old_contents: import os
  import numpy as np
  
  '''
  wrapper around generate_bdainput.py
  '''
  
  
  if __name__ == "__main__":
  
      layers = ['pool1','conv42','fc6']
      # layers = ['fc6']
      split_type = 'balancedavg'
      # splits = ['16','32','64','128','256','512']
      splits = map(str,np.arange(1,6))
      
      
      ## for the adapted encoder
      for layer in layers:
          for split_num in splits:
              cmd_string = "python generate_bdainput.py --adaptor_type multimodal_{} --split_type {}{}".format(layer,split_type,split_num)
              print '{}'.format(cmd_string)
              os.system(cmd_string)
  
              ## make bdaOutput subdirectories to save out to
              bda_out_path = '../models/bdaOutput/multimodal_{}_{}{}'.format(layer,split_type,split_num)
              if not os.path.exists(bda_out_path):
                  os.makedirs(bda_out_path)
                  os.makedirs(os.path.join(bda_out_path,'raw'))
  
      ## also for humans
      for split_num in splits:
          cmd_string = "python generate_bdainput.py --adaptor_type human --split_type {}{} --gen_similarity False --gen_centroid True".format(split_type,split_num)
          print '{}'.format(cmd_string)
          os.system(cmd_string)
  
          ## make bdaOutput subdirectories to save out to
          bda_out_path = '../models/bdaOutput/human_{}{}'.format(split_type,split_num)
          if not os.path.exists(bda_out_path):
              os.makedirs(bda_out_path)
              os.makedirs(os.path.join(bda_out_path,'raw'))
  
new_contents: import os
  import numpy as np
  
  '''
  wrapper around generate_bdainput.py
  '''
  
  
  if __name__ == "__main__":
  
      layers = ['pool1','conv42','fc6']
      split_type = 'balancedavg'
      splits = map(str,np.arange(1,6))
      
      
      ## for the adapted encoder
      for layer in layers:
          for split_num in splits:
              cmd_string = "python generate_bdainput.py --adaptor_type multimodal_{} --split_type {}{}".format(layer,split_type,split_num)
              print '{}'.format(cmd_string)
              os.system(cmd_string)
  
              ## make bdaOutput subdirectories to save out to
              bda_out_path = '../models/bdaOutput/multimodal_{}_{}{}'.format(layer,split_type,split_num)
              if not os.path.exists(bda_out_path):
                  os.makedirs(bda_out_path)
                  os.makedirs(os.path.join(bda_out_path,'raw'))
  
      ## also for humans
      for split_num in splits:
          cmd_string = "python generate_bdainput.py --adaptor_type human --split_type {}{} --gen_similarity False --gen_centroid True".format(split_type,split_num)
          print '{}'.format(cmd_string)
          os.system(cmd_string)
  
          ## make bdaOutput subdirectories to save out to
          bda_out_path = '../models/bdaOutput/human_{}{}'.format(split_type,split_num)
          if not os.path.exists(bda_out_path):
              os.makedirs(bda_out_path)
              os.makedirs(os.path.join(bda_out_path,'raw'))
  
subject: clean up rsa prep script