forked from mindspore-Ecosystem/mindspore
Add heartbeat check in summary and delete test cases that do not exit
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692d158f5c
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@ -14,10 +14,13 @@
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# ============================================================================
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"""Write events to disk in a base directory."""
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import os
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import sys
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import time
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import signal
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from collections import deque
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import psutil
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import mindspore.log as logger
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from mindspore.train.summary.enums import PluginEnum, WriterPluginEnum
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@ -78,6 +81,7 @@ class WriterPool(ctx.Process):
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self._queue, self._writers_ = ctx.Queue(ctx.cpu_count() * 2), None
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self._max_file_size = max_file_size
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self._raise_exception = raise_exception
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self._training_pid = os.getpid()
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self.start()
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def run(self):
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@ -97,10 +101,7 @@ class WriterPool(ctx.Process):
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with ctx.Pool(min(ctx.cpu_count(), 32)) as pool:
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deq = deque()
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while True:
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if not self._writers:
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logger.warning("Can not find any writer to write summary data, "
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"so SummaryRecord will not record data.")
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break
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self._check_heartbeat()
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while deq and deq[0].ready():
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for plugin, data in deq.popleft().get():
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@ -163,6 +164,7 @@ class WriterPool(ctx.Process):
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"""Close the writers in the subprocess."""
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for writer in self._writers:
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writer.close()
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super().close()
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def write(self, data) -> None:
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"""
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@ -180,4 +182,19 @@ class WriterPool(ctx.Process):
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def close(self) -> None:
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"""Close the writer."""
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self._queue.put(('END', None))
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self.join()
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def _check_heartbeat(self):
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"""Check if the summary process should survive."""
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is_exit = False
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if not psutil.pid_exists(self._training_pid):
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logger.warning("The training process %d is killed, summary process will exit.", self._training_pid)
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is_exit = True
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if not self._writers:
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logger.warning("Can not find any writer to write summary data, "
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"so SummaryRecord will not record data.")
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is_exit = True
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if is_exit:
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self._close()
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sys.exit(1)
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@ -399,6 +399,7 @@ class SummaryRecord:
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logger.info('Please wait it may take quite some time to finish writing and closing.')
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atexit.unregister(self.close)
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self._event_writer.close()
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self._event_writer.join()
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self._closed = True
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@staticmethod
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@ -17,3 +17,4 @@ astunparse >= 1.6.3
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packaging >= 20.0
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pycocotools >= 2.0.0 # for st test
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tables >= 3.6.1 # for st test
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psutil >= 5.6.1
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3
setup.py
3
setup.py
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@ -121,7 +121,8 @@ required_package = [
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'decorator >= 4.4.0',
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'setuptools >= 40.8.0',
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'astunparse >= 1.6.3',
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'packaging >= 20.0'
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'packaging >= 20.0',
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'psutil >= 5.6.1'
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]
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package_data = {
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@ -1,151 +0,0 @@
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""Test summary function of ops params valid check."""
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import os
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import tempfile
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import shutil
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from enum import Enum
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import numpy as np
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import pytest
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import mindspore.nn as nn
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from mindspore.common.tensor import Tensor
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from mindspore.ops import operations as P
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from mindspore.train.summary.summary_record import SummaryRecord
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class SummaryEnum(Enum):
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"""Summary enum."""
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IMAGE = P.ImageSummary.__name__
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SCALAR = P.ScalarSummary.__name__
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TENSOR = P.TensorSummary.__name__
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HISTOGRAM = P.HistogramSummary.__name__
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class SummaryNet(nn.Cell):
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"""Summary net definition."""
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def __init__(self, summary_type, tag, data):
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super(SummaryNet, self).__init__()
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self.tag = tag
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self.data = data
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self.summary_fn = getattr(P, summary_type)()
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self.one = Tensor(np.array([1]).astype(np.float32))
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self.add = P.Add()
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def construct(self):
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self.summary_fn(self.tag, self.data)
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return self.add(self.one, self.one)
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class TestSummaryOps:
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"""Test summary operators."""
