distributed_training/train_pytorch_single_maskrcnn.py [213:258]:
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    parser.add_argument(
        "--seed",
        help="manually set random seed for torch",
        type=int,
        default=99
    )
    parser.add_argument(
        "--skip-test",
        dest="skip_test",
        help="Do not test the final model",
        action="store_true",
    )
    parser.add_argument(
        "opts",
        help="Modify config options using the command-line",
        default=None,
        nargs=argparse.REMAINDER,
    )
    parser.add_argument(
        "--bucket-cap-mb",
        dest="bucket_cap_mb",
        help="specify bucket size for SMDataParallel",
        default=25,
        type=int,
    )
    parser.add_argument(
        "--data-dir",
        dest="data_dir",
        help="Absolute path of dataset ",
        type=str,
        default=None
    )
    parser.add_argument(
        "--dtype",
        dest="dtype"
    )
    parser.add_argument(
        "--spot_ckpt",
        default=None
    )


    args = parser.parse_args()
    keys = list(os.environ.keys())
    args.data_dir = os.environ['SM_CHANNEL_TRAIN'] if 'SM_CHANNEL_TRAIN' in keys else args.data_dir
    print("dataset dir: ", args.data_dir)
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distributed_training/train_pytorch_smdataparallel_maskrcnn.py [230:275]:
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    parser.add_argument(
        "--seed",
        help="manually set random seed for torch",
        type=int,
        default=99
    )
    parser.add_argument(
        "--skip-test",
        dest="skip_test",
        help="Do not test the final model",
        action="store_true",
    )
    parser.add_argument(
        "opts",
        help="Modify config options using the command-line",
        default=None,
        nargs=argparse.REMAINDER,
    )
    parser.add_argument(
        "--bucket-cap-mb",
        dest="bucket_cap_mb",
        help="specify bucket size for SMDataParallel",
        default=25,
        type=int,
    )
    parser.add_argument(
        "--data-dir",
        dest="data_dir",
        help="Absolute path of dataset ",
        type=str,
        default=None
    )
    parser.add_argument(
        "--dtype",
        dest="dtype"
    )
    parser.add_argument(
        "--spot_ckpt",
        default=None
    )


    args = parser.parse_args()
    keys = list(os.environ.keys())
    args.data_dir = os.environ['SM_CHANNEL_TRAIN'] if 'SM_CHANNEL_TRAIN' in keys else args.data_dir
    print("dataset dir: ", args.data_dir)
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