Jetson Xavier NX上でSimSiamとCIFAR-10で表現学習をやってみた(2) facebookreseach github main関数の変更

こちらは「Jetson Xavier NX上でSimSiamとCIFAR-10で表現学習をやってみた facebookresearch github引数部分の変更(1)」の続きになります

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目次

スポンサーリンク

1.実行環境

Jetson Xavier NX
ubuntu18.04
docker
python3.x
pytorch

->Jetson Xavier NX上におけるpytrorch環境構築は以下でやってますので、ご参考までに(^^)/

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2.コード変更

2.1 main関数変更

元のコードのマルチプロセス部分をコメントアウトしてmain_workerを呼び出すように変更

def main():
    args = parser.parse_args()

    if args.seed is not None:
        random.seed(args.seed)
        torch.manual_seed(args.seed)
        cudnn.deterministic = True
        warnings.warn('You have chosen to seed training. '
                      'This will turn on the CUDNN deterministic setting, '
                      'which can slow down your training considerably! '
                      'You may see unexpected behavior when restarting '
                      'from checkpoints.')

    if args.gpu is not None:
        warnings.warn('You have chosen a specific GPU. This will completely '
                      'disable data parallelism.')
    # ここから---------------------------------------------------------------------------------------------
    #if args.dist_url == "env://" and args.world_size == -1:
        #args.world_size = int(os.environ["WORLD_SIZE"])
    #args.distributed = args.world_size > 1 or args.multiprocessing_distributed
    #ngpus_per_node = torch.cuda.device_count()
    #if args.multiprocessing_distributed:
        # Since we have ngpus_per_node processes per node, the total world_size
        # needs to be adjusted accordingly
        #args.world_size = ngpus_per_node * args.world_size
        # Use torch.multiprocessing.spawn to launch distributed processes: the
        # main_worker process function
        #mp.spawn(main_worker, nprocs=ngpus_per_node, args=(ngpus_per_node, args))
    else:
        # Simply call main_worker function
        #main_worker(args.gpu, ngpus_per_node, args)
    # ここまでコメントアウト---------------------------------------------------------------------------

    # ここから---------------------------------------------------------------------------------------------
    ngpus_per_node = torch.cuda.device_count()
    main_worker(args.gpu, ngpus_per_node, args)
    # ここまで追加----------------------------------------------------------------------------------------

※(3)に続きます

参考

github.com スポンサーリンク