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108 lines
3.7 KiB
108 lines
3.7 KiB
# Copyright (c) 2020 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.fluid as fluid
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from paddle.fluid.layer_helper import LayerHelper
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import unittest
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import numpy as np
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import time
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def inplace_add(x, bias):
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helper = LayerHelper('scale', **locals())
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helper.append_op(
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type='scale',
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inputs={'X': [x]},
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outputs={'Out': [x]},
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attrs={'bias': bias})
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return x
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class TestAddReaderDependency(unittest.TestCase):
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def setUp(self):
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self.batch_num = 3
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self.sleep_time = 2
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self.use_double_buffer = True
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def test_main(self):
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self.run_main(fluid.CPUPlace())
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if fluid.is_compiled_with_cuda():
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self.run_main(fluid.CUDAPlace(0))
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def run_main(self, place):
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with fluid.program_guard(fluid.Program(), fluid.Program()):
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with fluid.scope_guard(fluid.Scope()):
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tmp_in = fluid.data(name='tmp_in', dtype='float32', shape=[1])
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loader = fluid.io.DataLoader.from_generator(
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feed_list=[tmp_in],
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capacity=16,
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iterable=False,
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use_double_buffer=self.use_double_buffer)
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def data_source():
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for _ in range(self.batch_num):
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time.sleep(self.sleep_time) # sleep some times
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yield np.random.uniform(
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low=-1, high=1, size=[1]).astype('float32'),
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persistable_in = fluid.data(
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name='persistable_in', dtype='float32', shape=[1])
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persistable_in.persistable = True
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persistable_in = inplace_add(persistable_in, bias=1)
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prog = fluid.CompiledProgram(fluid.default_main_program())
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exe = fluid.Executor(place)
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loader.set_batch_generator(data_source)
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loader.start()
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batch_id = 0
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try:
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while True:
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if batch_id == 0:
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feed = {
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persistable_in.name:
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np.array([-1]).astype('float32')
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}
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else:
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feed = None
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ret, = exe.run(prog,
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feed=feed,
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fetch_list=[persistable_in])
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self.assertEqual(ret.shape, (1, ))
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self.assertEqual(ret[0], batch_id)
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batch_id += 1
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except fluid.core.EOFException:
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loader.reset()
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self.assertEqual(batch_id, self.batch_num)
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t = fluid.global_scope().find_var(
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persistable_in.name).get_tensor()
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t_val = np.array(t)
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self.assertEqual(t_val.shape, (1, ))
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self.assertEqual(t_val[0] + 1, batch_id)
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class TestAddReaderDependencyWithoutDoubleBuffer(TestAddReaderDependency):
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def setUp(self):
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self.batch_num = 3
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self.sleep_time = 2
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self.use_double_buffer = False
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if __name__ == '__main__':
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unittest.main()
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