adjust ascend st from level0 to level1

tests/st/auto_monad/test_auto_monad_mindtester.py

@@ -123,7 +123,7 @@ class ControlGraphSupportNotEqual(Cell):
         return out, out2, out3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -143,7 +143,7 @@ def test_ctrl_if_while_graph_support_not_equal_true():
     allclose_nparray(out3, out_me[2].asnumpy(), 0.0001, 0.0001)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -186,7 +186,7 @@ class ControlBprop(Cell):
         return x*2, y*3, z, input_data*5.1
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -237,7 +237,7 @@ class InlineBpropTwoInput1(Cell):
         return grads[0]*2, grads[1]*2
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -315,7 +315,7 @@ class SideEffectMemoryCellAddnNet(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
@@ -347,7 +347,7 @@ class SideEffectIOCellAddnNet(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
@@ -379,7 +379,7 @@ class SideEffectReturnParameterNet(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
@@ -462,7 +462,7 @@ class SideEffectPrintInHighOrdeAddnNet(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
@@ -540,7 +540,7 @@ class SideEffectTwoAddnSwitchNet(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
@@ -582,7 +582,7 @@ class SideEffectGradIfNet(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
@@ -639,7 +639,7 @@ def test_highgrad_one_input_sec_grad():
     assert (dxdx.asnumpy() == np.array([5, 5]).astype(np.float32)).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/auto_monad/test_effect_ops.py

@@ -39,7 +39,7 @@ class AssignAddNet(nn.Cell):
         return self.para
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -63,7 +63,7 @@ class AssignSubNet(nn.Cell):
         return self.para
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -87,7 +87,7 @@ class ScatterAddNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -112,7 +112,7 @@ class ScatterSubNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -137,7 +137,7 @@ class ScatterMulNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -162,7 +162,7 @@ class ScatterDivNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -187,7 +187,7 @@ class ScatterMaxNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -212,7 +212,7 @@ class ScatterMinNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -237,7 +237,7 @@ class ScatterUpdateNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -262,7 +262,7 @@ class ScatterNdAddNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -287,7 +287,7 @@ class ScatterNdSubNet(nn.Cell):
         return self.input_x
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -380,7 +380,7 @@ def train_summary_record(test_writer, steps):
     return out_me_dict
 
 
-@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_effect_optimizer.py

@@ -74,7 +74,7 @@ class ApplyAdaMaxNet(nn.Cell):
         return self.var, self.m, self.v
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -109,7 +109,7 @@ class ApplyAdadeltaNet(nn.Cell):
         return self.var, self.accum, self.accum_update
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -140,7 +140,7 @@ class ApplyAdagrad(nn.Cell):
         return self.var, self.accum
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -168,7 +168,7 @@ class ApplyAdagradV2Net(nn.Cell):
         return self.var, self.accum
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -197,7 +197,7 @@ class ApplyAddSignNet(nn.Cell):
         return self.var, self.m
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -228,7 +228,7 @@ class ApplyCenteredRMSPropNet(nn.Cell):
         return self.var
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -295,7 +295,7 @@ class ApplyGradientDescentNet(nn.Cell):
         return self.var
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -382,7 +382,7 @@ class ApplyProximalAdagradNet(nn.Cell):
         return self.var, self.accum
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -411,7 +411,7 @@ class ApplyProximalGradientDescentNet(nn.Cell):
         return self.var
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -469,7 +469,7 @@ class FusedSparseAdamNet(nn.Cell):
         return self.var, self.m, self.v
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -607,7 +607,7 @@ class SparseApplyAdagradNet(nn.Cell):
         return self.var, self.accum
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -636,7 +636,7 @@ class SparseApplyAdagradV2Net(nn.Cell):
         return self.var, self.accum
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -759,7 +759,7 @@ class SGDNet(nn.Cell):
         return self.var
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -791,7 +791,7 @@ class ApplyProximalAdagradConstantNet(nn.Cell):
         return self.depend(self.const, optimizer)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -822,7 +822,7 @@ class MulSGDNet(nn.Cell):
         return 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_effect_random.py

@@ -149,7 +149,7 @@ class CompositePoissonNet(nn.Cell):
         return s1, s2, s3
 
 
-@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 @@ class StandardNormalNet(nn.Cell):
         return s1, s2, s3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -260,7 +260,7 @@ class GammaNet(nn.Cell):
         return s1, s2, s3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -289,7 +289,7 @@ class PoissonNet(nn.Cell):
         return s1, s2, s3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -317,7 +317,7 @@ class UniformIntNet(nn.Cell):
         return s1, s2, s3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -346,7 +346,7 @@ class UniformRealNet(nn.Cell):
         return s1, s2, s3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -423,7 +423,7 @@ class RandomCategoricalNet(nn.Cell):
         return s1, s2, s3
 
