argmax(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmax_1d():
@@ -48,7 +48,7 @@ def test_argmax_1d():
         assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmax_2d():

tests/st/ops/gpu/test_argmaxwithvalue_op.py

@@ -101,21 +101,21 @@ def argmaxwithvalue_3d(data_type, shape_x):
     assert (output[1].asnumpy() == expect2).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmaxwithvalue_base_float32():
     argmaxwithvalue_base(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmaxwithvalue_base_float16():
     argmaxwithvalue_base(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmaxwithvalue_3d_float32():
@@ -126,7 +126,7 @@ def test_argmaxwithvalue_3d_float32():
     argmaxwithvalue_3d(np.float32, shape_x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmaxwithvalue_3d_float16():
@@ -135,7 +135,7 @@ def test_argmaxwithvalue_3d_float16():
     argmaxwithvalue_3d(np.float16, shape_x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argmaxwithvalue_3d_big_float32():

tests/st/ops/gpu/test_argminwithvalue_op.py

@@ -101,21 +101,21 @@ def argminwithvalue_3d(data_type, shape_x):
     assert (output[1].asnumpy() == expect2).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argminwithvalue_base_float32():
     argminwithvalue_base(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argminwithvalue_base_float16():
     argminwithvalue_base(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argminwithvalue_3d_float32():
@@ -126,7 +126,7 @@ def test_argminwithvalue_3d_float32():
     argminwithvalue_3d(np.float32, shape_x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argminwithvalue_3d_float16():
@@ -135,7 +135,7 @@ def test_argminwithvalue_3d_float16():
     argminwithvalue_3d(np.float16, shape_x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_argminwithvalue_3d_big_float32():

tests/st/ops/gpu/test_asin_grad_grad_op.py

@@ -45,7 +45,7 @@ class Grad(nn.Cell):
         return self.grad(self.network)(x, grad, dout)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize("fp_type, error_magnitude, mode", [

tests/st/ops/gpu/test_asin_grad_op.py

@@ -21,7 +21,7 @@ from mindspore import Tensor
 import mindspore.ops.operations._grad_ops as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asingrad_fp32():
@@ -33,7 +33,7 @@ def test_asingrad_fp32():
     diff = output_ms.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asingrad_fp16():

tests/st/ops/gpu/test_asin_op.py

@@ -21,7 +21,7 @@ from mindspore import Tensor
 from mindspore.ops import operations as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asin_fp32():
@@ -30,7 +30,7 @@ def test_asin_fp32():
     output_np = np.arcsin(x_np)
     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_asin_fp16():

tests/st/ops/gpu/test_asinh_grad_grad_op.py

@@ -72,14 +72,14 @@ def asinh_grad_grad_base(dtype, loss):
     assert np.allclose(dgrad_ms.asnumpy(), dgrad_np, loss, loss)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asinh_grad_grad_float16():
     asinh_grad_grad_base(np.float16, 1e-3)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asinh_grad_grad_float32():

tests/st/ops/gpu/test_asinh_grad_op.py

@@ -22,7 +22,7 @@ import mindspore.ops.operations._grad_ops as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 np.random.seed(1)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asinhgrad_fp32():

tests/st/ops/gpu/test_asinh_op.py

@@ -22,7 +22,7 @@ from mindspore.ops import operations as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 np.random.seed(1)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_asinh_fp32():
@@ -31,7 +31,7 @@ def test_asinh_fp32():
     output_np = np.arcsinh(x_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_asinh_fp16():

tests/st/ops/gpu/test_assign_add_op.py

@@ -33,7 +33,7 @@ class AssignAdd(nn.Cell):
         return res
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_assign_add():

tests/st/ops/gpu/test_assign_op.py

@@ -36,7 +36,7 @@ x = np.array([[1.2, 1], [1, 0]]).astype(np.float32)
 value = np.array([[1, 2], [3, 4.0]]).astype(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_assign():
@@ -54,7 +54,7 @@ def test_assign():
     assert np.all(-diff2 < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_assign_float64():

tests/st/ops/gpu/test_atan_grad_grad_op.py

@@ -73,14 +73,14 @@ def atan_grad_grad_base(dtype, loss):
     assert np.allclose(dgrad_ms.asnumpy(), dgrad_np, loss, loss)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atan_grad_grad_float16():
     atan_grad_grad_base(np.float16, 1e-3)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atan_grad_grad_float32():

