TORCHELASTIC_RESTART_COUNT - The number of worker group restarts so far. MASTER_PORT - The port on the MASTER_ADDR that can be used to host the C10d TCP store. MASTER_ADDR - The FQDN of the host that is running worker with rank 0 used to initialize ROLE_WORLD_SIZE - The total number of workers that was launched with the same role specified WORLD_SIZE - The world size (total number of workers in the job). number of workers running locally) equals to
LOCAL_WORLD_SIZE - The local world size (e.g. Of the worker is specified in the WorkerSpec. ROLE_RANK - The rank of the worker across all the workers that have the same role. Running a single worker group per node, this is the rank of the node. GROUP_RANK - The rank of the worker group. The following environment variables are made available to you in your script: The union ofĪll LocalWorkerGroups in the nodes in the job comprise the WorkerGroup. Ī Node runs LOCAL_WORLD_SIZE workers which comprise a LocalWorkerGroup. Rdzv_endpoint - The rendezvous backend endpoint usually in form. Rdzv_backend - The backend of the rendezvous (e.g. Used by each node to join as a member of a particular worker group. Rdzv_id - A user-defined id that uniquely identifies the worker group for a job. LOCAL_WORLD_SIZE - The size of the local worker group. LOCAL_RANK - The rank of the worker within a local worker group. WORLD_SIZE - The total number of workers in a worker group. RANK - The rank of the worker within a worker group. LocalWorkerGroup - A subset of the workers in the worker group running on the same node. WorkerGroup - The set of workers that execute the same function (e.g. Worker - A worker in the context of distributed training. Node - A physical instance or a container maps to the unit that the job manager works with. Extending torch.func with autograd.Functionįor etcd-based rendezvous we recommend using etcd-v2 over etcd which is functionallyĮquivalent, but uses a revised implementation.CPU threading and TorchScript inference.CUDA Automatic Mixed Precision examples.
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