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summary_dir = ''
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@classmethod
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def run_case(cls, net):
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""" run_case """
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net.set_train()
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steps = 10
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with SummaryRecord(cls.summary_dir) as test_writer:
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for i in range(1, steps):
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net()
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test_writer.record(i)
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@classmethod
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def setup_class(cls):
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"""Run before class."""
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if not os.path.exists(cls.summary_dir):
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cls.summary_dir = tempfile.mkdtemp(suffix='_summary')
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@classmethod
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def teardown_class(cls):
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"""Run after class."""
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if os.path.exists(cls.summary_dir):
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shutil.rmtree(cls.summary_dir)
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@pytest.mark.parametrize(
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"summary_type, value",
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[
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(SummaryEnum.SCALAR.value, Tensor(1)),
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(SummaryEnum.SCALAR.value, Tensor(np.array([1]))),
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(SummaryEnum.IMAGE.value, Tensor(np.array([[[[1], [2], [3], [4]]]]))),
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(SummaryEnum.TENSOR.value, Tensor(np.array([[1], [2], [3], [4]]))),
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(SummaryEnum.HISTOGRAM.value, Tensor(np.array([[1], [2], [3], [4]]))),
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])
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def test_summary_success(self, summary_type, value):
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"""Test summary success with valid tag and valid data."""
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net = SummaryNet(summary_type, tag='tag', data=value)
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TestSummaryOps.run_case(net)
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@pytest.mark.parametrize(
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"summary_type",
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[
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SummaryEnum.SCALAR.value,
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SummaryEnum.IMAGE.value,
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SummaryEnum.HISTOGRAM.value,
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SummaryEnum.TENSOR.value
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])
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def test_summary_tag_is_none(self, summary_type):
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"""Test summary tag is None, all summary operator validation rules are consistent."""
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net = SummaryNet(summary_type, tag=None, data=Tensor(0))
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with pytest.raises(TypeError):
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TestSummaryOps.run_case(net)
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@pytest.mark.parametrize(
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"summary_type",
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[
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SummaryEnum.SCALAR.value,
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SummaryEnum.IMAGE.value,
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SummaryEnum.HISTOGRAM.value,
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SummaryEnum.TENSOR.value
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])
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def test_summary_tag_is_empty_string(self, summary_type):
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"""Test summary tag is a empty string, all summary operator validation rules are consistent."""
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net = SummaryNet(summary_type, tag='', data=Tensor(0))
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with pytest.raises(ValueError):
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TestSummaryOps.run_case(net)
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@pytest.mark.parametrize("tag", [123, True, Tensor(0)])
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def test_summary_tag_is_not_string(self, tag):
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"""Test summary tag is not a string, all summary operator validation rules are consistent."""
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# All summary operator validation rules are consistent, so we only test scalar summary.
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net = SummaryNet(SummaryEnum.SCALAR.value, tag=tag, data=Tensor(0))
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with pytest.raises(TypeError):
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TestSummaryOps.run_case(net)
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@pytest.mark.parametrize("value", [123, True, 'data'])
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def test_summary_value_type_invalid(self, value):
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"""Test the type of summary value is invalid, all summary operator validation rules are consistent."""
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# All summary operator validation rules are consistent, so we only test scalar summary.
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net = SummaryNet(SummaryEnum.SCALAR.value, tag='tag', data=value)
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with pytest.raises(TypeError):
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TestSummaryOps.run_case(net)
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@pytest.mark.parametrize(
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"summary_type, value",
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[
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(SummaryEnum.IMAGE.value, Tensor(np.array([1, 2]))),
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(SummaryEnum.SCALAR.value, Tensor(np.array([1, 2]))),
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(SummaryEnum.TENSOR.value, Tensor(0)),
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(SummaryEnum.HISTOGRAM.value, Tensor(0))
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])
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def test_value_shape_invalid(self, summary_type, value):
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"""Test invalid shape of every summary operators."""
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net = SummaryNet(summary_type, tag='tag', data=value)
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with pytest.raises(ValueError):
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TestSummaryOps.run_case(net)
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