torch.cuda.set_device(local_rank) 1. 2. 3. 4. 5. 6. 7. 8. local_rank表示进程的优先级,也可以认为是进程的序列号;MASTER_ADDR和MASTER_PORT分别表示通讯的地址和端口,torch.distributed.launch会将其设置为环境变量;world_size表示gpu*节点数,本例里就是gpu数量。这里代码里print出来展示。 dist.init_...
The backend in torch.distributed.init_process_group set to hccl now.. The torch.cuda.* and torch.cuda.amp.* are replaced with torch.npu.* and torch.npu.amp.* now.. The device parameters have been replaced with npu in the function below: torch.logspace, torch.randint, torch.hann_...
():device = torch.device(f"cuda:{int(os.environ['LOCAL_RANK'])}") torch.cuda.set_device(device) torch.distributed.init_process_group( backend="nccl", )defmain():layer_num = int(sys.argv[1]) init_dist() device ='cuda'model = Model(layer_num) mesh = init_device_mesh( device_...
n_gpu=torch.cuda.device_count()torch.distributed.init_process_group("nccl",world_size=n_gpus,rank=args.local_rank) 1.2.2.2.2 第二步 torch.cuda.set_device(args.local_rank)该语句作用相当于CUDA_VISIBLE_DEVICES环境变量 1.2.2.2.3 第三步 model=DistributedDataParallel(model.cuda(args.local_rank)...
The backend in torch.distributed.init_process_group set to hccl now.. The torch.cuda.* and torch.cuda.amp.* are replaced with torch.npu.* and torch.npu.amp.* now.. The device parameters have been replaced with npu in the function below: torch.logspace, torch.randint, torch.hann_window...
NotImplementedError: Using RTX 3090 or 4000 series doesn't support faster communication broadband via P2P or IB. Please setNCCL_P2P_DISABLE="1"andNCCL_IB_DISABLE="1" or useaccelerate launch` which will do this automatically. 解决:一行一行的执行如下代码: ...
local_rank=0 torch.cuda.set_device(local_rank) cuda(0)默认是第0块显卡, 但是设置CUDA_VISIBLE_DEVICES后: cuda(0)就是CUDA_VISIBLE_DEVICES里面的第一个gpu。 distributed.init报错outof memory importargparse importlogging importos importtime importtorch ...
True # Environment device: cuda dtype: bf16 # Activations Memory enable_activation_checkpointing: True # True reduces memory enable_activation_offloading: False # True reduces memory # Show case the usage of pytorch profiler # Set enabled to False as it's only needed for debugging training prof...
local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}, distributed training: {bool(training_args.local_rank != -1)}, fp16-bits training: {training_args.fp16}, bf16-bits training: {training_args.bf16}" ) logger.info(f"Training/evaluation parameters {training_args...
一、问题现象(附报错日志上下文): 目前cann版本是6.3.RC2,pytorch-npu版本是1.11.0,之前在cuda环境下一个模型采用单机多卡的方式(torch.nn.DataParallel),现在参照官网示例采用hccl: torch.distributed.init_process_group(backend="nccl",rank=args.local_rank,world_size=1) 加载模型时采用: net = torch.nn....