tests/st/ops/gpu/test_atan_grad_op.py

@@ -22,7 +22,7 @@ import mindspore.ops.operations._grad_ops as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 np.random.seed(1)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atangrad_fp32():
@@ -32,7 +32,7 @@ def test_atangrad_fp32():
     output_np = dout_np / (1 + np.square(x_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_atangrad_fp16():

tests/st/ops/gpu/test_atan_op.py

@@ -22,7 +22,7 @@ from mindspore.ops import operations as P
 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
 np.random.seed(1)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_atan_fp32():
@@ -31,7 +31,7 @@ def test_atan_fp32():
     output_np = np.arctan(x_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_atan_fp16():

tests/st/ops/gpu/test_batch_matmul.py

@@ -32,7 +32,7 @@ class BatchMatMulNet(nn.Cell):
     def construct(self, x, y):
         return self.batch_matmul(x, y)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_4d():
@@ -54,7 +54,7 @@ def test_4d():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_4d_float64():
@@ -76,7 +76,7 @@ def test_4d_float64():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_4d_transpose_a():
@@ -98,7 +98,7 @@ def test_4d_transpose_a():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_4d_transpose_b():
@@ -120,7 +120,7 @@ def test_4d_transpose_b():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_4d_transpose_ab():
@@ -142,7 +142,7 @@ def test_4d_transpose_ab():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_4D_fp16():
@@ -176,7 +176,7 @@ class BatchMatMul_d(nn.Cell):
         return self.batch_matmul(x, y)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchmatmul_dynamic():

tests/st/ops/gpu/test_batchnorm_fold2_op.py

@@ -52,7 +52,7 @@ class Net_gnd(nn.Cell):
         return out
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnrom_fold2():

tests/st/ops/gpu/test_batchnorm_fold_grad_op.py

@@ -43,7 +43,7 @@ def np_result(d_batch_mean, d_batch_std, x, batch_mean, batch_std):
     return dx
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_fold_grad1():
@@ -61,7 +61,7 @@ def test_batchnorm_fold_grad1():
     assert np.allclose(dx.asnumpy(), expect, rtol=1.e-7, atol=1.e-7)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_fold_grad2():
@@ -79,7 +79,7 @@ def test_batchnorm_fold_grad2():
     assert np.allclose(dx.asnumpy(), expect, rtol=1.e-7, atol=1.e-7)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_fold_grad_freeze():

tests/st/ops/gpu/test_batchnorm_fold_op.py

@@ -52,7 +52,7 @@ def np_result(x, mean, var, momentum, epsilon):
     return np_mean, np_var, mean_update, var_update, delay_mean, delay_std
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_fold():
@@ -77,7 +77,7 @@ def test_batchnorm_fold():
     assert np.allclose(delay_std.asnumpy(), expect6, rtol=1.e-7, atol=1.e-5)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_fold2():
@@ -100,7 +100,7 @@ def test_batchnorm_fold2():
     assert np.allclose(delay_std.asnumpy(), expect6, rtol=1.e-7, atol=1.e-5)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_batchnorm_fold_freeze():

tests/st/ops/gpu/test_batchnorm_op.py

@@ -47,7 +47,7 @@ class Grad(Cell):
         return gout
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_train_forward():
@@ -101,7 +101,7 @@ def test_train_forward():
     output = bn_net(Tensor(x))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_train_backward():
@@ -137,7 +137,7 @@ def test_train_backward():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_train_stats_false_forward():
@@ -181,7 +181,7 @@ def test_train_stats_false_forward():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_infer_backward():
@@ -229,7 +229,7 @@ class GradByListNet(Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_1d_train():
@@ -298,7 +298,7 @@ def test_1d_train():
         assert np.allclose(bn_net.bn1.moving_variance.asnumpy(), data[6], atol=1.0e-4)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_1d_eval():

