def init_argparse()

in run_experiments_real.py [0:0]

• 56 lines of code
• 1 McCabe index (conditional complexity)

def init_argparse() -> argparse.ArgumentParser:
    parser = argparse.ArgumentParser(
        usage="python run_experiments --cluster",
        description="runs experiments with specified parameters",
    )
    parser.add_argument("name", help="name of experiment")
    parser.add_argument(
        "--model",
        help="model for experiments. Example: autoencoder, cci_vae",
        default="autoencoder",
    )
    parser.add_argument(
        "--architecture", help="name of autoencoder architecture", default="Linear",
    )
    parser.add_argument(
        "--data",
        help="dataset used for training: mnist, single_digit_mnist",
        default="shapes",
    )
    parser.add_argument(
        "--mnist_proportion",
        help="proportion of mnist to use",
        default=0.01,
        type=float,
    )
    parser.add_argument(
        "--n_classes",
        help="number of classes to use for simple shapes",
        default=300,
        type=int,
    )
    parser.add_argument(
        "--z_dim", help="dataset used for training", default=1000, type=int
    )
    parser.add_argument(
        "--transformation",
        choices=["rotation", "shift_x", "shift_y"],
        type=str.lower,
        default="rotation",
    )
    parser.add_argument(
        "--distribution",
        help="likelihood distribution used for computing loss in CCI VAE",
        choices=["gaussian", "bernoulli"],
        type=str.lower,
        default="gaussian",
    )
    parser.add_argument("--beta", help="beta used for CCI VAE", default=1000, type=int)
    parser.add_argument(
        "--no_latent_op",
        help="use standard autoencoder without latent operators",
        action="store_true",
    )
    parser.add_argument("--cluster", action="store_true")
    parser.add_argument("--sweep", action="store_true")
    return parser