timeout 是一个 datetime.timedelta 对象,用于指定初始化进程组的超时时间。 默认值通常为 datetime.timedelta(seconds=1800),即30分钟。 2. 如何设置 timeout 参数 在调用 torch.distributed.init_process_group 函数时,可以通过 timeout 参数来调整超时时间。例如: python import datetime import torch.distributed as...
torch.distributed.init_process_group rendezvous 获取 store 构造default_pg 其他 前言:书接上回 start workers torchrun 完成Rendezvous 之后便会调用 LocalElasticAgent 类中实现的 _start_workers 方法启动每一个 worker 子进程,即 torchrun 命令最后跟着的 train.py 脚本。_start_workers 把WorkerGroup 中的信息...
torch.distributed.init_process_group(backend,,timeout=datetime.timedelta(0,,,group_name='')[source] Initializes the default distributed process group, and this will also initialize the distributed package. There are 2 main ways to initialize a process group: Specifystore,rank, andworld_sizeexplici...
torch.distributed.init_process_group() #初始化分布式进程组,设置进程之间的通信后端和通信方式。 torch.distributed.init_device_mesh() #初始化设备网格(Device Mesh),用于管理分布式训练中的设备布局。 torch.distributed.is_initialized() #检查分布式进程组是否已经初始化。 torch.distributed.is_nccl_available() ...
如果distributed包能够被使用,这将返回True。 方法二: torch.distributed.init_process_group(backend,init_method=None,timeout=datetime.timedelta(0, 1800),world_size=-1,rank=-1,store=None,group_name='') 初始化默认的分布式进程组,也将会初始化分布式包。
torch.distributed.init_process_group(backend,init_method=None,timeout=datetime.timedelta(0,1800),world_size=-1,rank=-1,store=None,group_name='')[source] 初始化默认的分布式进程组,并且也会初始化分布式包。 There are 2 main ways to initialize a process group: ...
torch.distributed.init_process_group with unspecified backend out of date#147631 New issue OpenDescription tpopp opened on Feb 21, 2025 📚 The doc issue "Support for multiple backends is experimental. Currently when no backend is specified, both gloo and nccl backends will be created." is ...
： nn.DataParallel[1] 简单方便的 nn.DataParallel torch.distributed[2] 使用 torch.distributed 加速...
torch.distributed.init_process_group(backend='nccl', init_method='env://') [W C:\cb\pytorch_1000000000000\work\torch\csrc\distributed\c10d\socket.cpp:601] [c10d] The client socket has failed to connect to [LAPTOP-FB9E7OEP]:12345...
🐛 Describe the bug TRAINING_SCRIPT.py def main(): dist.init_process_group("nccl", init_method='env://') ... if __name__ == "__main__": main() when I run this on both node0 and node1 export LOGLEVEL=INFO && python -m torch.distributed...