wehub-resource-sync
108 lines
3.6 KiB
Python
108 lines
3.6 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 multiprocessing
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import queue
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import unittest
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import numpy as np
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from paddle import base
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from paddle.base.reader import _reader_process_loop
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def get_random_images_and_labels(image_shape, label_shape):
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image = np.random.random(size=image_shape).astype('float32')
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label = np.random.random(size=label_shape).astype('int64')
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return image, label
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def batch_generator_creator(batch_size, batch_num):
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def __reader__():
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for _ in range(batch_num):
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batch_image, batch_label = get_random_images_and_labels(
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[batch_size, 784], [batch_size, 1]
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)
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yield batch_image, batch_label
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return __reader__
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# NOTE: coverage CI can't cover child process code, so need these test.
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# Here test child process loop function in main process
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class TestDygraphDataLoaderProcess(unittest.TestCase):
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def setUp(self):
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self.batch_size = 8
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self.batch_num = 4
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self.epoch_num = 2
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self.capacity = 2
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def test_reader_process_loop(self):
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# This unittest's memory mapped files needs to be cleaned manually
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def __clear_process__(util_queue):
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while True:
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try:
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util_queue.get_nowait()
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except queue.Empty:
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break
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with base.dygraph.guard():
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loader = base.io.DataLoader.from_generator(
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capacity=self.batch_num + 1, use_multiprocess=True
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)
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loader.set_batch_generator(
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batch_generator_creator(self.batch_size, self.batch_num),
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places=base.CPUPlace(),
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)
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loader._data_queue = queue.Queue(self.batch_num + 1)
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_reader_process_loop(loader._batch_reader, loader._data_queue)
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# For clean memory mapped files
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util_queue = multiprocessing.Queue(self.batch_num + 1)
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for _ in range(self.batch_num):
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data = loader._data_queue.get(timeout=10)
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util_queue.put(data)
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# Clean up memory mapped files
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clear_process = multiprocessing.Process(
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target=__clear_process__, args=(util_queue,)
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)
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clear_process.start()
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def test_reader_process_loop_simple_none(self):
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def none_sample_generator(batch_num):
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def __reader__():
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for _ in range(batch_num):
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yield None
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return __reader__
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with base.dygraph.guard():
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loader = base.io.DataLoader.from_generator(
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capacity=self.batch_num + 1, use_multiprocess=True
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)
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loader.set_batch_generator(
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none_sample_generator(self.batch_num), places=base.CPUPlace()
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)
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loader._data_queue = queue.Queue(self.batch_num + 1)
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exception = None
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try:
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_reader_process_loop(loader._batch_reader, loader._data_queue)
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except ValueError as ex:
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exception = ex
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self.assertIsNotNone(exception)
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if __name__ == '__main__':
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unittest.main()
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