 
-@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

@@ -990,7 +990,7 @@ def test_if_by_if_return_inside_grad():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -1165,7 +1165,7 @@ def test_if_by_if_forward_control_inside_net():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -1207,7 +1207,7 @@ def test_if_by_if_forward_use_namespace():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -1253,7 +1253,7 @@ def test_if_by_if_forward_use_global_op():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -1286,7 +1286,7 @@ def test_for_with_if_by_if_forward():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -1322,7 +1322,7 @@ def test_for_with_if_by_if_forward_namespace():
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -1368,7 +1368,7 @@ def test_if_by_if_forward_const_branch_inner():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/explainer/explanation/_attribution/_backprop/test_gradcam.py

@@ -58,7 +58,7 @@ class TestGradCAM:
         self.net = SimpleAvgLinear()
         self.data = ms.Tensor(np.random.random(size=(1, 1, 4, 4)), ms.float32)
 
-    @pytest.mark.level0
+    @pytest.mark.level1
     @pytest.mark.platform_arm_ascend_training
     @pytest.mark.platform_x86_ascend_training
     @pytest.mark.env_onecard
@@ -83,7 +83,7 @@ class TestGradCAM:
                 res = aggregation(gap_grad * activation)
                 assert np.allclose(res.asnumpy(), attribution.asnumpy(), atol=1e-5, rtol=1e-3)
 
-    @pytest.mark.level0
+    @pytest.mark.level1
     @pytest.mark.platform_arm_ascend_training
     @pytest.mark.platform_x86_ascend_training
     @pytest.mark.env_onecard

tests/st/explainer/explanation/_attribution/_backprop/test_gradient.py

@@ -51,7 +51,7 @@ class TestGradient:
         self.relu = P.ReLU()
         self.abs_ = P.Abs()
 
-    @pytest.mark.level0
+    @pytest.mark.level1
     @pytest.mark.platform_arm_ascend_training
     @pytest.mark.platform_x86_ascend_training
     @pytest.mark.env_onecard

tests/st/mix_precision/test_mix_precision.py

@@ -73,7 +73,7 @@ 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.platform_x86_gpu_training

