🚀 The feature, motivation and pitch For a symmetry with torch.distributed.get_global_rank it would be useful to add torch.distributed.get_local_rank rather than have the user fish for it in the LOCAL_RANK env var. This feature is almost ...
local_rank指在一个node上进程的相对序号,local_rank在node之间相互独立 WORLD_SIZE全局进程总个数,即在一个分布式任务中rank的数量 Group进程组,一个分布式任务对应了一个进程组。只有用户需要创立多个进程组时才会用到group来管理,默认情况下只有一个group 如下图所示,共有3个节点(机器),每个节点上有4个GPU,每...
1、local_rank = int(os.environ.get("LOCAL_RANK", -1)) - 在多卡训练场景下，存在多个进程，每个进程利用一张GPU进行训练。此代码用于获取某个进程使用的GPU编号。四卡训练时，四个进程的local_rank分别对应0、1、2和3。2、dist.init_process_group(backend="nccl") - 多卡训练前需执行初始...
举个栗子 : 4台机器 (每台机器8张卡) 进行分布式训练。通过 init_process_group() 对进程组进行初始化。 初始化后 可以通过 get_world_size() 获取到 world size = 32。在该例中为32, 即有32个进程,其编号为0-31通过 get_rank() 函数可以进行获取 在每台机器上,local rank均为0-8, 这是 local ra...
+ifenable_torchacc_compiler(): + dist.init_process_group(backend="xla", init_method="env://") + device = xm.xla_device() + xm.set_replication(device, [device]) +else: args.local_rank =int(os.environ["LOCAL_RANK"]) device = torch.device(f"cuda:{args.local_rank}") dist....
local_rank = args.local_rank 1. 2. 3. 获取到local_rank后, 我们可以对模型进行初始化或加载等操作, 注意这里torch.load()要添加map_location参数, 否则可能导致读取进来的数据全部集中在0卡上. 模型构建完以后, 再将模型转移到DDP上: torch.cuda.set_device(local_rank) ...
+if args.device == "xla": + device = xm.xla_device() + xm.set_replication(device, [device]) + train_device_loader = pl.MpDeviceLoader(train_device_loader, device) + model = model.to(device) +else: device = torch.device(f"cuda:{args.local_rank}") torch.cuda.set_device(device)...
def_mp_fn(rank,world_size):...-os.environ['MASTER_ADDR']='localhost'-os.environ['MASTER_PORT']='12355'-dist.init_process_group("gloo",rank=rank,world_size=world_size)+# Rank and world size are inferred from theXLAdevice runtime+dist.init_process_group("xla",init_method='xla://'...
(args.local_rank), label.to(args.local_rank) optimizer.zero_grad() prediction = model(data) loss = loss_func(prediction, label.unsqueeze(1)) loss.backward() optimizer.step() if dist.get_rank() == 0: torch.save(model.module.state_dict(), "model.pth") if __name__ == "__main_...
The module torch.distributed.launch is deprecated and will be removed in future. Use torchrun. Note that --use_env is set by default in torchrun. If your script expects `--local_rank` argument to be set, please change it to read from `os.environ['LOCAL_RANK']` instead. See https:...