text: import os
  
  sizes = [10**(-0.25*k) for k in range(4, 20, 3)]
  splits = [2, 3, 5, 9]
  datasets = ['CIFAR', 'MNIST']
  net_names = ['ConvBig', 'ConvMed', 'FFNN']
  perturbations = ['HazeThenRotation', 'ContrastVariationThenRotation', 'ContrastVariationThenHaze']
  
  NUM_IMAGES = 1  # number of images per category
  rotate_padding = 4
  
  for net in net_names:
      for dataset in datasets:
          for perturbation in perturbations:
              for s in sizes:
                  s1, s2 = s*2, s
                  if perturbation == 'ContrastVariationThenHaze':
                      s2 *= 2
                  filename = f'{net}_{dataset}_{perturbation}_nosplit.txt'
                  os.system(f'./{net.lower()}_compose {dataset} {perturbation} {s1} {s2} {NUM_IMAGES} {rotate_padding} >> results_compose/results_compose_nosplit/{filename}')
  
      for split in splits:
          for dataset in datasets:
              for perturbation in perturbations:
                  for s in sizes:
                      s1, s2 = s*2, s
                      if perturbation == 'ContrastVariationThenHaze':
                          s2 *= 2
                      filename = f'{net}_{dataset}_{perturbation}_split{split}.txt'
                      os.system(f'./{net.lower()}_compose_splitting {dataset} {perturbation} {s1} {s2} {NUM_IMAGES} {split} {rotate_padding} >> results_compose/results_compose_split{split}/{filename}')
  
  for dataset in datasets:
      for perturbation in perturbations:
          for s in sizes:
              s1, s2 = s*2, s
              if perturbation == 'ContrastVariationThenHaze':
                  s2 *= 2
              os.system(f'./perturb_compose_baseline {dataset} {perturbation} {s1} {s2} {NUM_IMAGES} {rotate_padding} >> results_compose/results_compose_baseline/perturbation_baseline.csv')
  