wehub-resource-sync
92 lines
3.3 KiB
Python
92 lines
3.3 KiB
Python
# Copyright (c) 2022 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 annotations
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from typing import TYPE_CHECKING
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import paddle
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from paddle.distributed.communication import stream
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from paddle.distributed.communication.reduce import ReduceOp
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if TYPE_CHECKING:
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from paddle import Tensor
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from paddle.base.core import task
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from paddle.distributed.communication.group import Group
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from paddle.distributed.communication.reduce import _ReduceOp
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def all_reduce(
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tensor: Tensor,
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op: _ReduceOp = ReduceOp.SUM,
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group: Group | None = None,
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sync_op: bool = True,
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) -> task:
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"""
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Reduce a tensor over all ranks so that all get the result.
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As shown below, one process is started with a GPU and the data of this process is represented
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by its group rank. The reduce operator is sum. Through all_reduce operator,
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each GPU will have the sum of the data from all GPUs.
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.. image:: https://githubraw.cdn.bcebos.com/PaddlePaddle/docs/develop/docs/api/paddle/distributed/img/allreduce.png
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:width: 800
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:alt: all_reduce
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:align: center
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Args:
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tensor (Tensor): The input Tensor. It also works as the output Tensor. Its data type
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should be float16, float32, float64, int32, int64, int8, uint8 or bool.
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op (ReduceOp.SUM|ReduceOp.MAX|ReduceOp.MIN|ReduceOp.PROD|ReduceOp.AVG, optional): The operation used. Default value is ReduceOp.SUM.
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group (Group|None, optional): The group instance return by new_group or None for global default group.
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sync_op (bool, optional): Whether this op is a sync op. Default value is True.
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Returns:
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Return a task object.
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Examples:
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.. code-block:: pycon
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>>> # doctest: +REQUIRES(env: DISTRIBUTED)
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>>> import paddle
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>>> import paddle.distributed as dist
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>>> dist.init_parallel_env()
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>>> if dist.get_rank() == 0:
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... data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
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>>> else:
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... data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
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>>> dist.all_reduce(data)
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>>> print(data)
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>>> # [[5, 7, 9], [5, 7, 9]] (2 GPUs)
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"""
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# AVG is only supported when nccl >= 2.10
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if op == ReduceOp.AVG and paddle.base.core.nccl_version() < 21000:
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group = (
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paddle.distributed.collective._get_global_group()
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if group is None
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else group
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)
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tensor.scale_(1.0 / group.nranks)
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return stream.all_reduce(
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tensor,
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op=ReduceOp.SUM,
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group=group,
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sync_op=sync_op,
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use_calc_stream=False,
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)
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return stream.all_reduce(
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tensor, op=op, group=group, sync_op=sync_op, use_calc_stream=False
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)
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