tests/st/ops/gpu/test_bce_with_logits_loss.py

@@ -32,7 +32,7 @@ class Net(nn.Cell):
         return self.loss(predict, target, weight, pos_weight)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_reduction_none_testcases():
@@ -70,7 +70,7 @@ def test_reduction_none_testcases():
     np.testing.assert_almost_equal(expected, output.asnumpy(), decimal=3)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_reduction_mean_testcases():

tests/st/ops/gpu/test_binary_cross_entropy_op.py

@@ -34,7 +34,7 @@ class Net(nn.Cell):
         return self.BinaryCrossEntropy(x, y, weight)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_binary_cross_entropy_loss():
@@ -73,7 +73,7 @@ class Grad(nn.Cell):
         return gout
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_binary_cross_entropy_loss_grad():

tests/st/ops/gpu/test_boundingbox_decode_op.py

@@ -32,7 +32,7 @@ class NetBoundingBoxDecode(nn.Cell):
     def construct(self, anchor, groundtruth):
         return self.decode(anchor, groundtruth)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_boundingbox_decode():

tests/st/ops/gpu/test_boundingbox_encode_op.py

@@ -53,7 +53,7 @@ def bbox2delta(proposals, gt, means, stds):
 
     return deltas
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_boundingbox_encode():

tests/st/ops/gpu/test_broadcast_op.py

@@ -21,7 +21,7 @@ from mindspore.common.tensor import Tensor
 from mindspore.ops import operations as P
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_nobroadcast():
@@ -92,7 +92,7 @@ def test_nobroadcast():
     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_nobroadcast_fp16():
@@ -155,7 +155,7 @@ def test_nobroadcast_fp16():
     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():
@@ -226,7 +226,7 @@ def test_broadcast():
     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():
@@ -357,7 +357,7 @@ def test_broadcast_diff_dims_float64():
     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_fp16():
@@ -420,7 +420,7 @@ def test_broadcast_fp16():
     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_divnonan_int8():
@@ -440,7 +440,7 @@ def test_divnonan_int8():
     assert np.allclose(output_ms.asnumpy(), x2_np_zero)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_divnonan_uint8():

tests/st/ops/gpu/test_broadcast_to_ops.py

@@ -21,7 +21,7 @@ from mindspore.common.tensor import Tensor
 from mindspore.ops import operations as P
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_broadcast():
@@ -69,7 +69,7 @@ def test_broadcast():
     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_init():

tests/st/ops/gpu/test_cast_op.py

@@ -53,7 +53,7 @@ class NetDynamic(Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cast():
@@ -224,7 +224,7 @@ def test_cast9():
     type1 = output[1].asnumpy().dtype
     assert type1 == 'float16'
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cast10():
@@ -292,7 +292,7 @@ def test_cast13():
     type1 = output[1].asnumpy().dtype
     assert type1 == 'float16'
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cast14():
@@ -547,7 +547,7 @@ def test_cast28():
     type1 = output[1].asnumpy().dtype
     assert type1 == 'int16'
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cast29():
@@ -599,7 +599,7 @@ def test_cast31():
     assert type1 == 'uint32'
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cast32():

tests/st/ops/gpu/test_check_valid_op.py

@@ -47,13 +47,13 @@ def check_valid(nptype):
     output = boundingbox_decode(anchor_box, image_metas_box)
     assert np.array_equal(output.asnumpy(), expect)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_check_valid_float32():
     check_valid(np.float32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_check_valid_float16():

tests/st/ops/gpu/test_concatv2_op.py

@@ -51,13 +51,13 @@ def axis32(nptype):
                         [3., 6., 7.]]]).astype(nptype)
     assert (output.asnumpy() == expect).all()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis32_float64():
     axis32(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis32_float32():
@@ -112,13 +112,13 @@ def axis43(nptype):
                          [14., 15., 21., 22., 23.]]]]).astype(nptype)
     assert (output.asnumpy() == expect).all()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis43_float64():
     axis43(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis43_float32():
@@ -130,7 +130,7 @@ def test_axis43_float32():
 def test_axis43_int16():
     axis43(np.int16)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis43_uint8():
@@ -167,13 +167,13 @@ def axis21(nptype):
                        [2., 3., 3., 4., 5.]]).astype(nptype)
     assert (output.asnumpy() == expect).all()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis21_float64():
     axis21(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis21_float32():
@@ -185,7 +185,7 @@ def test_axis21_float32():
 def test_axis21_int16():
     axis21(np.int16)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_axis21_uint8():
@@ -225,13 +225,13 @@ def concat_3i(nptype):
     diff = output_ms.asnumpy() - output_np
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_concat_3i_float64():
     concat_3i(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_concat_3i_float32():
@@ -298,13 +298,13 @@ def concat_4i(nptype):
     diff = output_ms.asnumpy() - output_np
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_concat_4i_float64():
     concat_4i(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_concat_4i_float32():

