class_docstr: Create Transformers for Datasets.
  
  When loading molnet datasets, you cannot directly pass in Transformers
  to use because many Transformers require the Dataset they will be applied to
  as a constructor argument.  Instead you pass in TransformerGenerator objects
  which can create the Transformers once the Dataset is loaded.
class_docstr_tok: ["Create","Transformers","for","Datasets",".","When","loading","molnet","datasets",",","you","can","not","directly","pass","in","Transformers","to","use","because","many","Transformers","require","the","Dataset","they","will","be","applied","to","as","a","constructor","argument",".","Instead","you","pass","in","TransformerGenerator","objects","which","can","create","the","Transformers","once","the","Dataset","is","loaded","."]
docstr: Get a name for directories on disk describing this Transformer.
docstr_tok: ["Get","a","name","for","directories","on","disk","describing","this","Transformer","."]
code: def get_directory_name(self) -> str:
      """Get a name for directories on disk describing this Transformer."""
      name = self.transformer_class.__name__
      for key, value in self.kwargs.items():
          if isinstance(value, list):
              continue
          name += "_" + key + "_" + str(value)
      return name
  
file_path: deepchem/deepchem/molnet/load_function/molnet_loader.py
imports: import os
  import logging
  import deepchem
  from deepchem.data import Dataset, DiskDataset
  from typing import List, Optional, Tuple, Type, Union
label_desc: Use image node_id 3 for calling the TransformerGenerator obj's underlying member method code with example usage: obj.get_directory_name() and returns: name