class_docstr: Base class for Annotator metrics.
class_docstr_tok: ["Base","class","for","Annotator","metrics","."]
docstr: Abstract method where the computation is done.
  
  Args:
      responses: Responses given by the user, as expected by the given metric.
      suggestions: Suggestions offered for the annotators, as expected by the given metric.
docstr_tok: ["Abstract","method","where","the","computation","is","done",".","Args",":","responses",":","Responses","given","by","the","user",",","as","expected","by","the","given","metric",".","suggestions",":","Suggestions","offered","for","the","annotators",",","as","expected","by","the","given","metric","."]
code: def _compute(
      self, responses: Responses, suggestions: Suggestions, **kwargs
  ):
      """Abstract method where the computation is done.
  
      Args:
          responses: Responses given by the user, as expected by the given metric.
          suggestions: Suggestions offered for the annotators, as expected by the given metric.
      """
      pass
  
imports: from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, Any, Callable, Dict, Hashable, List, Tuple, Union
  import pandas
  from argilla.client.feedback.schemas.remote.shared import RemoteSchema
  from argilla.pydantic_v1 import BaseModel
label_desc: Use image node_id 4 for calling the AnnotatorMetricBase obj's underlying member method code with example usage: obj._compute(responses, suggestions) without return types