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# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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 typing import List
class Mapping(object):
'''
A node with 8 GPUs, tp_size = 4, pp_size = 2
2 tp groups:
- [0, 1, 2, 3]
- [4, 5, 6, 7]
4 pp groups:
- [0, 4]
- [1, 5]
- [2, 6]
- [3, 7]
A node with 8 GPUs, moe_tp_size = 2, moe_ep_size = 4
4 moe_tp groups:
- [0, 4]
- [1, 5]
- [2, 6]
- [3, 7]
2 moe_ep groups:
- [0, 1, 2, 3]
- [4, 5, 6, 7]
2 nodes with 16 GPUs, moe_tp_size = 2, moe_ep_size = 4, pp_size = 2
8 moe_tp groups:
- [0 4]
- [1 5]
- [2 6]
- [3 7]
- [8 12]
- [9 13]
- [10 14]
- [11 15]
4 moe_ep groups:
- [0, 1, 2, 3]
- [4, 5, 6, 7]
- [8, 9, 10, 11]
- [12, 13, 14, 15]
8 pp groups:
- [0 8]
- [1 9]
- [2 10]
- [3 11]
- [4 12]
- [5 13]
- [6 14]
- [7 15]
'''
def __init__(
self,
world_size=1,
rank=0,
gpus_per_node=8,
tp_size=1,
pp_size=1,
moe_tp_size=-1, # -1 means no moe
moe_ep_size=-1): # -1 means no moe
# set default values for non-moe cases
if moe_tp_size == -1:
moe_tp_size = tp_size
moe_ep_size = 1
if pp_size * tp_size != world_size:
raise ValueError(
f"world_size must equal to pp_size * tp_size, but got {world_size} != {pp_size} * {tp_size}"
)
moe_tp_ep_size = moe_tp_size * moe_ep_size
if moe_tp_ep_size != tp_size:
raise ValueError(
f"tp_size must equal to moe_tp_size * moe_ep_size, but got {tp_size} != {moe_tp_size} * {moe_ep_size}"
)
self.tp_size = tp_size
self.pp_size = pp_size
self.moe_tp_size = moe_tp_size
self.moe_ep_size = moe_ep_size
self.world_size = world_size
self.rank = rank
self.gpus_per_node = gpus_per_node
self.pp_groups = []
self.tp_groups = []
self.moe_tp_groups = []
self.moe_ep_groups = []
# init pp group
for i in range(tp_size):
ranks = range(i, world_size, tp_size)
self.pp_groups.append(list(ranks))
# init tp group
for i in range(pp_size):
ranks = range(i * tp_size, (i + 1) * tp_size)
self.tp_groups.append(list(ranks))
# init moe tp group
for i in range(pp_size):
for j in range(moe_ep_size):
ranks = range(i * moe_tp_ep_size + j, (i + 1) * moe_tp_ep_size,
moe_ep_size)
self.moe_tp_groups.append(list(ranks))
# init moe ep group
for i in range(pp_size):
for j in range(moe_tp_size):
ranks = range(i * moe_tp_ep_size + j * moe_ep_size,
i * moe_tp_ep_size + (j + 1) * moe_ep_size)
self.moe_ep_groups.append(list(ranks))
self.pp_rank = self.rank // self.tp_size
self.tp_rank = self.rank % self.tp_size
self.moe_tp_rank = self.tp_rank // self.moe_ep_size
self.moe_ep_rank = self.tp_rank % self.moe_ep_size
self.tp_group = self.tp_groups[self.pp_rank]
self.pp_group = self.pp_groups[self.tp_rank]
self.moe_tp_group = self.moe_tp_groups[self.pp_rank * moe_ep_size +
self.moe_ep_rank]
self.moe_ep_group = self.moe_ep_groups[self.pp_rank * moe_tp_size +
self.moe_tp_rank]
self.node_rank = self.rank // self.gpus_per_node
self.local_rank = self.rank % self.gpus_per_node
def get_node_rank(self, rank: int):
return rank // self.gpus_per_node
def get_local_rank(self, rank: int):
return rank % self.gpus_per_node
def has_tp(self):
return self.tp_size > 1
def is_last_pp_rank(self):
return self.pp_rank == self.pp_size - 1
def is_first_pp_rank(self):
return self.pp_rank == 0
def has_pp(self):
return self.pp_size > 1
def prev_pp_rank(self):
p = self.rank - self.tp_size
if p < 0:
p = p + self.world_size
return p
def next_pp_rank(self):
p = self.rank + self.tp_size
if p >= self.world_size:
p = p - self.world_size
return p
def has_moe_tp(self):
return self.moe_tp_size > 1
def has_moe_ep(self):
return self.moe_ep_size > 1
def pp_layers(self, num_layers: int) -> List[int]:
layers_per_pipeline_stage = num_layers // self.pp_size
layers_range = range(self.pp_rank * layers_per_pipeline_stage,
(self.pp_rank + 1) * layers_per_pipeline_stage)
return list(layers_range)
def ep_experts(self, num_experts: int) -> List[int]:
experts_per_rank = num_experts // self.moe_ep_size
experts_range = range(self.moe_ep_rank * experts_per_rank,
(self.moe_ep_rank + 1) * experts_per_rank)
return list(experts_range)
@classmethod
def from_dict(cls, mapping: dict):
return cls(**mapping)
def to_dict(self):
return {
'world_size': self.world_size,
'rank': self.rank,
'gpus_per_node': self.gpus_per_node,
'tp_size': self.tp_size,
'pp_size': self.pp_size,
'moe_tp_size': self.moe_tp_size,
'moe_ep_size': self.moe_ep_size
}
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