# Copyright (c) 2019 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 paddle import paddle.fluid as fluid from paddle.reader import multiprocess_reader import unittest import numpy as np class ReaderException(Exception): pass class TestMultiprocessReaderExceptionWithQueueSuccess(unittest.TestCase): def setUp(self): self.use_pipe = False self.raise_exception = False def places(self): if fluid.is_compiled_with_cuda(): return [fluid.CPUPlace(), fluid.CUDAPlace(0)] else: return [fluid.CPUPlace()] def main_impl(self, place, iterable): sample_num = 40 batch_size = 4 def fake_reader(): def __impl__(): for _ in range(sample_num): if not self.raise_exception: yield list(np.random.uniform(low=-1, high=1, size=[10])), else: raise ValueError() return __impl__ with fluid.program_guard(fluid.Program(), fluid.Program()): image = fluid.data(name='image', dtype='float32', shape=[None, 10]) reader = fluid.io.DataLoader.from_generator(feed_list=[image], capacity=2, iterable=iterable) image_p_1 = image + 1 decorated_reader = multiprocess_reader( [fake_reader(), fake_reader()], use_pipe=self.use_pipe) if isinstance(place, fluid.CUDAPlace): reader.set_sample_generator(decorated_reader, batch_size=batch_size, places=fluid.cuda_places(0)) else: reader.set_sample_generator(decorated_reader, batch_size=batch_size, places=fluid.cpu_places(1)) exe = fluid.Executor(place) exe.run(fluid.default_startup_program()) batch_num = int(sample_num * 2 / batch_size) if iterable: for _ in range(3): num = 0 try: for data in reader(): exe.run(feed=data, fetch_list=[image_p_1]) num += 1 self.assertEqual(num, batch_num) except SystemError as ex: self.assertEqual(num, 0) raise ReaderException() else: for _ in range(3): num = 0 reader.start() try: while True: exe.run(fetch_list=[image_p_1]) num += 1 except fluid.core.EOFException: reader.reset() self.assertFalse(self.raise_exception) self.assertEqual(num, batch_num) except SystemError as ex: self.assertTrue(self.raise_exception) self.assertEqual(num, 0) raise ReaderException() def test_main(self): for p in self.places(): for iterable in [False, True]: try: with fluid.scope_guard(fluid.Scope()): self.main_impl(p, iterable) self.assertTrue(not self.raise_exception) except ReaderException: self.assertTrue(self.raise_exception) class TestMultiprocessReaderExceptionWithQueueFailed( TestMultiprocessReaderExceptionWithQueueSuccess): def setUp(self): self.use_pipe = False self.raise_exception = True class TestMultiprocessReaderExceptionWithPipeSuccess( TestMultiprocessReaderExceptionWithQueueSuccess): def setUp(self): self.use_pipe = True self.raise_exception = False class TestMultiprocessReaderExceptionWithPipeFailed( TestMultiprocessReaderExceptionWithQueueSuccess): def setUp(self): self.use_pipe = True self.raise_exception = True if __name__ == '__main__': paddle.enable_static() unittest.main()