针对你遇到的错误 "error initializing torch.distributed using env:// rendezvous: environment variable rank expected, but not set",以下是一些详细的解答和建议: 1. 理解错误信息 错误信息表明,在使用 PyTorch 的分布式训练功能时,初始化过程中遇到了问题。具体来说,通过环境变量(env://)进行集合(rendezvous)...
def __init__(self, dataset, num_replicas=None, rank=None, shuffle=True): if num_replicas is None: if not dist.is_available(): raise RuntimeError("Requires distributed package to be available") num_replicas = dist.get_world_size() if rank is None: if not dist.is_available(): raise...
local_rank` argument to be set, please change it to read from `os.environ['LOCAL_RANK']` instead. See https://pytorch.org/docs/stable/distributed.html#launch-utility for further instructions warnings.warn( WARNING:torch.distributed.run: *** Setting OMP_NUM_THREADS environment variable for eac...
按照马佬的建议,此处如果不想用到cpu的话,也可以map_location=rank。具体的写法参考了《pytorch源码》以及《pytorch 分布式训练 distributed parallel 笔记》 # 获取GPU的rank号 gpu = torch.distributed.get_rank(group=group) # group是可选参数,返回int,执行该脚本的进程的rank # 获取了进程号后 rank = 'cuda...
DistributedDataParallel 调试 总结 简介 PyTorch 2.0 的使命是更快、更 Pythonic 以及一如既往地支持动态特性。为了达到这个目的,PyTorch 2.0 引入了torch.compile,在解决 PyTorch 固有的性能问题的同时,把部分用 C++ 实现的东西引入 Python 中。PyTorch 2.0 利用了 4 个组件: TorchDynamo,AOTAutograd,PrimTorch和Torch...
运行Huggingface权重转换到Megatron-LM格式的脚本bash examples/llama2/ckpt_convert_llama2_hf2legacy.sh时出现了如下报错: ImportError: /home/ma-user/anaconda3/envs/fbig/lib/python3.8/site-packages/torch_npu/dynamo/torchair/core/_abi_compat_ge_apis.so: undefined symbol: _ZN2ge5Graph28LoadFromSeriali...
torch/distributed/run.py ifargs.rdzv_backend=="static":rdzv_configs["rank"]=args.node_rank 如果没有指定--node_rank参数,在构造 rdzd_handler 时则会直接报错退出: torch/distributed/elastic/rendezvous/static_tcp_rendezvous.py defcreate_rdzv_handler(params:RendezvousParameters)->RendezvousHandler:...
['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_type='cuda', mesh_shape=(dist.get_world_size(),...
🚀 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 ...
1.2.2 方式二:torch.nn.parallel.DistributedDataParallel(推荐) 1.2.2.1 多进程执行多卡训练,效率高 1.2.2.2 代码编写流程 1.2.2.2.1 第一步 n_gpu=torch.cuda.device_count()torch.distributed.init_process_group("nccl",world_size=n_gpus,rank=args.local_rank) ...