text: 
  def get_options():
      import argparse
      parser = argparse.ArgumentParser(
          description='Creating training on heatmaps')
  
      parser.add_argument('--classes', required=False,
                          default=2,
                          metavar="int", type=int,
                          help='number of classes')
  
      parser.add_argument('--batch_size', required=False,
                          default=4,
                          metavar="int", type=int,
                          help='batch size value')
  
      parser.add_argument('--path', required=False,
                          default="/Users/naylorpeter/tmp/predict_from_umap_cell/patients/comp3",
                          metavar="str", type=str,
                          help='path to input data')
  
      parser.add_argument('--labels', required=False,
                          default="/Users/naylorpeter/tmp/predict_from_umap_cell/patients/multi_class.csv",
                          metavar="str", type=str,
                          help='path to label csv file')
  
      parser.add_argument('--y_interest', required=False,
                          default="RCB_class",
                          metavar="str", type=str,
                          help='tag for the variable of interest in labels')
  
      parser.add_argument('--loss', required=False,
                          default="categorical_crossentropy",
                          metavar="str", type=str,
                          help='type of loss, categorical_crossentropy or mse')
  
      parser.add_argument('--out_weight', required=False,
                          default="weight_models.h5",
                          metavar="str", type=str,
                          help='name for the weight file')   
  
      parser.add_argument('--model', required=False,
                          default='resnet50',
                          metavar="str", type=str,
                          help='name for the weight file')
  
      parser.add_argument('--epochs', required=False,
                          default=2,
                          metavar="int", type=int,
                          help='number of epochs')
  
      parser.add_argument('--workers', required=False,
                          default=5,
                          metavar="int", type=int,
                          help='number of workers')
  
      parser.add_argument('--repeat', required=False,
                          default=5,
                          metavar="int", type=int,
                          help='number of repeats for the evaluation of validation or test')
  
      parser.add_argument('--multiprocess', required=False,
                          default=0,
                          metavar="int", type=int,
                          help='wether to use multi_processing for keras')
  
      parser.add_argument('--inner_fold', required=False,
                          default=5,
                          metavar="int", type=int,
                          help='number of inner folds to perform')
  
      parser.add_argument('--fold_test', required=False,
                          default=0,
                          metavar="int", type=int,
                          help='outer fold number to perform test on')
  
      parser.add_argument('--optimizer', required=False,
                          default='adam',
                          metavar="str", type=str,
                          help='optimizer key')
  
      parser.add_argument('--lr', required=False,
                          default=10e-4,
                          metavar="float", type=float,
                          help='initial learning_rate')
  
      parser.add_argument('--callback', required=False,
                          default="version1",
                          metavar="str", type=str,
                          help='callback version to load')
  
      parser.add_argument('--dropout', required=False,
                          default=0.5,
                          metavar="float", type=float,
                          help='dropout value')
  
      parser.add_argument('--filename', required=False,
                          default="results.pkl",
                          metavar="str", type=str,
                          help='file name for val and test')
  
  
      parser.add_argument('--probaname', required=False,
                          default="proba.csv",
                          metavar="str", type=str,
                          help='proba file name for val and test')
  
      args = parser.parse_args()
      return args
  
  