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group.py
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group.py
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# 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.
import warnings
import paddle
import paddle.distributed as dist
from paddle import framework
class Group:
"""
The abstract representation of group.
"""
def __init__(self, rank_in_group, id, ranks, pg=None, name=None):
self._rank_in_group = rank_in_group
self._world_size = len(ranks) if rank_in_group >= 0 else -1
self._id = id
self._ranks = ranks
self._pg = pg
self._name = name
@property
def rank(self):
return self._rank_in_group
@property
def ranks(self):
return self._ranks
@property
def nranks(self):
return len(self._ranks)
@property
def name(self):
return self._name
@property
def process_group(self):
return self._pg
@property
def world_size(self):
return self._world_size
@property
def backend(self):
return self._pg.name()
@property
def id(self):
return self._id
def is_member(self):
if self.rank < 0:
return False
if self.nranks < 2:
return False
return True
def get_group_rank(self, rank):
if self.is_member():
return self.ranks.index(rank)
else:
return -1
def __repr__(self):
debug_str = "rank: {}, nranks: {}, id: {}, ranks: ".format(
self.rank, self.nranks, self.id
)
debug_str += ", ".join(map(str, self.ranks))
debug_str += "; name: "
debug_str += self.name if self.name else "None"
return debug_str
class _GroupManager:
global_group_id = 0
group_map_by_id = {}
def _get_global_group():
if _GroupManager.global_group_id not in _GroupManager.group_map_by_id:
raise RuntimeError("The global group is not initialized.")
return _GroupManager.group_map_by_id[_GroupManager.global_group_id]
def _add_new_group(group):
if group.id in _GroupManager.group_map_by_id:
raise RuntimeError(f"The group with id {group.id} already exist.")
_GroupManager.group_map_by_id[group.id] = group
def _is_global_group(group):
return group.id == _GroupManager.global_group_id
def _warn_cur_rank_not_in_group(group):
global_rank = dist.get_rank()
if group and not group.is_member():
warnings.warn(
"Current global rank {} is not in group {}".format(
global_rank, group.name
)
)
return True
return False
def _get_or_throw_group_rank(global_rank, group):
group_rank = group.get_group_rank(global_rank)
assert (
group_rank >= 0
), "The input rank {} can not be found inside the group {}".format(
global_rank, group.name
)
return group_rank
def is_initialized():
"""
Check whether the distributed environment has been initialized
Returns:
`True` if distributed environment has been initialized, otherwise `False`.
Warning:
This API only supports the dygraph mode.
Examples:
.. code-block:: python
# required: distributed
import paddle
print(paddle.distributed.is_initialized())
# False
paddle.distributed.init_parallel_env()
print(paddle.distributed.is_initialized())
# True
"""
return _GroupManager.global_group_id in _GroupManager.group_map_by_id
def destroy_process_group(group=None):
"""
Destroy a given group for communication
Args:
group (Group, optional): The group to be destroyed. All of process groups, including
the default group, will be destroyed and the distributed
environment will be deinitialized.
Returns : None
Warning:
This API only supports the dygraph mode.
Examples:
.. code-block:: python
# required: distributed
import paddle
import paddle.distributed as dist
dist.init_parallel_env()
group = dist.new_group([0, 1])
dist.destroy_process_group(group)
print(dist.is_initialized())
# True
dist.destroy_process_group()
print(dist.is_initialized())
# False
"""
group = _get_global_group() if group is None else group
assert (
group.id in _GroupManager.group_map_by_id
), f"Destroy group with id {group.id} is invalid."
if _is_global_group(group):
_GroupManager.group_map_by_id.clear()
else:
del _GroupManager.group_map_by_id[group.id]
def get_group(id=0):
"""
Get group instance by group id.
Args:
id (int): the group id. Default value is 0.
Returns:
Group: the group instance.
Examples:
.. code-block:: python
# required: distributed
import paddle
import paddle.distributed as dist
dist.init_parallel_env()
gid = paddle.distributed.new_group([2,4,6])
paddle.distributed.get_group(gid.id)
"""
if id in _GroupManager.group_map_by_id:
return _GroupManager.group_map_by_id[id]
warnings.warn(f"Group {id} is not initialized.")
return None
def _sync_calc_stream(tensor):
if framework.in_dynamic_mode():
return paddle._legacy_C_ops.c_sync_calc_stream(tensor, tensor)
else:
op_type = 'c_sync_calc_stream'
helper = framework.LayerHelper(op_type, **locals())
helper.append_op(
type=op_type,
inputs={'X': [tensor]},
outputs={'Out': [tensor]},
)
def _sync_comm_stream(tensor, ring_id=0):
if framework.in_dynamic_mode():
return paddle._legacy_C_ops.c_sync_comm_stream(
[tensor], [tensor], 'ring_id', ring_id
)
else:
op_type = 'c_sync_comm_stream'
helper = framework.LayerHelper(op_type, **locals())
helper.append_op(
type=op_type,
inputs={'X': [tensor]},
outputs={'Out': [tensor]},
attrs={'ring_id': ring_id},
)
def wait(tensor, group=None, use_calc_stream=True):
"""
wait to sync stream for group.
Args:
tensor (Tensor): The Tensor used before sync.
group (Group): The Group instance to perform sync.
use_calc_stream (bool): Wether to use calculation stream (True) or communication stream (False).
Default to True.
Returns:
None.
Examples:
.. code-block:: python
import paddle
paddle.distributed.init_parallel_env()
tindata = paddle.randn(shape=[2, 3])
paddle.distributed.all_reduce(tindata, sync_op=True)
paddle.distributed.wait(tindata)
"""
if group is not None and not group.is_member():
return
if use_calc_stream:
_sync_calc_stream(tensor)
else:
ring_id = 0 if group is None else group.id
_sync_comm_stream(tensor, ring_id)
def barrier(group=None):
"""
Barrier among all participators in the group.
Args:
group (Group): The group instance return by new_group or None for global default group.
Returns:
None.
Examples:
.. code-block:: python
import paddle
from paddle.distributed import init_parallel_env
paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
init_parallel_env()
paddle.distributed.barrier()
"""
if group is not None and not group.is_member():
return
if framework.in_dynamic_mode():
group = _get_global_group() if group is None else group
place = framework._current_expected_place()
if isinstance(place, framework.CPUPlace):
task = group.process_group.barrier()
else:
device_id = place.get_device_id()
task = group.process_group.barrier(device_id)
task.wait()
return
ring_id = 0 if group is None else group.id
barrier_tensor = paddle.full([1], 1, dtype="int32")
if framework.in_dynamic_mode():
return paddle._legacy_C_ops.barrier(
barrier_tensor, barrier_tensor, 'ring_id', ring_id
)
else:
op_type = 'barrier'
if not isinstance(ring_id, int):
raise ValueError("The type of 'group' for barrier must be int.")
helper = framework.LayerHelper(op_type, **locals())
helper.append_op(
type=op_type,
inputs={'X': [barrier_tensor]},
outputs={'Out': [barrier_tensor]},
attrs={'ring_id': ring_id},
)
def get_backend(group=None):
"""
Get the backend of given group.
Args:
group (Group): The group to work on. Use the global group as default.
Returns:
Returns the name of the given group backend.
Examples:
.. code-block:: python
# required: distributed
import paddle
paddle.distributed.init_parallel_env()
paddle.distributed.get_backend() # NCCL
"""
if _warn_cur_rank_not_in_group(group):
raise RuntimeError("Invalid group specified")
group = _get_global_group() if group is None else group
return group.backend