tests/st/model_zoo_tests/deeplabv3/test_DeeplabV3_voc2007.py

@@ -1,63 +1,63 @@
-# Copyright 2021 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 os
-import pytest
-
-from tests.st.model_zoo_tests import utils
-
-
-@pytest.mark.level0
-@pytest.mark.platform_x86_ascend_training
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.env_single
-def test_DeeplabV3_voc2007():
-    cur_path = os.path.dirname(os.path.abspath(__file__))
-    model_path = "{}/../../../../model_zoo/official/cv".format(cur_path)
-    model_name = "deeplabv3"
-    utils.copy_files(model_path, cur_path, model_name)
-    cur_model_path = os.path.join(cur_path, model_name)
-
-    old_list = ['/PATH_TO_DATA/vocaug/vocaug_mindrecord/vocaug_mindrecord0',
-                '/PATH/TO/PRETRAIN_MODEL']
-    new_list = [os.path.join(utils.data_root, "voc/voc2012/mindrecord_train/vocaug_mindrecord0"),
-                os.path.join(utils.ckpt_root, "deeplabv3/resnet101_ascend.ckpt")]
-    utils.exec_sed_command(old_list, new_list,
-                           os.path.join(cur_model_path, "scripts/run_distribute_train_s16_r1.sh"))
-
-    old_list = ['model.train(args.train_epochs',
-                'callbacks=cbs']
-    new_list = ['model.train(70',
-                'callbacks=cbs, sink_size=2']
-    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
-
-    exec_network_shell = "cd {}/scripts; sh run_distribute_train_s16_r1.sh {}".format(
-        model_name, utils.rank_table_path)
-    ret = os.system(exec_network_shell)
-    assert ret == 0
-    cmd = "ps -ef | grep python | grep train.py | grep -v grep"
-    ret = utils.process_check(100, cmd)
-    assert ret
-
-    log_file = os.path.join(cur_model_path, "scripts/s16_aug_train/device{}/log")
-    for i in range(8):
-        per_step_time = utils.get_perf_data(log_file.format(i))
-        print("per_step_time is", per_step_time)
-        assert per_step_time < 530.0
-    loss_list = []
-    for i in range(8):
-        loss = utils.get_loss_data_list(log_file.format(i))
-        print("loss is", loss[-1])
-        loss_list.append(loss[-1])
-    assert sum(loss_list) / len(loss_list) < 2.5
+# Copyright 2021 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 os
+import pytest
+
+from tests.st.model_zoo_tests import utils
+
+
+@pytest.mark.level1
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_single
+def test_DeeplabV3_voc2007():
+    cur_path = os.path.dirname(os.path.abspath(__file__))
+    model_path = "{}/../../../../model_zoo/official/cv".format(cur_path)
+    model_name = "deeplabv3"
+    utils.copy_files(model_path, cur_path, model_name)
+    cur_model_path = os.path.join(cur_path, model_name)
+
+    old_list = ['/PATH_TO_DATA/vocaug/vocaug_mindrecord/vocaug_mindrecord0',
+                '/PATH/TO/PRETRAIN_MODEL']
+    new_list = [os.path.join(utils.data_root, "voc/voc2012/mindrecord_train/vocaug_mindrecord0"),
+                os.path.join(utils.ckpt_root, "deeplabv3/resnet101_ascend.ckpt")]
+    utils.exec_sed_command(old_list, new_list,
+                           os.path.join(cur_model_path, "scripts/run_distribute_train_s16_r1.sh"))
+
+    old_list = ['model.train(args.train_epochs',
+                'callbacks=cbs']
+    new_list = ['model.train(70',
+                'callbacks=cbs, sink_size=2']
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
+
+    exec_network_shell = "cd {}/scripts; sh run_distribute_train_s16_r1.sh {}".format(
+        model_name, utils.rank_table_path)
+    ret = os.system(exec_network_shell)
+    assert ret == 0
+    cmd = "ps -ef | grep python | grep train.py | grep -v grep"
+    ret = utils.process_check(100, cmd)
+    assert ret
+
+    log_file = os.path.join(cur_model_path, "scripts/s16_aug_train/device{}/log")
+    for i in range(8):
+        per_step_time = utils.get_perf_data(log_file.format(i))
+        print("per_step_time is", per_step_time)
+        assert per_step_time < 530.0
+    loss_list = []
+    for i in range(8):
+        loss = utils.get_loss_data_list(log_file.format(i))
+        print("loss is", loss[-1])
+        loss_list.append(loss[-1])
+    assert sum(loss_list) / len(loss_list) < 2.5

