def METHOD_NAME():
    """Parses all arguments and assigns default values when missing.
    Convert argument strings to objects and assign them as attributes of the
    namespace.
    Returns:
        An object containing all the parsed arguments for script to use.
    """
    args_parser = argparse.ArgumentParser()
    args_parser.add_argument(
        '--job-dir',
        help='GCS location to write checkpoints and export models.',
        required=True
    )
    args_parser.add_argument(
        '--training_path',
        help='Location to training data.',
        default='gs://bee-health/data/train.csv'
    )
    args_parser.add_argument(
        '--validation_path',
        help='Location to validation data.',
        default='gs://bee-health/data/valid.csv'
    )
    args_parser.add_argument(
        '--image_path',
        help='Location of image folder.',
        default='gs://bee-health/bee_imgs/'
    )
    args_parser.add_argument(
        '--subspecies_embedding',
        help='Size of subspecies embedding.',
        default=1,
        type=int
    )
    args_parser.add_argument(
        '--dropout',
        help='Dropout probability.',
        default=0.3737,
        type=float
    )
    args_parser.add_argument(
        '--first_layer_size',
        help='First layer size.',
        default=308,
        type=int
    )
    args_parser.add_argument(
        '--number_layers',
        help='Number of hidden layers.',
        default=8,
        type=int
    )
    args_parser.add_argument(
        '--layer_reduction_fraction',
        help='Fraction to reduce layers in network.',
        default=0.91,
        type=float
    )
    args_parser.add_argument(
        '--learning_rate',
        help='Learning rate.',
        default=0.0031,
        type=float
    )
    args_parser.add_argument(
        '--batch_size',
        help='Training batch size.',
        default=32,
        type=int
    )
    args_parser.add_argument(
        '--eval_batch_size',
        help='Evaluation batch size.',
        default=32,
        type=int
    )
    args_parser.add_argument(
        '--max_steps',
        help='Maximum steps for training.',
        default=5000,
        type=int
    )
    args_parser.add_argument(
        '--tf_hub_module',
        help='TF Hub module to use for images.',
        default=TF_HUB_IMAGENET + 'mobilenet_v1_025_224/feature_vector/1',
        type=str
    )
    return args_parser.parse_args()