tools/multi_thread/distributed.py

# Copyright (c) Facebook, Inc. and its affiliates.

# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.

import os
import subprocess
from dataclasses import dataclass
import torch.distributed as dist


@dataclass(frozen=True, repr=True, eq=True, unsafe_hash=True)
class DistributedContext:
    is_distributed: bool
    rank: int
    local_rank: int
    world_size: int
    mode: str

    @property
    def is_leader(self) -> bool:
        return self.rank == 0


def init_distributed_context(port: int) -> DistributedContext:
    # Sometimes the nccl backend hangs on the barrier op (https://github.com/pytorch/pytorch/issues/53658).
    # Since it is the only op we care about here, we'd use the gloo backend.
    BACKEND = "gloo"

    # default, non-distributed context
    context = DistributedContext(
        is_distributed=False, rank=0, local_rank=0, world_size=1, mode="none"
    )

    launch_keys = ["MASTER_ADDR", "MASTER_PORT", "WORLD_SIZE", "RANK", "LOCAL_RANK"]
    slurm_keys = [
        "SLURM_LOCALID",
        "SLURM_PROCID",
        "SLURM_NTASKS",
        "SLURM_NODEID",
        "SLURM_JOB_NODELIST",
    ]

    # is it torch.distributed.launch?
    if all(key in os.environ for key in launch_keys):
        init_method = "env://"
        world_size = int(os.environ["WORLD_SIZE"])
        rank = int(os.environ["RANK"])
        local_rank = int(os.environ["LOCAL_RANK"])
        context = DistributedContext(
            is_distributed=True,
            rank=rank,
            world_size=world_size,
            local_rank=local_rank,
            mode="launch",
        )
        dist.init_process_group(
            backend=BACKEND, init_method=init_method, world_size=world_size, rank=rank
        )
    # is it slurm?
    elif all(key in os.environ for key in slurm_keys):
        init_method = "env://"
        local_rank = int(os.environ["SLURM_LOCALID"])
        rank = int(os.environ["SLURM_PROCID"])
        world_size = int(os.environ["SLURM_NTASKS"])

        hostnames = subprocess.check_output(
            ["scontrol", "show", "hostnames", os.environ["SLURM_JOB_NODELIST"]]
        )
        leader_addr = hostnames.split()[0].decode("utf-8")

        os.environ["MASTER_ADDR"] = leader_addr
        os.environ["MASTER_PORT"] = str(port)
        os.environ["WORLD_SIZE"] = str(world_size)
        os.environ["RANK"] = str(rank)

        context = DistributedContext(
            is_distributed=True,
            rank=rank,
            local_rank=local_rank,
            world_size=world_size,
            mode="slurm",
        )
        dist.init_process_group(
            backend=BACKEND,
            init_method=init_method,
            world_size=world_size,
            rank=rank,
        )

    return context