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67 lines
2.5 KiB
67 lines
2.5 KiB
# Copyright (c) 2018 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 unittest
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import paddle.fluid as fluid
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import paddle
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import paddle.dataset.mnist as mnist
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class TestMultipleReader(unittest.TestCase):
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def setUp(self):
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self.batch_size = 64
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self.pass_num = 3
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# Convert mnist to recordio file
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with fluid.program_guard(fluid.Program(), fluid.Program()):
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data_file = paddle.batch(mnist.train(), batch_size=self.batch_size)
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feeder = fluid.DataFeeder(
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feed_list=[
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fluid.layers.data(
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name='image', shape=[784]),
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fluid.layers.data(
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name='label', shape=[1], dtype='int64'),
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],
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place=fluid.CPUPlace())
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self.num_batch = fluid.recordio_writer.convert_reader_to_recordio_file(
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'./mnist.recordio', data_file, feeder)
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def test_main(self):
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with fluid.program_guard(fluid.Program(), fluid.Program()):
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data_file = fluid.layers.open_recordio_file(
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filename='./mnist.recordio',
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shapes=[(-1, 784), (-1, 1)],
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lod_levels=[0, 0],
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dtypes=['float32', 'int64'],
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pass_num=self.pass_num)
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img, label = fluid.layers.read_file(data_file)
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if fluid.core.is_compiled_with_cuda():
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place = fluid.CUDAPlace(0)
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else:
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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exe.run(fluid.default_startup_program())
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batch_count = 0
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while True:
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try:
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img_val, = exe.run(fetch_list=[img])
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except fluid.core.EOFException:
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break
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batch_count += 1
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self.assertLessEqual(img_val.shape[0], self.batch_size)
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self.assertEqual(batch_count, self.num_batch * self.pass_num)
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