tests/st/model_zoo_tests/gnmt_v2/test_gnmtv2_WMT_English_German.py

@@ -1,64 +1,64 @@
-# Copyright 2021 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 os
-import pytest
-
-from tests.st.model_zoo_tests import utils
-
-
-@pytest.mark.level0
-@pytest.mark.platform_x86_ascend_training
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.env_single
-def test_gnmtv2_WMT_English_German():
-    cur_path = os.path.dirname(os.path.abspath(__file__))
-    model_path = "{}/../../../../model_zoo/official/nlp".format(cur_path)
-    model_name = "gnmt_v2"
-    utils.copy_files(model_path, cur_path, model_name)
-    cur_model_path = os.path.join(cur_path, model_name)
-
-    old_list = ['dataset_sink_mode=config.dataset_sink_mode']
-    new_list = ['dataset_sink_mode=config.dataset_sink_mode, sink_size=100']
-    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
-    old_list = ['"epochs": 6,']
-    new_list = ['"epochs": 4,']
-    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "config/config.json"))
-
-    mindrecord_file = "wmt16_de_en/train_tok_mindrecord/train.tok.clean.bpe.32000.en.mindrecord"
-    exec_network_shell = "cd {}/scripts; sh run_distributed_train_ascend.sh {} {}"\
-        .format(model_name, utils.rank_table_path, os.path.join(utils.data_root, mindrecord_file))
-    ret = os.system(exec_network_shell)
-    assert ret == 0
-
-    cmd = "ps -ef | grep python | grep train.py | grep train.tok.clean.bpe | grep -v grep"
-    ret = utils.process_check(120, cmd)
-    assert ret
-
-    log_file = os.path.join(cur_model_path, "scripts/device{}/log_gnmt_network{}.log")
-    for i in range(8):
-        per_step_time = utils.get_perf_data(log_file.format(i, i))
-        print("per_step_time is", per_step_time)
-        assert per_step_time < 270.0
-
-    log_file = os.path.join(cur_model_path, "scripts/device{}/loss.log")
-    loss_list = []
-    for i in range(8):
-        pattern1 = r"loss\: ([\d\.\+]+)\,"
-        loss = utils.parse_log_file(pattern1, log_file.format(i))
-        print("loss is", loss)
-        loss_list.append(loss[-1])
-    print("loss_list is", loss_list)
-    print(sum(loss_list) / len(loss_list))
-    assert sum(loss_list) / len(loss_list) < 120
+# Copyright 2021 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 os
+import pytest
+
+from tests.st.model_zoo_tests import utils
+
+
+@pytest.mark.level1
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_single
+def test_gnmtv2_WMT_English_German():
+    cur_path = os.path.dirname(os.path.abspath(__file__))
+    model_path = "{}/../../../../model_zoo/official/nlp".format(cur_path)
+    model_name = "gnmt_v2"
+    utils.copy_files(model_path, cur_path, model_name)
+    cur_model_path = os.path.join(cur_path, model_name)
+
+    old_list = ['dataset_sink_mode=config.dataset_sink_mode']
+    new_list = ['dataset_sink_mode=config.dataset_sink_mode, sink_size=100']
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
+    old_list = ['"epochs": 6,']
+    new_list = ['"epochs": 4,']
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "config/config.json"))
+
+    mindrecord_file = "wmt16_de_en/train_tok_mindrecord/train.tok.clean.bpe.32000.en.mindrecord"
+    exec_network_shell = "cd {}/scripts; sh run_distributed_train_ascend.sh {} {}"\
+        .format(model_name, utils.rank_table_path, os.path.join(utils.data_root, mindrecord_file))
+    ret = os.system(exec_network_shell)
+    assert ret == 0
+
+    cmd = "ps -ef | grep python | grep train.py | grep train.tok.clean.bpe | grep -v grep"
+    ret = utils.process_check(120, cmd)
+    assert ret
+
+    log_file = os.path.join(cur_model_path, "scripts/device{}/log_gnmt_network{}.log")
+    for i in range(8):
+        per_step_time = utils.get_perf_data(log_file.format(i, i))
+        print("per_step_time is", per_step_time)
+        assert per_step_time < 270.0
+
+    log_file = os.path.join(cur_model_path, "scripts/device{}/loss.log")
+    loss_list = []
+    for i in range(8):
+        pattern1 = r"loss\: ([\d\.\+]+)\,"
+        loss = utils.parse_log_file(pattern1, log_file.format(i))
+        print("loss is", loss)
+        loss_list.append(loss[-1])
+    print("loss_list is", loss_list)
+    print(sum(loss_list) / len(loss_list))
+    assert sum(loss_list) / len(loss_list) < 120

tests/st/model_zoo_tests/maskrcnn/test_maskrcnn.py

@@ -24,7 +24,7 @@ from mindspore import Tensor, context, export
 
 context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/model_zoo_tests/transformer/test_transformer.py

@@ -203,7 +203,7 @@ def test_transformer():
     assert per_step_mseconds <= expect_per_step_mseconds + 2
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/model_zoo_tests/yolov3/test_yolov3.py

@@ -84,7 +84,7 @@ class TimeMonitor(Callback):
 
 DATA_DIR = "/home/workspace/mindspore_dataset/coco/coco2017/mindrecord_train/yolov3"
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_single

tests/st/model_zoo_tests/yolov3_darknet53/test_yolov3_darknet53.py

@@ -212,7 +212,7 @@ def test_yolov3_darknet53():
     print('==========test case passed===========')
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_single

tests/st/networks/models/bert/bert_precision/test_bert_tdt_lossscale.py

@@ -245,7 +245,7 @@ def test_bert_precision(enable_graph_kernel=False):
     assert np.allclose(loss_scale, expect_loss_scale, 0, 0)
 
 
-@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_gradient_accumulation.py

@@ -203,7 +203,7 @@ def create_dataset(data_path, batch_size=32, repeat_size=1,
     return mnist_ds
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard

tests/st/numpy_native/test_array_creations.py

@@ -974,7 +974,7 @@ def test_empty_like_exception():
         mnp.empty_like([[1, 2, 3], [4, 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/probability/distribution/test_gamma_pynative.py

@@ -39,7 +39,7 @@ class GammaMean(nn.Cell):
 
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
 def test_probability_gamma_mean_cdoncentration_rate_rand_2_ndarray():

tests/st/pynative/dynamic_shape/test_pynative_ftrl.py

@@ -35,7 +35,7 @@ class NetWithSparseGatherV2(nn.Cell):
     def construct(self, indices, label):
         return self.gather(self.weight1, indices, self.axis) + self.weight2
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -56,7 +56,7 @@ def test_pynative_ftrl_net():
                                                  [[0.6821311, 0.6821311]],
                                                  [[0.6821311, 0.6821311]]]))
 
