1.2.1 PipelineModule(layers=join_layers(net),..) - Setup world info - Initialize partition information Setup world info: # # dist.new_group() 将 RANK 实例放入一个组中 self.world_group = dist.new_group(ranks=range(dist.get_world_size())) self.global_rank = dist.get_rank(group=self....
world_size = dist.get_world_size self.global_rank = dist.get_rank() # 3. ZERO 最核心的部分:建立 optimizer # self.optimizer = self._configure_zero_optimizer(optimizer=None) if zero_stage <= ZeroStageEnum.gradients: # zero1 or zero2 optimizer = DeepSpeedZeroOptimizer( optimizer , dp_...
worker-0: nnodes=1, num_local_procs=1, node_rank=0 worker-0: global_rank_mapping=defaultdict(, {'worker-0': [0]}) worker-0: dist_world_size=1 worker-0: Setting CUDA_VISIBLE_DEVICES=0 worker-0: Files already downloaded and verified worker-0: Files already downloaded and verified wo...
对于dist.init_process_group("gloo", rank=rank, world_size=world_size)用于初始化每个进程的通信组。初始化进程组后,每个进程都会知道其他所有进程,并可以与它们进行通信。这对于分布式训练至关重要,因为它允许进程之间同步和交换数据,如模型参数、梯度等。
当world_size=1 时相当于只使用了一个GPU,其延时结果如下,与原始版本相比性能提高了62.6%: DS model: P95 latency (ms) - 1482.9604600323364; Average latency (ms) - 1482.22 +- 0.51; 当world_size=4 时并使用deepspeed --num_gpus 4 test.py运行代码,此时使用了4块 GPU,性能如下所示,延时约为 单GPU...
gzxj-sys-rpm04ejelea: cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size) gzxj-sys-rpm04ejelea: File "/opt/conda/lib/python3.8/site-packages/deepspeed/comm/torch.py", line 60, in init gzxj-sys-rpm04ejelea: self.init_process_group(backend, timeout, init_method...
importtorchimporttorch.distributedasdistimporttorch.nnasnnimporttorch.multiprocessingasmpdeftrain(rank,world_size):dist.init_process_group("nccl",rank=rank,world_size=world_size)model=nn.Linear(10,10).cuda(rank)model=nn.parallel.DistributedDataParallel(model,device_ids=[rank])optimizer=torch.optim.SGD...
mpu – 可选:一个实现以下方法的对象:get_model_parallel_rank/group/world_size 和 get_data_parallel_rank/group/world_size。 deepspeed_config – 可选:当提供DeepSpeed配置JSON文件时,将用于配置DeepSpeed激活检查点。 partition_activations – 可选:启用后在模型并行GPU之间Partitions activation checkpoint。默认...
num_local_procs=2, node_rank=0 [2023-08-22 13:32:36,171] [INFO] [launch.py:162:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0, 1]}) [2023-08-22 13:32:36,171] [INFO] [launch.py:163:main] dist_world_size=2 [2023-08-22 13:32:36,171] [INFO]...
专门吐槽一下文档。get started 这里上来就是 world_size, local_rank 没有解释。文档里似乎急于说明用...