tests/st/ops/gpu/test_conv2d_backprop_filter_op.py

@@ -47,7 +47,7 @@ class Conv2dFilter(nn.Cell):
         return self.conv_filter(out, x, self.get_shape(w))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv2d_backprop_filter():

tests/st/ops/gpu/test_conv2d_backprop_input_op.py

@@ -46,7 +46,7 @@ class Conv2dInput(nn.Cell):
         return self.conv_input(out, w, self.get_shape(x))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv2d_backprop_input():

tests/st/ops/gpu/test_conv2d_op.py

@@ -43,7 +43,7 @@ class NetConv2d(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_conv2d():
@@ -86,7 +86,7 @@ class NetConv(nn.Cell):
         return self.conv(self.x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv():
@@ -190,7 +190,7 @@ class NetConv2dDynamic(nn.Cell):
         return x_conv
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv2d_dynamic():
@@ -251,7 +251,7 @@ class NetConvNHWC(nn.Cell):
         return self.conv(self.x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_conv_NHWC():

tests/st/ops/gpu/test_conv3dtranspose_op.py

@@ -40,7 +40,7 @@ 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_conv3d_transpose():

tests/st/ops/gpu/test_correction_mul_grad_op.py

@@ -36,7 +36,7 @@ class Net(nn.Cell):
         return dx, d_batch_std
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_correction_mul_grad():

tests/st/ops/gpu/test_correction_mul_op.py

@@ -35,7 +35,7 @@ class Net(nn.Cell):
         return self.op(x, batch_var, moving_var)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_correction_mul():

tests/st/ops/gpu/test_cos_op.py

@@ -41,7 +41,7 @@ def test_cos_float16():
 def test_cos_float32():
     cos(np.float32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cos_float64():

tests/st/ops/gpu/test_crop_and_resize.py

@@ -190,7 +190,7 @@ def test_crop_and_resize_float16_nearest(datatype=np.float16):
     assert np.all(abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_crop_and_resize_float32_bilinear(datatype=np.float32):
@@ -239,7 +239,7 @@ def test_crop_and_resize_float32_bilinear(datatype=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_crop_and_resize_float64_nearest(datatype=np.float64):
@@ -284,7 +284,7 @@ def test_crop_and_resize_float64_nearest(datatype=np.float64):
     assert np.all(abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_crop_and_resize_int64_bilinearv2(datatype=np.int64):

tests/st/ops/gpu/test_ctcloss_op.py

@@ -47,7 +47,7 @@ class GradData(nn.Cell):
         return self.grad(self.network)(probs, indices, labels, input_lengths)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_ctcloss():

tests/st/ops/gpu/test_cudnn_inplace_fusion.py

@@ -47,7 +47,7 @@ class Conv2dBpropInputInplace(nn.Cell):
         return y
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_inplace_fusion1():

tests/st/ops/gpu/test_cumprod_op.py

@@ -126,7 +126,7 @@ def cum_prod(nptype):
     assert np.all(diff6 < error6)
     assert output[6].shape == expect6.shape
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cum_prod_uint8():
@@ -144,13 +144,13 @@ def test_cum_prod_int8():
 def test_cum_prod_int32():
     cum_prod(np.int32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cum_prod_float16():
     cum_prod(np.float16)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cum_prod_float32():

tests/st/ops/gpu/test_cumsum_op.py

@@ -132,7 +132,7 @@ def cum_sum(nptype):
 def test_cum_sum_uint8():
     cum_sum(np.uint8)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cum_sum_int8():
@@ -144,13 +144,13 @@ def test_cum_sum_int8():
 def test_cum_sum_int32():
     cum_sum(np.int32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cum_sum_float16():
     cum_sum(np.float16)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_cum_sum_float32():

