ColossalAI/colossalai/shardformer/shard/shard_config.py

62 lines
2.3 KiB
Python

from dataclasses import dataclass
from typing import Optional
import torch.distributed as dist
from torch.distributed import ProcessGroup
from colossalai.pipeline.stage_manager import PipelineStageManager
__all__ = ['ShardConfig']
@dataclass
class ShardConfig:
r"""
The config for sharding the huggingface model
Args:
tensor_parallel_process_group (Optional[ProcessGroup]): The process group for tensor parallelism, defaults to None, which is the global process group.
pipeline_stage_manager (Optional[PipelineStageManager]): The pipeline stage manager, defaults to None, which means no pipeline.
enable_tensor_parallelism (bool): Whether to turn on tensor parallelism, default is True.
enable_fused_normalization (bool): Whether to use fused layernorm, default is False.
enable_all_optimization (bool): Whether to turn on all optimization, default is False.
"""
tensor_parallel_process_group: Optional[ProcessGroup] = None
pipeline_stage_manager: Optional[PipelineStageManager] = None
enable_tensor_parallelism: bool = True
enable_fused_normalization: bool = False
enable_all_optimization: bool = False
enable_flash_attention: bool = False
enable_jit_fused: bool = False
enable_sequence_parallelism: bool = False
# pipeline_parallel_size: int
# data_parallel_size: int
# tensor_parallel_mode: Literal['1d', '2d', '2.5d', '3d']
# inference_only: bool = True
# gather_output: bool = True
@property
def tensor_parallel_size(self):
return self._tensor_parallel_size
def __post_init__(self):
if not self.enable_tensor_parallelism:
self._tensor_parallel_size = 1
else:
# get the parallel size
self._tensor_parallel_size = dist.get_world_size(self.tensor_parallel_process_group)
# turn on all optimization if all_optimization is set to True
if self.enable_all_optimization:
self._turn_on_all_optimization()
def _turn_on_all_optimization(self):
"""
Turn on all optimization.
"""
# you can add all the optimization flag here
self.enable_fused_normalization = True
self.enable_flash_attention = True
self.enable_jit_fused = True
self.enable_sequence_parallelism = True