def get_arguments():
    'Parse all the arguments provided from the CLI.\n\n    Returns:\n      A list of parsed arguments.\n    '
    parser = argparse.ArgumentParser(description='DeepLab-ResNet Network')
    parser.add_argument('--model', type=str, default=MODEL, help='Model Choice (DeeplabMulti/DeeplabVGG/Oracle).')
    parser.add_argument('--data-dir', type=str, default=DATA_DIRECTORY, help='Path to the directory containing the Cityscapes dataset.')
    parser.add_argument('--data-list', type=str, default=DATA_LIST_PATH, help='Path to the file listing the images in the dataset.')
    parser.add_argument('--ignore-label', type=int, default=IGNORE_LABEL, help='The index of the label to ignore during the training.')
    parser.add_argument('--num-classes', type=int, default=NUM_CLASSES, help='Number of classes to predict (including background).')
    parser.add_argument('--restore-from', type=str, default=RESTORE_FROM, help='Where restore model parameters from.')
    parser.add_argument('--gpu', type=int, default=0, help='choose gpu device.')
    parser.add_argument('--batchsize', type=int, default=4, help='choose gpu device.')
    parser.add_argument('--set', type=str, default=SET, help='choose evaluation set.')
    parser.add_argument('--save', type=str, default=SAVE_PATH, help='Path to save result.')
    parser.add_argument('--input-size', type=str, default=INPUT_SIZE, help='Comma-separated string with height and width of source images.')
    return parser.parse_args()
Parse all the arguments provided from the CLI.

Returns:
  A list of parsed arguments.
def get_arguments():
    'Parse all the arguments provided from the CLI.\n\n    Returns:\n      A list of parsed arguments.\n    '
    parser = argparse.ArgumentParser(description='DeepLab-ResNet Network')
    parser.add_argument('--model', type=str, default=MODEL, help='Model Choice (DeeplabMulti/DeeplabVGG/Oracle).')
    parser.add_argument('--data-dir', type=str, default=DATA_DIRECTORY, help='Path to the directory containing the Cityscapes dataset.')
    parser.add_argument('--data-list', type=str, default=DATA_LIST_PATH, help='Path to the file listing the images in the dataset.')
    parser.add_argument('--ignore-label', type=int, default=IGNORE_LABEL, help='The index of the label to ignore during the training.')
    parser.add_argument('--num-classes', type=int, default=NUM_CLASSES, help='Number of classes to predict (including background).')
    parser.add_argument('--restore-from', type=str, default=RESTORE_FROM, help='Where restore model parameters from.')
    parser.add_argument('--gpu', type=int, default=0, help='choose gpu device.')
    parser.add_argument('--batchsize', type=int, default=4, help='choose gpu device.')
    parser.add_argument('--set', type=str, default=SET, help='choose evaluation set.')
    parser.add_argument('--save', type=str, default=SAVE_PATH, help='Path to save result.')
    parser.add_argument('--input-size', type=str, default=INPUT_SIZE, help='Comma-separated string with height and width of source images.')
    return parser.parse_args()