tests/st/ops/gpu/test_dense_op.py

@@ -34,7 +34,7 @@ class BiasAdd(nn.Cell):
         return self.ba(x, b)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_biasadd():
@@ -98,7 +98,7 @@ class DenseNet(nn.Cell):
         return self.dense(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dx():
@@ -128,7 +128,7 @@ def test_dx():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dx_ND():
@@ -169,7 +169,7 @@ def test_dx_ND():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dw():
@@ -206,7 +206,7 @@ def test_dw():
     assert np.all(-diff < db_error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dw_ND():
@@ -259,7 +259,7 @@ class Grad(nn.Cell):
         return self.grad(self.network)(input_, bias, dy)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_biasadd_3d():
@@ -326,7 +326,7 @@ def test_biasadd_3d():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_biasadd_4d():
@@ -455,7 +455,7 @@ class BiasAddDynamic(nn.Cell):
         output = self.ba(x, b)
         return output
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_bias_add_dynamic_two_inputs():

tests/st/ops/gpu/test_depthtospace_op.py

@@ -75,13 +75,13 @@ def DepthToSpace_pynative(nptype, block_size=2, input_shape=(1, 12, 1, 1)):
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_depthtospace_graph_float32():
     DepthToSpace(np.float32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_depthtospace_graph_float16():
@@ -135,13 +135,13 @@ def test_depthtospace_graph_uint32():
 def test_depthtospace_graph_uint64():
     DepthToSpace(np.uint64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_depthtospace_pynative_float32():
     DepthToSpace_pynative(np.float32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_depthtospace_pynative_float16():

tests/st/ops/gpu/test_div_op.py

@@ -90,13 +90,13 @@ def div(nptype):
     assert np.all(diff4 < error4)
     assert output4.shape == expect4.shape
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_div_float64():
     div(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_div_float32():

tests/st/ops/gpu/test_dropout.py

@@ -30,7 +30,7 @@ class Net(nn.Cell):
         return self.drop(x_)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dropout():
@@ -67,7 +67,7 @@ class DropoutDynamic(nn.Cell):
         return self.drop(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dropout_dynamic():

tests/st/ops/gpu/test_dtype_op.py

@@ -116,14 +116,14 @@ def test_dtype_float16():
     dtype_with_testcase(ms.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dtype_float32():
     dtype_with_testcase(ms.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dtype_float64():
@@ -186,14 +186,14 @@ def test_dynamic_dtype_float16():
     dtype_dynamic_with_testcase(ms.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dynamic_dtype_float32():
     dtype_dynamic_with_testcase(ms.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dynamic_dtype_float64():

tests/st/ops/gpu/test_dynamic_shape_op.py

@@ -98,13 +98,13 @@ def dynamic_shape(np_type):
 def test_dynamic_shape_int32():
     dynamic_shape(np.int32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dynamic_shape_float16():
     dynamic_shape(np.float16)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_dynamic_shape_float32():

tests/st/ops/gpu/test_elu_grad_op.py

@@ -31,7 +31,7 @@ class NetEluGrad(nn.Cell):
         return self.eluGrad(dy, x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_elu_grad_fp16():
@@ -46,7 +46,7 @@ def test_elu_grad_fp16():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_elu_grad_fp32():

tests/st/ops/gpu/test_elu_op.py

@@ -30,7 +30,7 @@ class NetElu(nn.Cell):
         return self.elu(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_elu_fp16():
@@ -50,7 +50,7 @@ def test_elu_fp16():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_elu_fp32():

tests/st/ops/gpu/test_embedding_lookup_op.py

@@ -49,14 +49,14 @@ def embeddinglookup_testcase(nptype):
     np.testing.assert_almost_equal(expect, output.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_embeddinglookup_float32():
     embeddinglookup_testcase(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_embeddinglookup_float16():

tests/st/ops/gpu/test_equal_op.py

@@ -136,7 +136,7 @@ def test_equal():
         assert output.shape == expect[i].shape
         print('test [%d/%d] passed!' % (i, len(x)))
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_notequal():
@@ -182,7 +182,7 @@ def test_notequal():
         assert output.shape == expect[i].shape
         print('test [%d/%d] passed!' % (i, len(x)))
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_greaterqual():
@@ -233,7 +233,7 @@ def test_greaterqual():
         print('test [%d/%d] passed!' % (i, len(x)))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_equal_dynamic_shape():

