class_docstr: Convenience class to let singletask models be fit on multitask data.
  
  This wrapper class groups a set of singletask `SklearnModel` objects to
  create a multitask model. This class exists primarily to facilitate
  benchmarking.
  
  Note
  ----
  This current implementation is only functional for sklearn models.
class_docstr_tok: ["Convenience","class","to","let","singletask","models","be","fit","on","multitask","data",".","This","wrapper","class","groups","a","set","of","singletask","`","SklearnModel","`","objects","to","create","a","multitask","model",".","This","class","exists","primarily","to","facilitate","benchmarking",".","Note","--","--","This","current","implementation","is","only","functional","for","sklearn","models","."]
docstr: Save all models
  
  TODO(rbharath): Saving is not yet supported for this model.
docstr_tok: ["Save","all","models","TODO","(","rbharath",")",":","Saving","is","not","yet","supported","for","this","model","."]
code: def save(self):
      """Save all models
  
      TODO(rbharath): Saving is not yet supported for this model.
      """
      pass
  
file_path: deepchem/deepchem/models/multitask.py
imports: import os
  import numpy
  import shutil
  import logging
  from deepchem.models import Model
  from deepchem.data import DiskDataset
  from deepchem.trans import undo_transforms
label_desc: Use image node_id 7 for calling the SingletaskToMultitask obj's underlying member method code with example usage: obj.save() without return types