object_detection/pt/src/utils/yolod/setup_env.py

# /*---------------------------------------------------------------------------------------------
#  * Copyright (c) 2025 STMicroelectronics.
#  * All rights reserved.
#  *
#  * This software is licensed under terms that can be found in the LICENSE file in
#  * the root directory of this software component.
#  * If no LICENSE file comes with this software, it is provided AS-IS.
#  *--------------------------------------------------------------------------------------------*/
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
# Copyright (c) Megvii Inc. All rights reserved.

import os
import subprocess
from loguru import logger
import torch
import cv2

from .dist import get_world_size, is_main_process
from datetime import timedelta
import torch.distributed as dist

__all__ = ["configure_nccl", "configure_module", "configure_omp", "init_distributed_mode"]


def configure_nccl():
    """Configure multi-machine environment variables of NCCL."""
    os.environ["NCCL_LAUNCH_MODE"] = "PARALLEL"
    os.environ["NCCL_IB_HCA"] = subprocess.getoutput(
        "pushd /sys/class/infiniband/ > /dev/null; for i in mlx5_*; "
        "do cat $i/ports/1/gid_attrs/types/* 2>/dev/null "
        "| grep v >/dev/null && echo $i ; done; popd > /dev/null"
    )
    os.environ["NCCL_IB_GID_INDEX"] = "3"
    os.environ["NCCL_IB_TC"] = "106"


def configure_omp(num_threads=1):
    """
    If OMP_NUM_THREADS is not configured and world_size is greater than 1,
    Configure OMP_NUM_THREADS environment variables of NCCL to `num_thread`.

    Args:
        num_threads (int): value of `OMP_NUM_THREADS` to set.
    """
    # We set OMP_NUM_THREADS=1 by default, which achieves the best speed on our machines
    # feel free to change it for better performance.
    if "OMP_NUM_THREADS" not in os.environ and get_world_size() > 1:
        os.environ["OMP_NUM_THREADS"] = str(num_threads)
        if is_main_process():
            logger.info(
                "\n***************************************************************\n"
                "We set `OMP_NUM_THREADS` for each process to {} to speed up.\n"
                "please further tune the variable for optimal performance.\n"
                "***************************************************************".format(
                    os.environ["OMP_NUM_THREADS"]
                )
            )


def configure_module(ulimit_value=8192):
    """
    Configure pytorch module environment. setting of ulimit and cv2 will be set.

    Args:
        ulimit_value(int): default open file number on linux. Default value: 8192.
    """
    # system setting
    try:
        import resource

        rlimit = resource.getrlimit(resource.RLIMIT_NOFILE)
        resource.setrlimit(resource.RLIMIT_NOFILE, (ulimit_value, rlimit[1]))
    except Exception:
        # Exception might be raised in Windows OS or rlimit reaches max limit number.
        # However, set rlimit value might not be necessary.
        pass

    # cv2
    # multiprocess might be harmful on performance of torch dataloader
    os.environ["OPENCV_OPENCL_RUNTIME"] = "disabled"
    try:
        cv2.setNumThreads(0)
        cv2.ocl.setUseOpenCL(False)
    except Exception:
        # cv2 version mismatch might rasie exceptions.
        pass

def init_distributed_mode(backend="nccl", timeout=timedelta(minutes=30)):
    """
    Initialize torch.distributed using environment variables set by torchrun.
    Returns: rank, world_size, local_rank
    """
    if "RANK" in os.environ and "WORLD_SIZE" in os.environ:
        rank = int(os.environ["RANK"])
        world_size = int(os.environ["WORLD_SIZE"])
        dist.init_process_group(
            backend=backend,
            init_method="env://",
            world_size=world_size,
            rank=rank,
            timeout=timeout,
        )
        # local_rank = int(os.environ["LOCAL_RANK"])
        local_rank = int(os.getenv("LOCAL_RANK", 0))
        torch.cuda.set_device(local_rank)
    else:
        rank = 0
        world_size = 1
        local_rank = 0