139 lines
4.9 KiB
Python
139 lines
4.9 KiB
Python
# Copyright (c) 2023 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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import warnings
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from typing import TYPE_CHECKING
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import paddle
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import paddle.distributed as dist
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from paddle import framework
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from paddle.distributed.communication.group import (
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_get_global_group,
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_get_or_throw_group_rank,
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_warn_cur_rank_not_in_group,
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)
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if TYPE_CHECKING:
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from collections.abc import Sequence
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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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def _gather_in_dygraph(
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tensor, gather_list, dst_rank_in_group, group, sync_op, use_calc_stream
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):
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nranks = group.nranks
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if group.rank == dst_rank_in_group:
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if len(gather_list) == 0:
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gather_list += [paddle.empty_like(tensor) for _ in range(nranks)]
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else:
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gather_list = [tensor for _ in range(nranks)]
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assert len(gather_list) == nranks, (
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f" gather_list length {len(gather_list)} and nrankd {nranks} not equal"
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)
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task = group.process_group.gather(
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tensor, gather_list, dst_rank_in_group, sync_op, use_calc_stream
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)
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if sync_op:
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task.wait()
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return task
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def gather(
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tensor: Tensor,
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gather_list: Sequence[Tensor] | None = None,
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dst: int = 0,
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group: Group | None = None,
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sync_op: bool = True,
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use_calc_stream: bool = False,
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) -> task | None:
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"""
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Gather tensors from all participators.
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Args:
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tensor (Tensor): The input Tensor. Its data type
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should be float16, float32, float64, int32, int64, int8, uint8, bool or bfloat16.
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gather_list (list|None): A list of Tensors to hold the gathered tensors. Every element in the list must be a Tensor whose data type
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should be float16, float32, float64, int32, int64, int8, uint8, bool or bfloat16. Default value is None.
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dst (int): The dst rank id. Default value is 0.
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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. The default value is True.
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use_calc_stream (bool, optional): Indicate whether the communication is done on calculation stream. If none is given, use false as default. This
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option is designed for high performance demand, be careful to turn it on except you are clearly know its meaning.
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Returns:
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Async work handle,which can be wait on, if async_op is set to True.
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None, if not async_op
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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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>>> gather_list = [] # type: ignore[var-annotated]
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>>> if dist.get_rank() == 0:
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... data = paddle.to_tensor([1, 2, 3])
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... dist.stream.gather(data, gather_list, dst=0)
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>>> else:
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... data = paddle.to_tensor([4, 5, 6])
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... dist.stream.gather(data, gather_list, dst=0)
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>>> print(gather_list)
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>>> # [[1, 2, 3], [4, 5, 6]] (2 GPUs, out for rank 0)
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>>> # [] (2 GPUs, out for rank 1)
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"""
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assert framework.in_dynamic_mode(), (
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"gather doesn't support static graph mode yet."
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)
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if _warn_cur_rank_not_in_group(group):
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return
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if not sync_op and use_calc_stream:
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raise RuntimeError(
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"use_calc_stream can only be true in sync op behavior."
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)
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# NOTE(liuzhenhai): Only the dst rank needs to specific the gather_list argument.
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# Other ranks which pass this argument in will be ignored with a warning.
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# The passed in type for non-dst rank is meaningless, for it will be ignored.
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if dst != dist.get_rank():
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if gather_list is not None:
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warnings.warn(
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"Specific `gather_list` is meaningless for rank which is not dst."
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)
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gather_list = []
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else:
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assert gather_list is not None, (
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"gather_list must not be none for dst rank"
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)
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group = _get_global_group() if group is None else group
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dst_rank_in_group = _get_or_throw_group_rank(dst, group)
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return _gather_in_dygraph(
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tensor, gather_list, dst_rank_in_group, group, sync_op, use_calc_stream
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)
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