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

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2.5 KiB

# 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 six
import paddle.fluid as fluid
from paddle.fluid.framework import Variable
def cyclic_reader(reader):
def __reader__():
while True:
for data in reader():
yield data
return __reader__
class FeedDataReader(object):
def __init__(self, feed_list, reader):
self._feed_list = []
for var in feed_list:
if isinstance(var, Variable):
self._feed_list.append(var.name)
else:
self._feed_list.append(var)
self._reader = cyclic_reader(reader)
self._iter = self._reader()
def _feed_executor(self):
next_data = next(self._iter)
feed_data = dict()
assert len(self._feed_list) == len(next_data)
for key, value in six.moves.zip(self._feed_list, next_data):
feed_data[key] = value
return feed_data
def _feed_parallel_executor(self, device_num):
feed_data = []
for _ in six.moves.range(device_num):
feed_data.append(self._feed_executor())
return feed_data
def get_next(self, exe, program):
result = []
assert isinstance(exe, fluid.Executor), "exe must be Executor"
use_cuda = isinstance(exe.place, fluid.CUDAPlace)
if isinstance(program, fluid.CompiledProgram):
if program._is_data_parallel:
use_executor = False
if program._places is None:
device_num = len(fluid.cuda_places()) if use_cuda else len(
fluid.cpu_places())
else:
device_num = len(program._places)
else:
use_executor = True
device_num = 1
else:
use_executor = True
device_num = 1
if use_executor:
return self._feed_executor()
else:
return self._feed_parallel_executor(device_num)