class_docstr: Directs usage of user-computed featurizations.
class_docstr_tok: ["Directs","usage","of","user-computed","featurizations","."]
docstr: Creates user-defined-featurizer.
docstr_tok: ["Creates","user-defined-featurizer","."]
code: def __init__(self, feature_fields):
      """Creates user-defined-featurizer."""
      self.feature_fields = feature_fields
  
imports: import inspect
  import logging
  import numpy
  from typing import Any, Dict, Iterable, Optional, Tuple, Union, cast
  from deepchem.utils import get_print_threshold
  from deepchem.utils.typing import PymatgenStructure
label_desc: Use image node_id 1 to create a new UserDefinedFeaturizer object from inherited base classes: Featurizer with example: obj = UserDefinedFeaturizer(feature_fields)