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67 lines
2.0 KiB
67 lines
2.0 KiB
6 years ago
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# Copyright (c) 2019 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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from __future__ import print_function
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import os
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__all__ = ["distributed_sampler"]
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def distributed_sampler(reader, batch_size):
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"""
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Create a distributed reader.
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:param reader: the data reader to read from.
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:type reader: callable
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:param batch_size: the size of the batch
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:type batch_size: int
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"""
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def batch_reader():
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if not os.getenv('PADDLE_TRAINER_ID'):
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raise RuntimeError(
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"The current program is not in distributed mode.")
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trainer_id = int(os.getenv("PADDLE_TRAINER_ID", "0"))
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trainer_count = int(os.getenv("PADDLE_TRAINERS_NUM", "1"))
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def _slice_data(size):
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per_node_lines = size // trainer_count
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return [
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trainer_id * per_node_lines, (trainer_id + 1) * per_node_lines
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]
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r = reader()
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b = []
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for instance in r:
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b.append(instance)
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if len(b) == batch_size:
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if len(b) >= trainer_count:
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begin, end = _slice_data(len(b))
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yield b[begin:end]
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b = []
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if len(b) >= trainer_count:
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begin, end = _slice_data(len(b))
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yield b[begin:end]
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# Batch size check
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batch_size = int(batch_size)
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if batch_size <= 0:
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raise ValueError("batch_size should be a positive integeral value, "
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"but got batch_size={}".format(batch_size))
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return batch_reader
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