wehub-resource-sync
272 lines
8.2 KiB
Python
272 lines
8.2 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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import paddle.distributed as dist
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from paddle.distributed.fleet.layers.mpu import RNGStatesTracker
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class StrategyGroupBase:
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"""
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The base class of communication group with distributed strategy.
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Args:
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list_of_ranks: A 2D-array, such as `[[0, 1, 2, 3], [4, 5, 6, 7]]`. Ranks in sublist represents
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they are in the same communication group.
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Returns:
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The instance of strategy group.
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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.distributed as dist
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>>> from paddle.distributed.fleet.base.strategy_group import StrategyGroupBase
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>>> dist.init_parallel_env()
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>>> strategy_group = dist.fleet.base.strategy_group.StrategyGroupBase([[0, 1], [2, 3]])
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>>> print(strategy_group.world_size)
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2
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"""
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def __init__(self, list_of_ranks):
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"""
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Initialize the communication group.
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"""
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assert dist.is_initialized(), (
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"The global communication group need to be initialized."
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)
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assert len(list_of_ranks), "The list_of_ranks can not be empty."
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self._rank = dist.get_rank()
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self._list_of_ranks = list_of_ranks
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self._group = self._create_group()
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self.random_states_tracker = RNGStatesTracker()
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def add_random_seed(self, name, seed):
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"""
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Add random seed for current rank.
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"""
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self.random_states_tracker.add(name, seed)
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def get_random_states_tracker(self):
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"""
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Get the random states tracker.
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"""
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return self.random_states_tracker
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@property
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def world_size(self):
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"""
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The world size of communication group.
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Returns:
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Integer if the world_size of each group are equal, or a list of world_size if they are not equal.
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"""
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world_size_list = []
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for ranks in self._list_of_ranks:
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world_size_list.append(len(ranks))
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is_value = all(
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world_size == world_size_list[0] for world_size in world_size_list
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)
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return world_size_list[0] if is_value else world_size_list
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@property
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def group(self):
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"""
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The communication group which current rank belongs to.
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Returns:
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Group if current rank only belong to single communication group, or a list of Group if it belongs many.
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"""
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return self._group
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def _create_group(self):
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self.list_of_group = []
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for ranks in self._list_of_ranks:
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group = dist.new_group(ranks=ranks)
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if self._rank in ranks:
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self.list_of_group.append(group)
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if not self.list_of_group:
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return None
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else:
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return (
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self.list_of_group[0]
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if len(self.list_of_group) == 1
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else self.list_of_group
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)
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def __repr__(self):
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debug_str = f"seed: {self._seed}; "
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if not self.list_of_group:
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return debug_str + "No group."
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for i in range(len(self.list_of_group)):
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debug_str += f"Group[{i}]: {self.list_of_group[i]}; "
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return debug_str
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class DPGroup(StrategyGroupBase):
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"""
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The communication group strategy for data parallel.
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Args:
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list_of_ranks: A 2D-array, such as `[[0, 1, 2, 3], [4, 5, 6, 7]]`. Ranks in sublist represents
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they are in the same communication group.
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Returns:
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The instance of data parallel strategy group.
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"""
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def __init__(self, list_of_ranks):
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super().__init__(list_of_ranks)
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assert not isinstance(self.group, list), (
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f"Rank {self._rank} belongs to multi dp groups"
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)
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class MPGroup(StrategyGroupBase):
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"""
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The communication group strategy for model parallel.
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Args:
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list_of_ranks: A 2D-array, such as `[[0, 1, 2, 3], [4, 5, 6, 7]]`. Ranks in sublist represents
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they are in the same communication group.
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Returns:
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The instance of model parallel strategy group.
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"""
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def __init__(self, list_of_ranks):
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super().__init__(list_of_ranks)
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assert not isinstance(self.group, list), (
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f"Rank {self._rank} belongs to multi mp groups"
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)
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class ShardingGroup(StrategyGroupBase):
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"""
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The communication group strategy for sharding parallel.
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Args:
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list_of_ranks: A 2D-array, such as `[[0, 1, 2, 3], [4, 5, 6, 7]]`. Ranks in sublist represents
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they are in the same communication group.
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Returns:
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The instance of sharding parallel strategy group.
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"""
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def __init__(self, list_of_ranks):
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super().__init__(list_of_ranks)
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assert not isinstance(self.group, list), (
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f"Rank {self._rank} belongs to multi sharding groups"
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)
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class PPGroup(StrategyGroupBase):
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"""
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The communication group strategy for pipeline parallel.
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Args:
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list_of_ranks: A 2D-array, such as `[[0, 1, 2, 3], [4, 5, 6, 7]]`. Ranks in sublist represents
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they are in the same communication group.
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Returns:
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The instance of pipeline parallel strategy group.
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"""
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def __init__(self, list_of_ranks):
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super().__init__(list_of_ranks)
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assert not isinstance(self.group, list), (
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f"Rank {self._rank} belongs to multi pp groups"
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)
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self._send_next_group = None
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self._send_prev_group = None
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self._recv_next_group = None
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self._recv_prev_group = None
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self._rank_of_next_stage = None
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self._rank_of_prev_stage = None
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if self.world_size > 1:
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self._create_p2p_group()
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@property
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def rank_of_prev_stage(self):
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"""
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Rank of the previous pp stage.
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Returns:
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The global rank of previous pp stage. `None` if without previous.
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"""
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return self._rank_of_prev_stage
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@property
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def rank_of_next_stage(self):
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"""
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Rank of the next pp stage.
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Returns:
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The global rank of next pp stage. `None` if without next.
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"""
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return self._rank_of_next_stage
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@property
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def p2p_groups(self):
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"""
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Communication subgroup in order to switch data with previous and next stage.
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Returns:
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Four subgroups including send/recv to/from prev/next.
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"""
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return (
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self._send_next_group,
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self._send_prev_group,
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self._recv_next_group,
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self._recv_prev_group,
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)
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def _create_p2p_group(self):
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degree = self.world_size
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for ranks in self._list_of_ranks:
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for idx, rank in enumerate(ranks):
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next_rank = ranks[(idx + 1) % degree]
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prev_rank = ranks[(idx - 1) % degree]
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if self._rank == rank:
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self._rank_of_next_stage = next_rank
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self._rank_of_prev_stage = prev_rank
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next_group = dist.new_group(ranks=[rank, next_rank])
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if self._rank == rank:
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self._send_next_group = next_group
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elif self._rank == next_rank:
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self._recv_prev_group = next_group
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prev_group = dist.new_group(ranks=[prev_rank, rank])
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if self._rank == rank:
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self._send_prev_group = prev_group
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elif self._rank == prev_rank:
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self._recv_next_group = prev_group
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assert (
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self._send_next_group
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and self._send_prev_group
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and self._recv_next_group
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and self._recv_prev_group
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), f"Error occurs while creating p2p group for rank {self._rank}."
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