param_parser.py

"""Parameter parsing."""

import argparse

def parameter_parser():
    """
    A method to parse up command line parameters. By default it trains on the Cora dataset.
    The default hyperparameters give a good quality representation without grid search.
    """
    parser = argparse.ArgumentParser(description="Run MixHop/N-GCN.")

    parser.add_argument("--edge-path",
                        nargs="?",
                        default="./input/cora_edges.csv",
	                help="Edge list csv.")

    parser.add_argument("--features-path",
                        nargs="?",
                        default="./input/cora_features.json",
	                help="Features json.")

    parser.add_argument("--target-path",
                        nargs="?",
                        default="./input/cora_target.csv",
	                help="Target classes csv.")

    parser.add_argument("--model",
                        nargs="?",
                        default="mixhop",
	                help="Target classes csv.")

    parser.add_argument("--epochs",
                        type=int,
                        default=2000,
	                help="Number of training epochs. Default is 2000.")

    parser.add_argument("--seed",
                        type=int,
                        default=42,
	                help="Random seed for train-test split. Default is 42.")

    parser.add_argument("--early-stopping",
                        type=int,
                        default=10,
	                help="Number of early stopping rounds. Default is 10.")

    parser.add_argument("--training-size",
                        type=int,
                        default=1500,
	                help="Training set size. Default is 1500.")

    parser.add_argument("--validation-size",
                        type=int,
                        default=500,
	                help="Validation set size. Default is 500.")

    parser.add_argument("--dropout",
                        type=float,
                        default=0.5,
	                help="Dropout parameter. Default is 0.5.")

    parser.add_argument("--learning-rate",
                        type=float,
                        default=0.01,
	                help="Learning rate. Default is 0.01.")

    parser.add_argument("--cut-off",
                        type=float,
                        default=0.1,
	                help="Weight cut-off. Default is 0.1.")

    parser.add_argument("--lambd",
                        type=float,
                        default=0.0005,
	                help="L2 regularization coefficient. Default is 0.0005.")

    parser.add_argument("--layers-1",
                        nargs="+",
                        type=int,
                        help="Layer dimensions separated by space (top). E.g. 200 20.")

    parser.add_argument("--layers-2",
                        nargs="+",
                        type=int,
                        help="Layer dimensions separated by space (bottom). E.g. 200 200.")

    parser.add_argument("--budget",
                        type=int,
                        default=60,
                        help="Architecture neuron allocation budget. Default is 60.")

    parser.set_defaults(layers_1=[200, 200, 200])
    parser.set_defaults(layers_2=[200, 200, 200])
    
    return parser.parse_args()