tests/st/ops/gpu/test_equalcount_op.py

@@ -31,7 +31,7 @@ class NetEqualCount(nn.Cell):
         return self.equalcount(x, y)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_equalcount():

tests/st/ops/gpu/test_erf_op.py

@@ -34,7 +34,7 @@ class NetErf(nn.Cell):
         return self.erf(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_erf_fp32():
@@ -45,7 +45,7 @@ def test_erf_fp32():
     tol = 1e-6
     assert (np.abs(output.asnumpy() - expect) < tol).all()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_erf_fp16():

tests/st/ops/gpu/test_erfc_op.py

@@ -34,7 +34,7 @@ class NetErfc(nn.Cell):
         return self.erfc(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_erfc_fp32():
@@ -45,7 +45,7 @@ def test_erfc_fp32():
     tol = 1e-6
     assert (np.abs(output.asnumpy() - expect) < tol).all()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_erfc_fp16():

tests/st/ops/gpu/test_exp_op.py

@@ -31,7 +31,7 @@ class NetExp(nn.Cell):
         return self.exp(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_exp():

tests/st/ops/gpu/test_expand_dims.py

@@ -119,7 +119,7 @@ def test_net_float16():
     assert np.all(output.asnumpy() == np.expand_dims(x, -1))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_float32():
@@ -130,7 +130,7 @@ def test_net_float32():
     assert np.all(output.asnumpy() == np.expand_dims(x, -1))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_net_float64():

tests/st/ops/gpu/test_extract_image_patches_op.py

@@ -31,7 +31,7 @@ class Net(nn.Cell):
         return self.extractimagepatches(input_tensor)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_extract_image_patches_valid():
@@ -62,7 +62,7 @@ def test_extract_image_patches_valid():
     assert np.all(output.asnumpy() == expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_extract_image_patches_same():

tests/st/ops/gpu/test_fake_quant_perchannel.py

@@ -36,7 +36,7 @@ class Net(nn.Cell):
         return self.op(x, minq, maxq)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_perchannel1():
@@ -77,7 +77,7 @@ def test_fake_quant_perchannel2():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_perchannel3():
@@ -387,7 +387,7 @@ def test_fake_quant_perchannel15():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_perchannel16():
@@ -408,7 +408,7 @@ def test_fake_quant_perchannel16():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_perchannel17():
@@ -571,7 +571,7 @@ def test_fake_quant_perchannel23():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_perchannel24():
@@ -598,7 +598,7 @@ def test_fake_quant_perchannel24():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_perchannel25():

tests/st/ops/gpu/test_fake_quant_perchannel_grad.py

@@ -309,7 +309,7 @@ def test_fake_quant_grad11():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_grad12():
@@ -341,7 +341,7 @@ def test_fake_quant_grad12():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_grad13():

tests/st/ops/gpu/test_fake_quant_perlayer.py

@@ -42,7 +42,7 @@ class Net(nn.Cell):
         return self.fake_quant(x, minq, maxq)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant1():
@@ -346,7 +346,7 @@ def test_fake_quant15():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant16():
@@ -366,7 +366,7 @@ def test_fake_quant16():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant17():

tests/st/ops/gpu/test_fake_quant_perlayer_grad.py

@@ -179,7 +179,7 @@ def test_fake_quant_grad7():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_grad8():
@@ -200,7 +200,7 @@ def test_fake_quant_grad8():
     assert np.all(np.abs(diff) < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_fake_quant_grad9():

tests/st/ops/gpu/test_flatten_grad_op.py

@@ -32,7 +32,7 @@ class NetFlattenGrad(nn.Cell):
         return self.flattengrad(x, self.type)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_flatten_grad():

tests/st/ops/gpu/test_flatten_op.py

@@ -76,7 +76,7 @@ class NetLastFlatten(nn.Cell):
         return x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_flatten():
@@ -93,7 +93,7 @@ def test_flatten():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_all_flatten():
@@ -127,7 +127,7 @@ def test_first_flatten():
     assert (output.asnumpy() == expect).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_last_flatten():