-@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/loss_scale/test_loss_scale.py

@@ -145,7 +145,7 @@ class MSELoss(nn.Cell):
         diff = data - label
         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
@@ -168,7 +168,7 @@ def test_loss_scale_fp16_lr_overflow():
     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
@@ -211,7 +211,7 @@ def test_loss_scale_fp16_model_train_overflow():
     model = Model(net, loss_fn=loss, optimizer=optimizer, metrics=None, loss_scale_manager=scale_manager)
     model.train(2, dataset, dataset_sink_mode=False)
 
-@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/parser/test_parser_tensor_assign.py

@@ -73,7 +73,7 @@ def test_parser_tensor_assign_slice_002():
 
     assert np.allclose(out_me.asnumpy(), input_np_x, rtol=0.01, atol=0.01)
 
-@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_pynative_hook_grad.py

@@ -436,7 +436,7 @@ def test_pynative_hook_outermost_cell_not_change_grad_gpu():
     context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
     pynative_hook_outermost_cell_not_change_grad()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -451,7 +451,7 @@ def test_pynative_hook_all_cell_record_grad_gpu():
     context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
     pynative_hook_all_cell_record_grad()
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
@@ -481,7 +481,7 @@ def test_pynative_hook_mul2_change_input_grad_gpu():
     context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
     pynative_hook_mul2_change_input_grad()
 
-@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_tensor_augassign.py

@@ -604,7 +604,7 @@ def test_tesnsor_augassign_by_list():
 
 
 # GPU: does not supported op "FloorMod"
-@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_tensor_getitem.py

@@ -48,7 +48,7 @@ class NetWorkSlicePositive(Cell):
         return ret0, ret1, ret2, ret3
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -213,7 +213,7 @@ class TensorGetItemByMixedTensorsBasicCase(Cell):
         return ret0, ret1, ret2, ret3, ret4, ret5
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -247,7 +247,7 @@ class TensorItemByNone(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -272,7 +272,7 @@ class TensorItemByItem(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -308,7 +308,7 @@ def test_item_by_int():
         net(input_3d_ms, index_np_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
@@ -439,7 +439,7 @@ class TensorSetItemByMixedTensors_2(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -466,7 +466,7 @@ class TensorGetItemByMixedTensorsIndexError(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -493,7 +493,7 @@ class TensorSetItemByOneTensorWithNumber(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -522,7 +522,7 @@ class TensorSetItemByOneTensorWithTensor(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -553,7 +553,7 @@ class TensorSetItemByOneTensorWithTupleOfNumber(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -582,7 +582,7 @@ class TensorSetItemByOneTensorWithTupleOfTensor(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -617,7 +617,7 @@ class TensorSetItemByTensorsWithNumber(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -685,7 +685,7 @@ class TensorSetItemByTensorsWithTensorNumberError(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -714,7 +714,7 @@ class TensorSetItemByTensorsWithTupleOfNumber(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 # GPU op has bug, and has not been fixed.
@@ -747,7 +747,7 @@ class TensorSetItemByTensorsWithTupleOfTensor(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 # GPU op has bug, and has not been fixed.
@@ -785,7 +785,7 @@ class TensorSetItemByTensorsWithTupleOfTensorNumberError(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -877,7 +877,7 @@ class TensorAssignWithSlice(Cell):
         return z
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -927,7 +927,7 @@ def test_tensor_assign_slice_value_2():
     assert np.all(z == out.asnumpy())
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -1121,7 +1121,7 @@ def test_tensor_assign_bool_index_0():
     assert np.all(out.asnumpy() == res)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -1142,7 +1142,7 @@ def test_tensor_assign_bool_index_1():
     assert np.all(out.asnumpy() == res)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -1207,7 +1207,7 @@ def test_tensor_slice_reduce_out_of_bounds_neg():
     assert "begin should be in [-6, 6), but got stride: 1, begin: -7." in str(ex.value)
 
 
-@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/pynative/test_tensor_setitem.py

@@ -236,7 +236,7 @@ class TensorItemSetWithNumber(Cell):
         return ret
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -287,7 +287,7 @@ def test_setitem_dim_expand():
     setup_testcase(x, cases)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -341,7 +341,7 @@ def test_itemset_by_number_with_number():
         net(input_3d_ms, index_np_4, value_np_2)
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training