world_size = torch.distributed.get_world_size() # 取得全局进程的个数 else: # 如果未创建好分布式环境 if args.rank == 0: print("> initializing torch distributed ...", flush=True) # 1. 初始化进程,分配GPU,并设置进程大组(group) if device_count > 0: device = args.rank % device_count...
* encoder_pipeline_model_parallel_size * context_parallel_size ) decoder_model_size = ( tensor_model_parallel_size * pipeline_model_parallel_size * context_parallel_size ) total_model_size = encoder_model_size + decoder_model_size if world_size % total_model_size != 0: raise RuntimeError...
num_tensor_model_parallel_groups=world_size//tensor_model_parallel_size#TP的组数num_pipeline_model_parallel_groups=world_size//pipeline_model_parallel_size#PP的组数num_data_parallel_groups=world_size//data_parallel_size#DP的组数ifvirtual_pipeline_model_parallel_size_isnotNone:global_VIRTUAL_PIPELINE_...
另外涉及到experts的分配的时候也需要格外小心。我们对比dense的转换在moe模型的convert脚本中新增了两个参数(expert_model_parallel_size和world_size(总卡数))来对experts的分布进行精细化处理。比如mixtral的experts的总数是8,那么在16张卡有三种转换情况, tp4ep4, tp8ep2, tp2ep8,按照每种情况来分配moe层的权重。
self.output_size = output_size self.gather_output = gather_output# Divide the weight matrix along the last dimension.world_size = get_tensor_model_parallel_world_size()# 获得本tensor并行组的world sizeself.output_size_per_partition = divide(output_size, world_size)# 获得本子模型应输出sizeself...
world_size=get_tensor_model_parallel_world_size()# 更改输入的第一个维度以考虑模型并行的全部大小。 dim_size=list(input.size())dim_size[0]=dim_size[0]*world_size # 收集所有GPU上的输入。 all_gather_buffer=get_global_memory_buffer().get_tensor(dim_size,input.dtype,"mpu")torch.distributed...
WORLD_SIZE=$(($GPUS_PER_NODE*$NNODES)) DATA_PATH=<Specify path and file prefix>_text_sentence CHECKPOINT_PATH=<Specify path> DISTRIBUTED_ARGS="--nproc_per_node $GPUS_PER_NODE --nnodes $NNODES --node_rank $NODE_RANK --master_addr $MASTER_ADDR --master_port $MASTER_PORT" ...
get_pipeline_model_parallel_world_size 获取本流水线组world size数目,就是流水线深度。 defget_pipeline_model_parallel_world_size(): """Returnworldsizeforthepipelinemodelparallelgroup.""" global_MPU_PIPELINE_MODEL_PARALLEL_WORLD_SIZE if_MPU_PIPELINE_MODEL_PARALLEL_WORLD_SIZEisnotNone: return_MPU_PIP...
WORLD_SIZE=$(($GPUS_PER_NODE*$NNODES)) DISTRIBUTED_ARGS="--nproc_per_node$GPUS_PER_NODE--nnodes$NNODES--node_rank$NODE_RANK--master_addr$MASTER_ADDR--master_port$MASTER_PORT" CHECKPOINT_PATH=/workspace/Megatron-LM/experiments/codeparrot-small ...
WORLD_SIZE=$(($GPUS_PER_NODE*$NNODES)) DISTRIBUTED_ARGS="--nproc_per_node$GPUS_PER_NODE--nnodes$NNODES--node_rank$NODE_RANK--master_addr$MASTER_ADDR--master_port$MASTER_PORT" CHECKPOINT_PATH=/workspace/Megatron-LM/experiments/codeparrot-small ...