class_docstr: Base class for LIT interpretation components.
class_docstr_tok: ["Base","class","for","LIT","interpretation","components","."]
docstr: Returns the metadata spec of this component.
  
  Can be used to represent information about what this interpreter returns,
  for use in the UI. For example, indicating if a saliency map is signed
  or unsigned which will affect the display of the results.
  
  Returns:
    A spec of what this component returns, to be used to drive the UI.
docstr_tok: ["Returns","the","metadata","spec","of","this","component",".","Can","be","used","to","represent","information","about","what","this","interpreter","returns",",","for","use","in","the","UI",".","For","example",",","indicating","if","a","saliency","map","is","signed","or","unsigned","which","will","affect","the","display","of","the","results",".","Returns",":","A","spec","of","what","this","component","returns",",","to","be","used","to","drive","the","UI","."]
code: def meta_spec(self) -> types.Spec:
      """Returns the metadata spec of this component.
  
      Can be used to represent information about what this interpreter returns,
      for use in the UI. For example, indicating if a saliency map is signed
      or unsigned which will affect the display of the results.
  
      Returns:
        A spec of what this component returns, to be used to drive the UI.
      """
      return {}
  
imports: import abc
  from collections.abc import Sequence
  import inspect
  from typing import Any, Optional
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
label_desc: Use image node_id 5 for calling the Interpreter obj's underlying member method code with example usage: obj.meta_spec() and returns: dict