code: def _setup_memory(self):
          
          if self.memory:
              if isinstance(self.memory, str):
                  if self.memory == "auto":
                      # Create a temporary folder to store the transformers of the pipeline
                      self._cachedir = mkdtemp()
                  else:
                      if not os.path.isdir(self.memory):
                          try:
                              os.makedirs(self.memory)
                          except:
                              raise ValueError(
                                  'Could not create directory for memory caching: {}'.format(self.memory)
                              )
                      self._cachedir = self.memory
  
                  self._memory = Memory(cachedir=self._cachedir, verbose=0)
              elif isinstance(self.memory, Memory):
                  self._memory = self.memory
              else:
                  raise ValueError(
                      'Could not recognize Memory object for pipeline caching. '
                      'Please provide an instance of sklearn.external.joblib.Memory,'
                      ' a path to a directory on your system, or \"auto\".'
                  )
docs: Setup Memory object for memory caching.