def parse_args()

in sagemaker/source/train.py [0:0]

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

def parse_args():
    parser = argparse.ArgumentParser(description='FPM args')
    parser.add_argument('--train_input_filename', type=str, default="../data/processed/train_dataset.csv",
                        help='input path of the data, default: "../data/processed/train_dataset.csv"')
    parser.add_argument('--test_input_filename', type=str, default="../data/processed/test_dataset.csv",
                        help='input path of the data, default: "../data/processed/test_dataset.csv"')
    parser.add_argument('--output_path', type=str, default="../output",
                        help='output to store model artefacts, default: "../output"')

    parser.add_argument('--sensor_headers', type=str, default=json.dumps(["voltage", "current"]),
                        help='sensors headers in the dataset, default: {}'.format(json.dumps(["voltage", "current"])))
    parser.add_argument('--target_column', type=str, default="target",
                        help='name of the target in the dataset, default: target')

    parser.add_argument('--lr', type=float, default=0.001,
                        help='learning rate, default: 0.001')
    parser.add_argument('--epochs', type=int, default=200,
                        help='epochs, default: 200')
    parser.add_argument('--batch_size', type=int, default=128,
                        help='batch_size, default: 128')
    parser.add_argument('--dropout', type=float, default=0.0,
                        help='drop out, default: 0.0')
    parser.add_argument('--fc_hidden_units', type=str, default="[256, 128]",
                       help="Hidden units, default \"[256, 128]\"")
    parser.add_argument('--conv_channels', type=str, default="[2, 8, 2]",
                       help="Conv channels, default \"[2, 8, 2]\"")

    args = parser.parse_args()

    return args