move useless testcases from level0 to level1

tests/st/auto_monad/test_auto_monad.py

@@ -1042,7 +1042,7 @@ def test_variable_from_outer_graph():
     np.testing.assert_array_equal(out.asnumpy(), expect.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -1079,7 +1079,7 @@ def test_ctrl_while_by_while_and_if_in_first_while():
     net(input_me_a)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/auto_monad/test_auto_monad_gpu.py

@@ -226,7 +226,7 @@ class SideEffectTwoAssignTwoAddnDependencyNet(Cell):
         return grad_out
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_ctrl_while_by_while_and_if_in_first_while():
@@ -262,7 +262,7 @@ def test_ctrl_while_by_while_and_if_in_first_while():
     net(input_me_a)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_ctrl_while_by_while_and_while_in_first_while():

tests/st/auto_monad/test_auto_monad_mindtester.py

@@ -507,7 +507,7 @@ class SideEffectControlFlowAssignDependTwoIfNet(Cell):
         return grad_out
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/auto_monad/test_auto_monad_momentum_loss.py

@@ -61,7 +61,7 @@ class MSELoss(Cell):
         return self.reduce_mean(self.square(diff), get_axis(diff))
 
 
-@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/test_cont_grad.py

@@ -1484,7 +1484,7 @@ def test_if_by_if_forward_all_const_branch():
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
@@ -1520,7 +1520,7 @@ def test_if_const_grad():
     net(a, b)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
@@ -1560,7 +1560,7 @@ def test_if_by_if_const_grad():
     net(a, b)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
@@ -1594,7 +1594,7 @@ def test_while_const_grad():
     net(a, b)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard

tests/st/fusion/test_tbe_eltwise_fusion_1.py

@@ -36,7 +36,7 @@ class Net(nn.Cell):
         return x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/fusion/test_tbe_eltwise_fusion_2.py

@@ -42,7 +42,7 @@ class Net(nn.Cell):
         return x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/fusion/test_tbe_reduce_eltwise_fusion.py

@@ -42,7 +42,7 @@ class Net(nn.Cell):
         return x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/host_device/test_host_device_lenet.py

@@ -78,7 +78,7 @@ def train(net, data, label):
     assert np.all(diff < 1.e-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/networks/test_cpu_lenet.py

@@ -71,7 +71,7 @@ def train(net, data, label):
     assert res
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_lenet():

tests/st/networks/test_gpu_lenet.py

@@ -187,7 +187,7 @@ def create_dataset(data_path, batch_size=32, repeat_size=1,
     return mnist_ds
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_train_and_eval_lenet():

tests/st/ops/cpu/test_cpu_type.py

@@ -57,7 +57,7 @@ class Net2(nn.Cell):
         return self.bias_add1(self.bias_add(x, b), c)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_bias_add2():

tests/st/ops/cpu/test_dropout_op.py

@@ -33,7 +33,7 @@ class Net(nn.Cell):
         return self.dropout(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_net():
@@ -54,7 +54,7 @@ class Net1(nn.Cell):
         return self.dropout(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_net1():
@@ -75,7 +75,7 @@ class Net2(nn.Cell):
         return self.dropout(x)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_net2():

tests/st/ops/cpu/test_gather_d_grad_op.py

@@ -46,7 +46,7 @@ class NetGatherDGrad(nn.Cell):
         return self.grad(self.network)(inputx, index, output_grad)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_gatherd_grad_fp32():
@@ -64,7 +64,7 @@ def test_gatherd_grad_fp32():
     print(output_grad.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_gatherd_grad_fp16():
@@ -82,7 +82,7 @@ def test_gatherd_grad_fp16():
     print(output_grad.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_gatherd_grad_int32():

tests/st/ops/cpu/test_lstm_op.py

@@ -254,7 +254,7 @@ class MultiLayerBiLstmNet(nn.Cell):
         return self.lstm(self.x, (self.h, self.c))
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_multi_layer_bilstm():
@@ -345,7 +345,7 @@ class Net(nn.Cell):
         return self.lstm(self.x, (self.h, self.c))[0]
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_grad():

tests/st/ops/cpu/test_minimum_grad_op.py

@@ -63,7 +63,7 @@ def gen_data(inputA_np, inputB_np, grad_=None):
     return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_min_tensor_grad_4d():

tests/st/ops/cpu/test_momentum_op.py

@@ -42,7 +42,7 @@ class MomentumNet(nn.Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_momentum():

tests/st/ops/cpu/test_tile_op.py

@@ -35,7 +35,7 @@ class Net(nn.Cell):
 arr_x = np.array([[0], [1], [2], [3]]).astype(np.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_net():
@@ -48,7 +48,7 @@ def test_net():
 arr_x = np.array([[0], [1], [2], [3]]).astype(np.float64)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_net_float64():
@@ -61,7 +61,7 @@ def test_net_float64():
 arr_x = np.array([[0], [1], [2], [3]]).astype(np.bool_)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_net_bool():

tests/st/ops/gpu/test_error_on_dynamic_shape_input_op.py

@@ -46,7 +46,7 @@ def test_error_on_dynamic_shape_input_is_dynamic():
         error_on_dynamic_shape_input.infer_shape([-1, -1, -1])
     assert "Input is dynamically shaped" in str(info.value)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_error_on_dynamic_shape_input_not_dynamic():

tests/st/ops/gpu/test_momentum_op.py

@@ -42,7 +42,7 @@ class NetMomentum(nn.Cell):
         return output
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_momentum():

tests/st/ops/gpu/test_print_op.py

@@ -118,84 +118,84 @@ def test_print_multiple_types():
     net(x, y, z)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_bool():
     print_testcase(np.bool)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_int8():
     print_testcase(np.int8)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_int16():
     print_testcase(np.int16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_int32():
     print_testcase(np.int32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_int64():
     print_testcase(np.int64)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_uint8():
     print_testcase(np.uint8)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_uint16():
     print_testcase(np.uint16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_uint32():
     print_testcase(np.uint32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_uint64():
     print_testcase(np.uint64)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_float16():
     print_testcase(np.float16)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_float32():
     print_testcase(np.float32)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_print_string():

tests/st/probability/distribution/test_categorical_gpu.py

@@ -52,7 +52,7 @@ class CategoricalProb(nn.Cell):
 
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_probability_categorical_prob_cdf_probs_none():

tests/st/probability/distribution/test_cauchy_pynative.py

@@ -36,7 +36,7 @@ class CauchyMean(nn.Cell):
 
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
 def test_probability_cauchy_mean_loc_scale_rand_2_ndarray():
@@ -61,7 +61,7 @@ class CauchyProb(nn.Cell):
         return out1, out2, out3, out4, out5, out6
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
 def test_probability_cauchy_prob_cdf_loc_scale_rand_4_ndarray():

tests/st/pynative/loss_scale/test_loss_scale.py

@@ -193,7 +193,7 @@ def test_loss_scale_fp16_lr_overflow_set_sense_scale():
     assert output_1[0].asnumpy() == output_2[0].asnumpy()
     assert output_1[1].asnumpy() == output_2[1].asnumpy() == True
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/pynative/test_graph_param_transform.py

@@ -179,7 +179,7 @@ def test_parser_switch_layer_inputs_tuple():
     assert np.allclose(goodout.asnumpy(), netout.asnumpy(), 0, 0)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard