class_docstr: Base class for Annotator metrics.
class_docstr_tok: ["Base","class","for","Annotator","metrics","."]
docstr: Args:
      responses: Responses given by the user.
          Depending on the type of question it can be a list of strings, or integers.
      suggestions: Suggestions offered for the annotators.
          Same format as `responses`.
docstr_tok: ["Args",":","responses",":","Responses","given","by","the","user",".","Depending","on","the","type","of","question","it","can","be","a","list","of","strings",",","or","integers",".","suggestions",":","Suggestions","offered","for","the","annotators",".","Same","format","as","`","responses","`","."]
code: def __init__(
      self, responses: Responses = None, suggestions: Suggestions = None
  ) -> None:
      """
      Args:
          responses: Responses given by the user.
              Depending on the type of question it can be a list of strings, or integers.
          suggestions: Suggestions offered for the annotators.
              Same format as `responses`.
      """
      self._responses = responses
      self._suggestions = suggestions
  
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 1 to create a new AnnotatorMetricBase object from inherited base classes: ABC with example: obj = AnnotatorMetricBase(responses, suggestions)