tests/st/ops/gpu/test_float_status_op.py

@@ -64,7 +64,7 @@ x2 = np.array([[np.inf, 1, 88.0, 0]]).astype(np.float32)
 x3 = np.array([[1, 2], [3, 4], [5.0, 88.0]]).astype(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype', [np.float16, np.float32, np.float64])
@@ -88,7 +88,7 @@ def test_status(dtype):
     assert output3.asnumpy()[0] == expect3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype', [np.float16, np.float32, np.float64])
@@ -112,7 +112,7 @@ def test_nan(dtype):
     assert (output3.asnumpy() == expect3).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype', [np.float16, np.float32, np.float64])
@@ -136,7 +136,7 @@ def test_inf(dtype):
     assert (output3.asnumpy() == expect3).all()
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 @pytest.mark.parametrize('dtype', [np.float16, np.float32, np.float64])

tests/st/ops/gpu/test_floordiv_op.py

@@ -29,7 +29,7 @@ class NetFloorDiv(nn.Cell):
     def construct(self, x, y):
         return self.floordiv(x, y)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_floor_div():

tests/st/ops/gpu/test_ftrl_op.py

@@ -41,7 +41,7 @@ class NetFtrl(nn.Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_ftrl():

tests/st/ops/gpu/test_gatherV2_op.py

@@ -32,7 +32,7 @@ class GatherNet(nn.Cell):
         return self.gather(x, indices, 1)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather0():
@@ -856,7 +856,7 @@ class GatherNet1(nn.Cell):
         return self.gather(x, indices, -1)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather1():
@@ -910,7 +910,7 @@ class GatherNet2(nn.Cell):
         return self.gather(x, indices, 0)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather2():
@@ -959,7 +959,7 @@ class GatherNetDynamic(nn.Cell):
         return self.gather(x, indices, self.axis)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gatherV2_dyn_ab():
@@ -990,7 +990,7 @@ def test_gatherV2_dyn_ab():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gatherV2_dyn_a():
@@ -1066,7 +1066,7 @@ def test_gatherV2_dyn_a():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gatherV2_dyn_b():
@@ -1137,7 +1137,7 @@ def test_gatherV2_dyn_b():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather1_float64():
@@ -1182,7 +1182,7 @@ def test_gather1_float64():
     assert np.all(-diff < error)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather1_int32():

tests/st/ops/gpu/test_gather_grad_op.py

@@ -33,7 +33,7 @@ class GatherDNet(nn.Cell):
     def construct(self, x, index):
         return self.gather_d(x, self.dim, index)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_graph_int32_fp32():
@@ -52,7 +52,7 @@ def test_gather_grad_graph_int32_fp32():
     diff = output[0].asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_graph_int64_fp32():
@@ -71,7 +71,7 @@ def test_gather_grad_graph_int64_fp32():
     diff = output[0].asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_graph_int32_fp16():
@@ -90,7 +90,7 @@ def test_gather_grad_graph_int32_fp16():
     diff = output[0].asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_graph_int64_fp16():
@@ -109,7 +109,7 @@ def test_gather_grad_graph_int64_fp16():
     diff = output[0].asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_pynative_int32_fp32():
@@ -126,7 +126,7 @@ def test_gather_grad_pynative_int32_fp32():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_pynative_int64_fp32():
@@ -143,7 +143,7 @@ def test_gather_grad_pynative_int64_fp32():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_pynative_int32_fp16():
@@ -160,7 +160,7 @@ def test_gather_grad_pynative_int32_fp16():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_grad_pynative_int64_fp16():

tests/st/ops/gpu/test_gather_op.py

@@ -32,7 +32,7 @@ class GatherNet(nn.Cell):
     def construct(self, x, index):
         return self.gather(x, self.dim, index)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_pynative_fp32_int32():
@@ -46,7 +46,7 @@ def test_gather_pynative_fp32_int32():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_pynative_fp32_int64():
@@ -60,7 +60,7 @@ def test_gather_pynative_fp32_int64():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_pynative_fp16_int32():
@@ -74,7 +74,7 @@ def test_gather_pynative_fp16_int32():
     diff = output.asnumpy() - expect
     assert np.all(diff < error)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gather_pynative_fp16_int64():

