Function add_generic_args

examples/lightning_base.py:235–273

(parser, root_dir)

def add_generic_args(parser, root_dir) -> None:
    #  TODO(SS): allow all pl args? parser = pl.Trainer.add_argparse_args(parser)
    parser.add_argument(
        "--output_dir",
        default=None,
        type=str,
        required=True,
        help="The output directory where the model predictions and checkpoints will be written.",
    )

    parser.add_argument(
        "--fp16",
        action="store_true",
        help="Whether to use 16-bit (mixed) precision (through NVIDIA apex) instead of 32-bit",
    )

    parser.add_argument(
        "--fp16_opt_level",
        type=str,
        default="O1",
        help="For fp16: Apex AMP optimization level selected in ['O0', 'O1', 'O2', and 'O3']."
        "See details at https://nvidia.github.io/apex/amp.html",
    )
    parser.add_argument("--fast_dev_run", action="store_true")
    parser.add_argument("--gpus", type=int, default=1)
    parser.add_argument("--n_tpu_cores", type=int, default=0)
    parser.add_argument("--max_grad_norm", default=1.0, type=float, help="Max gradient norm.")
    parser.add_argument("--do_train", action="store_true", help="Whether to run training.")
    parser.add_argument("--do_predict", action="store_true", help="Whether to run predictions on the test set.")
    parser.add_argument(
        "--gradient_accumulation_steps",
        type=int,
        default=1,
        help="Number of updates steps to accumulate before performing a backward/update pass.",
    )

    parser.add_argument("--seed", type=int, default=42, help="random seed for initialization")
    parser.add_argument("--resume_from_checkpoint", type=str, default=None)
    parser.add_argument("--val_check_interval", default=1.0, type=float)


def generic_train(