forked from PulseFocusPlatform/PulseFocusPlatform
153 lines
3.8 KiB
Python
153 lines
3.8 KiB
Python
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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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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import os
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import time
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import unittest
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import sys
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import logging
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import random
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import copy
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# add python path of PadleDetection to sys.path
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parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 4)))
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if parent_path not in sys.path:
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sys.path.append(parent_path)
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from ppdet.data.parallel_map import ParallelMap
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from ppdet.utils.check import enable_static_mode
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class MemorySource(object):
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""" memory data source for testing
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"""
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def __init__(self, samples):
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self._epoch = -1
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self._pos = -1
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self._drained = False
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self._samples = samples
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def __iter__(self):
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return self
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def __next__(self):
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return self.next()
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def next(self):
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if self._epoch < 0:
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self.reset()
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if self._pos >= self.size():
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self._drained = True
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raise StopIteration("no more data in " + str(self))
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else:
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sample = copy.deepcopy(self._samples[self._pos])
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self._pos += 1
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return sample
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def reset(self):
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if self._epoch < 0:
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self._epoch = 0
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else:
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self._epoch += 1
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self._pos = 0
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self._drained = False
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random.shuffle(self._samples)
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def size(self):
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return len(self._samples)
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def drained(self):
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assert self._epoch >= 0, "the first epoch has not started yet"
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return self._pos >= self.size()
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def epoch_id(self):
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return self._epoch
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class TestDataset(unittest.TestCase):
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"""Test cases for ppdet.data.dataset
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"""
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@classmethod
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def setUpClass(cls):
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""" setup
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"""
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pass
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@classmethod
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def tearDownClass(cls):
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""" tearDownClass """
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pass
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def test_next(self):
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""" test next
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"""
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samples = list(range(10))
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mem_sc = MemorySource(samples)
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for i, d in enumerate(mem_sc):
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self.assertTrue(d in samples)
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def test_transform_with_abnormal_worker(self):
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""" test dataset transform with abnormally exit process
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"""
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samples = list(range(20))
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mem_sc = MemorySource(samples)
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def _worker(sample):
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if sample == 3:
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sys.exit(1)
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return 2 * sample
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test_worker = ParallelMap(
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mem_sc, _worker, worker_num=2, use_process=True, memsize='2M')
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ct = 0
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for i, d in enumerate(test_worker):
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ct += 1
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self.assertTrue(d / 2 in samples)
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self.assertEqual(len(samples) - 1, ct)
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def test_transform_with_delay_worker(self):
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""" test dataset transform with delayed process
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"""
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samples = list(range(20))
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mem_sc = MemorySource(samples)
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def _worker(sample):
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if sample == 3:
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time.sleep(30)
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return 2 * sample
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test_worker = ParallelMap(
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mem_sc, _worker, worker_num=2, use_process=True, memsize='2M')
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ct = 0
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for i, d in enumerate(test_worker):
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ct += 1
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self.assertTrue(d / 2 in samples)
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self.assertEqual(len(samples), ct)
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if __name__ == '__main__':
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enable_static_mode()
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logging.basicConfig()
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unittest.main()
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