|
- # 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 shutil
- import glob
- import numpy as np
- import pytest
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.ops import operations as P
- from mindspore.profiler import Profiler
-
- class Net(nn.Cell):
- def __init__(self):
- super(Net, self).__init__()
- self.add = P.Add()
-
- def construct(self, x_, y_):
- return self.add(x_, y_)
-
-
- x = np.random.randn(1, 3, 3, 4).astype(np.float32)
- y = np.random.randn(1, 3, 3, 4).astype(np.float32)
-
- @pytest.mark.level0
- @pytest.mark.platform_arm_ascend_training
- @pytest.mark.platform_x86_ascend_training
- @pytest.mark.env_onecard
- def test_ascend_profiling():
- if os.path.isdir("./data_ascend_profiler"):
- shutil.rmtree("./data_ascend_profiler")
- context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
- profiler = Profiler(output_path="./data_ascend_profiler", is_detail=True, is_show_op_path=False, subgraph="all")
- add = Net()
- add(Tensor(x), Tensor(y))
- profiler.analyse()
- assert len(glob.glob("./data_ascend_profiler/profiler*/JOB*/data/Framework*")) == 6
|