code: def _build_optml_volumes(self, host, subdirs):
          
          volumes = []
  
          for subdir in subdirs:
              host_dir = os.path.join(self.container_root, host, subdir)
              container_dir = '/opt/ml/{}'.format(subdir)
              volume = _Volume(host_dir, container_dir)
              volumes.append(volume)
  
          return volumes
docs: Generate a list of :class:`~sagemaker.local_session.Volume` required for the container to start.
  
          It takes a folder with the necessary files for training and creates a list of opt volumes that
          the Container needs to start.
  
          Args:
              host (str): container for which the volumes will be generated.
              subdirs (list): list of subdirectories that will be mapped. For example: ['input', 'output', 'model']
  
          Returns: (list) List of :class:`~sagemaker.local_session.Volume`