chore: import upstream snapshot with attribution
This commit is contained in:
@@ -0,0 +1,166 @@
|
||||
# Copyright (c) 2022 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.
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from paddle import _C_ops, framework
|
||||
from paddle.base import data_feeder
|
||||
from paddle.distributed.communication.group import (
|
||||
_get_global_group,
|
||||
_warn_cur_rank_not_in_group,
|
||||
)
|
||||
from paddle.distributed.communication.reduce import (
|
||||
ReduceOp,
|
||||
_get_reduce_op,
|
||||
_to_inplace_op,
|
||||
)
|
||||
from paddle.framework import in_pir_mode
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from paddle import Tensor
|
||||
from paddle.base.core import task
|
||||
from paddle.distributed.communication.group import Group
|
||||
|
||||
from ..all_reduce import _ReduceOp
|
||||
|
||||
|
||||
def _all_reduce_in_dygraph(
|
||||
tensor: Tensor,
|
||||
op: _ReduceOp,
|
||||
group: Group,
|
||||
sync_op: bool,
|
||||
use_calc_stream: bool,
|
||||
) -> task:
|
||||
op_type = _get_reduce_op(op)
|
||||
|
||||
if use_calc_stream:
|
||||
return group.process_group.all_reduce_on_calc_stream(tensor, op_type)
|
||||
|
||||
task = group.process_group.all_reduce(tensor, op_type, sync_op)
|
||||
if sync_op:
|
||||
task.wait()
|
||||
|
||||
return task
|
||||
|
||||
|
||||
def _all_reduce_in_static_mode(
|
||||
tensor: Tensor,
|
||||
op: _ReduceOp,
|
||||
group: Group,
|
||||
sync_op: bool,
|
||||
use_calc_stream: bool,
|
||||
) -> None:
|
||||
data_feeder.check_variable_and_dtype(
|
||||
tensor,
|
||||
'tensor',
|
||||
[
|
||||
'float16',
|
||||
'float32',
|
||||
'float64',
|
||||
'int32',
|
||||
'int64',
|
||||
'int8',
|
||||
'uint8',
|
||||
'bool',
|
||||
'uint16',
|
||||
],
|
||||
'all_reduce',
|
||||
)
|
||||
|
||||
ring_id = 0 if group is None else group.id
|
||||
|
||||
if not isinstance(ring_id, int):
|
||||
raise ValueError("The type of 'ring_id' for all_reduce should be int.")
|
||||
|
||||
if in_pir_mode():
|
||||
op_type: str = _to_inplace_op(op)
|
||||
_C_ops.all_reduce_(tensor, ring_id, op)
|
||||
return
|
||||
|
||||
# TODO: Support task and use task.wait in static graph mode
|
||||
# Use use_calc_stream rather than sync_op
|
||||
op_type = _get_reduce_op(op)
|
||||
helper = framework.LayerHelper(op_type, **locals())
|
||||
helper.append_op(
|
||||
type=op_type,
|
||||
inputs={'X': [tensor]},
|
||||
outputs={'Out': [tensor]},
|
||||
attrs={'ring_id': ring_id, 'use_calc_stream': sync_op},
|
||||
)
|
||||
|
||||
|
||||
def all_reduce(
|
||||
tensor: Tensor,
|
||||
op: _ReduceOp = ReduceOp.SUM,
|
||||
group: Group | None = None,
|
||||
sync_op: bool = True,
|
||||
use_calc_stream: bool = False,
|
||||
) -> task | None:
|
||||
"""
|
||||
|
||||
Perform specific reduction (for example, sum, max) on inputs across devices.
|
||||
|
||||
Args:
|
||||
tensor (Tensor): The input tensor on each rank. The result will overwrite this tenor after communication. Support
|
||||
float16, float32, float64, int32, int64, int8, uint8 or bool as the input data type.
|
||||
op (ReduceOp.SUM|ReduceOp.MAX|ReduceOp.MIN|ReduceOp.PROD, optional): The reduction used. If none is given, use ReduceOp.SUM as default.
|
||||
group (Group|None, optional): Communicate in which group. If none is given, use the global group as default.
|
||||
sync_op (bool, optional): Indicate whether the communication is sync or not. If none is given, use true as default.
|
||||
use_calc_stream (bool, optional): Indicate whether the communication is done on calculation stream. If none is given, use false as default. This
|
||||
option is designed for high performance demand, be careful to turn it on except you are clearly know its meaning.
|
||||
|
||||
Returns:
|
||||
Return a task object.
|
||||
|
||||
Examples:
|
||||
.. code-block:: pycon
|
||||
|
||||
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
|
||||
>>> import paddle
|
||||
>>> import paddle.distributed as dist
|
||||
|
||||
>>> dist.init_parallel_env()
|
||||
>>> local_rank = dist.get_rank()
|
||||
>>> data = None
|
||||
>>> if local_rank == 0:
|
||||
... data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
|
||||
>>> else:
|
||||
... data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
|
||||
>>> task = dist.stream.all_reduce(data, sync_op=False)
|
||||
>>> task.wait() # type: ignore[union-attr]
|
||||
>>> out = data
|
||||
>>> print(out)
|
||||
[[5, 7, 9], [5, 7, 9]]
|
||||
"""
|
||||
if _warn_cur_rank_not_in_group(group):
|
||||
return
|
||||
|
||||
if not sync_op and use_calc_stream:
|
||||
raise RuntimeError(
|
||||
"use_calc_stream can only be true in sync op behavior."
|
||||
)
|
||||
|
||||
if framework.in_dynamic_mode():
|
||||
group = _get_global_group() if group is None else group
|
||||
return _all_reduce_in_dygraph(
|
||||
tensor, op, group, sync_op, use_calc_stream
|
||||
)
|
||||
else:
|
||||
assert group is None, (
|
||||
"Group can not be used in static graph mode for now."
|
||||
)
|
||||
return _all_reduce_in_static_mode(
|
||||
tensor, op, group, sync_op, use_calc_stream
|
||||
)
|
||||
Reference in New Issue
Block a user