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85 lines
3.1 KiB
85 lines
3.1 KiB
# 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 paddle
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import paddle.fluid as fluid
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import unittest
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import numpy as np
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class TestPyReader(unittest.TestCase):
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def setUp(self):
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self.batch_size = 32
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self.epoch_num = 2
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self.sample_num = 10
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def test_returnlist(self):
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def reader_creator_random_image(height, width):
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def reader():
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for i in range(self.sample_num):
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yield np.random.uniform(
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low=0, high=255, size=[height, width]),
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return reader
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for return_list in [True, False]:
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with fluid.program_guard(fluid.Program(), fluid.Program()):
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image = fluid.layers.data(
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name='image', shape=[784, 784], dtype='float32')
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reader = fluid.io.PyReader(
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feed_list=[image],
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capacity=4,
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iterable=True,
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return_list=return_list)
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user_defined_reader = reader_creator_random_image(784, 784)
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reader.decorate_sample_list_generator(
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paddle.batch(
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user_defined_reader, batch_size=self.batch_size),
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fluid.core.CPUPlace())
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# definition of network is omitted
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executor = fluid.Executor(fluid.core.CPUPlace())
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executor.run(fluid.default_main_program())
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for _ in range(self.epoch_num):
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for data in reader():
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if return_list:
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executor.run(feed={"image": data[0]})
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else:
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executor.run(feed=data)
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with fluid.dygraph.guard():
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batch_py_reader = fluid.io.PyReader(
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feed_list=[
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np.empty(
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[self.batch_size, 784, 784], dtype='float32')
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],
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capacity=2,
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use_double_buffer=True,
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return_list=return_list)
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user_defined_reader = reader_creator_random_image(784, 784)
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batch_py_reader.decorate_sample_generator(
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user_defined_reader,
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batch_size=self.batch_size,
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places=fluid.core.CPUPlace())
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for epoch in range(self.epoch_num):
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for _, data in enumerate(batch_py_reader()):
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# empty network
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pass
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if __name__ == "__main__":
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unittest.main()
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