tests/st/ops/gpu/test_gathernd_op.py

@@ -40,7 +40,7 @@ def gathernd0(nptype):
 
     assert np.array_equal(output.asnumpy(), expect)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gathernd0_float64():
@@ -116,13 +116,13 @@ def gathernd1(nptype):
 
     assert np.array_equal(output.asnumpy(), expect)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gathernd1_float64():
     gathernd1(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gathernd1_float32():
@@ -175,13 +175,13 @@ def gathernd2(nptype):
 
     assert np.array_equal(output.asnumpy(), expect)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gathernd2_float64():
     gathernd2(np.float64)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gathernd2_float32():
@@ -225,7 +225,7 @@ def test_gathernd_bool():
 
     assert np.array_equal(output.asnumpy(), expect)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gathernd_indices_int64():

tests/st/ops/gpu/test_gelu_grad_op.py

@@ -45,7 +45,7 @@ class Grad(nn.Cell):
         return gout
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gelugrad():
@@ -62,7 +62,7 @@ def test_gelugrad():
               0.34266686, 0.57757664, 0.04707306, 0.51536125]
     assert np.allclose(output[0].asnumpy(), expect)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gelugrad_fp16():

tests/st/ops/gpu/test_gelu_op.py

@@ -37,7 +37,7 @@ def GeluCompute(x):
     return 0.5 * x * (1.0 + np.tanh(np.sqrt(2 / np.pi) * (x + 0.044715 * x * x * x)))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gelu_1d():
@@ -51,7 +51,7 @@ def test_gelu_1d():
     assert np.allclose(y_np, y_ms.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gelu_2d():
@@ -65,7 +65,7 @@ def test_gelu_2d():
     assert np.allclose(y_np, y_ms.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gelu_4d():
@@ -79,7 +79,7 @@ def test_gelu_4d():
     assert np.allclose(y_np, y_ms.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gelu_neg():
@@ -92,7 +92,7 @@ def test_gelu_neg():
 
     assert np.allclose(y_np, y_ms.asnumpy())
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gelu_4d_fp16():

tests/st/ops/gpu/test_gpu_convert_to_dynamic_shape_op.py

@@ -22,7 +22,7 @@ import mindspore.nn as nn
 import mindspore.context as context
 
 # test to make sure this op actually generates a dynamically shaped output
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gpu_convert_to_dyanamic_shape_confirm_dynamic():
@@ -103,13 +103,13 @@ def test_gpu_convert_to_dynamic_shape_bool():
 def test_gpu_convert_to_dynamic_shape_float16():
     gpu_convert_to_dynamic_shape_float(np.float16)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gpu_convert_to_dynamic_shape_float32():
     gpu_convert_to_dynamic_shape_float(np.float32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_gpu_convert_to_dynamic_shape_float64():

tests/st/ops/gpu/test_hsigmoid_op.py

@@ -90,21 +90,21 @@ def generate_dynamic_testcase(nptype):
     np.testing.assert_almost_equal(output.asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_hsigmoid_dynamic_float32():
     generate_dynamic_testcase(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_hsigmoid_float32():
     generate_testcases(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_hsigmoid_float16():

tests/st/ops/gpu/test_hswish_op.py

@@ -71,7 +71,7 @@ def generate_test_cases(np_type, mode):
     judge_result_correct(output[0].asnumpy(), expect)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_hswish_forward_and_backward():

tests/st/ops/gpu/test_identity_op.py

@@ -48,14 +48,14 @@ def generate_testcases(nptype):
     assert id(input_tensor) != id(output)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_identity_float64():
     generate_testcases(np.float64)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_identity_float32():

tests/st/ops/gpu/test_in_top_k.py

@@ -100,19 +100,19 @@ def in_top_k(nptype):
     expected_output = np.array([True, True, True])
     np.testing.assert_array_equal(output.asnumpy(), expected_output)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_in_top_k_float16():
     in_top_k(np.float16)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_in_top_k_float32():
     in_top_k(np.float32)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_in_top_k_invalid_input():