initialize_model_parallel是模型初始化的重点,定义在megatron/core/parallel_state.py def initialize_model_parallel( tensor_model_parallel_size: int = 1, pipeline_model_parallel_size: int = 1, virtual_pipeline_model_parallel_size: Optional[int] = None, pipeline_model_parallel_split_rank: Optional[in...
pipeline_model_parallel_size, args.virtual_pipeline_model_parallel_size, ) # 设置DeepSpeed ZeRO-R,对activation进行优化 if args.deepspeed and args.deepspeed_activation_checkpointing: setup_deepspeed_random_and_activation_checkpointing(args) 总体来说,这个代码实现了3个目的: 设置分布式环境:初始化进程,...
也就是定好了TP和PP,DP_size就能根据 world_size // (TP_size * PP_size)计算得出。因此不用定义。 我们来看具体代码: definitialize_model_parallel( tensor_model_parallel_size_=1, pipeline_model_parallel_size_=1, virtual_pipeline_model_parallel_size_=None, ):""" Initializemodeldataparallelgroups....
defget_model(model_provider_func):"""Buildthemodel."""args=get_args()#1、定义并构建CPU版模型if(#1.1、当分布式进行框架采用virtualpipeline(是NVDIA后续提出的对Megatron的优化方法,可先忽略不看)mpu.get_pipeline_model_parallel_world_size()>1andargs.virtual_pipeline_model_parallel_sizeisnotNone): mod...
defget_model(model_provider_func): """Build the model.""" args = get_args() # 1、定义并构建CPU版模型 if(# 1.1、当分布式进行框架采用virtual pipeline (是NVDIA后续提出的对Megatron的优化方法,可先忽略不看) mpu.get_pipeline_model_parallel_world_size() >1 ...
pipeline_model_parallel_size: number of GPUs used for pipeline model parallelism. virtual_pipeline_model_parallel_size: number of virtual stages (interleaved pipeline). pipeline_model_parallel_split_rank: for models with both encoder and decoder, ...
NVIDIA Megatron 是一个基于 PyTorch 的分布式训练框架,用来训练超大Transformer语言模型,其通过综合应用了数据并行,Tensor并行和Pipeline并行来复现 GPT3,值得我们深入分析其背后机理。本文将对 Megatron 的基本架构做一下梳理。
_VIRTUAL_PIPELINE_MODEL_PARALLEL_RANK = None _VIRTUAL_PIPELINE_MODEL_PARALLEL_WORLD_SIZE = None _PIPELINE_MODEL_PARALLEL_SPLIT_RANK = None # These values enable us to change the mpu sizes on the fly. _MPU_TENSOR_MODEL_PARALLEL_WORLD_SIZE = None ...
我们首先把 initialize_model_parallel 代码摘录出来。initialize_model_parallel 作用就是对模型进行分组,然后初始化进程组相关的各种全局变量。 代码语言:javascript 复制 def initialize_model_parallel(tensor_model_parallel_size_=1, pipeline_model_parallel_size_=1, virtual_pipeline_model_parallel_size_=None, pi...
测试过程中选择的seqlen是4096,并固定TP(tensor model parallel size)为2,PP(pipeline model parallel size)为1,DP(data parallel size)为4。 同时我们也在NVIDIA前沿GPU卡上对FP8以及FlashAttention-3的收敛稳定性进行了评测。下图中绿线表示FP8和FlashAttention-3开关同时打开,蓝线表示仅开启FlashAttention-3开关,...