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Paddle/python/paddle/fluid/tests/unittests/test_multi_file_reader.py

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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
import paddle.fluid as fluid
import paddle
import paddle.dataset.mnist as mnist
from shutil import copyfile
class TestMultipleReader(unittest.TestCase):
def setUp(self):
self.batch_size = 64
# Convert mnist to recordio file
with fluid.program_guard(fluid.Program(), fluid.Program()):
reader = paddle.batch(mnist.train(), batch_size=self.batch_size)
feeder = fluid.DataFeeder(
feed_list=[ # order is image and label
fluid.layers.data(
name='image', shape=[784]),
fluid.layers.data(
name='label', shape=[1], dtype='int64'),
],
place=fluid.CPUPlace())
self.num_batch = fluid.recordio_writer.convert_reader_to_recordio_file(
'./mnist_0.recordio', reader, feeder)
copyfile('./mnist_0.recordio', './mnist_1.recordio')
copyfile('./mnist_0.recordio', './mnist_2.recordio')
def main(self, thread_num):
file_list = [
'./mnist_0.recordio', './mnist_1.recordio', './mnist_2.recordio'
]
with fluid.program_guard(fluid.Program(), fluid.Program()):
data_files = fluid.layers.open_files(
filenames=file_list,
thread_num=thread_num,
shapes=[(-1, 784), (-1, 1)],
lod_levels=[0, 0],
dtypes=['float32', 'int64'])
img, label = fluid.layers.read_file(data_files)
if fluid.core.is_compiled_with_cuda():
place = fluid.CUDAPlace(0)
else:
place = fluid.CPUPlace()
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
batch_count = 0
while True:
try:
img_val, = exe.run(fetch_list=[img])
except fluid.core.EnforceNotMet as ex:
self.assertIn("There is no next data.", ex.message)
break
batch_count += 1
self.assertLessEqual(img_val.shape[0], self.batch_size)
self.assertEqual(batch_count, self.num_batch * 3)
def test_main(self):
self.main(thread_num=3) # thread number equals to file number
self.main(thread_num=10) # thread number is larger than file number
self.main(thread_num=2) # thread number is less than file number