forked from mindspore-Ecosystem/mindspore
75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
# 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.
|
|
# ============================================================================
|
|
"""Test ascend profiling."""
|
|
import glob
|
|
import tempfile
|
|
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 import Profiler
|
|
from tests.security_utils import security_off_wrap
|
|
|
|
|
|
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
|
|
@security_off_wrap
|
|
def test_ascend_profiling():
|
|
"""Test ascend profiling"""
|
|
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
|
|
with tempfile.TemporaryDirectory() as tmpdir:
|
|
profiler = Profiler(output_path=tmpdir)
|
|
add = Net()
|
|
add(Tensor(x), Tensor(y))
|
|
profiler.analyse()
|
|
assert len(glob.glob(f"{tmpdir}/profiler*/*PROF*/device_*/data/Framework*")) == 4
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
@security_off_wrap
|
|
def test_ascend_pynative_profiling():
|
|
"""
|
|
Feature: Test the ascend pynative model profiling
|
|
Description: Generate the Net op timeline
|
|
Expectation: Timeline generated successfully
|
|
"""
|
|
context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
|
|
with tempfile.TemporaryDirectory() as tmpdir:
|
|
profiler = Profiler(output_path=tmpdir)
|
|
add = Net()
|
|
add(Tensor(x), Tensor(y))
|
|
profiler.analyse()
|
|
assert len(glob.glob(f"{tmpdir}/profiler*/output_timeline_data_*.txt")) == 1
|