class_docstr: Wrapper class to adversarially mitigate biases in any pretrained Model.
  
  # Parameters
  
  vocab : `Vocabulary`
      Vocabulary of predictor.
  predictor : `Model`
      Model for which to mitigate biases.
  adversary : `Model`
      Model that attempts to recover protected variable values from predictor's predictions.
  bias_direction : `BiasDirectionWrapper`
      Bias direction used by adversarial bias mitigator.
  predictor_output_key : `str`
      Key corresponding to output in `output_dict` of predictor that should be passed as input
      to adversary.
  
  !!! Note
      adversary must use same vocab as predictor, if it requires a vocab.
code: def get_parameters_for_histogram_tensorboard_logging(
      self, *args, **kwargs
  ):
      return self.predictor.get_parameters_for_histogram_tensorboard_logging(
          *args, **kwargs
      )
  
imports: from typing import Dict, Optional
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.data import Vocabulary
  from allennlp.fairness.bias_direction_wrappers import BiasDirectionWrapper
  from allennlp.modules.feedforward import FeedForward
  from allennlp.models import Model
  from allennlp.nn import InitializerApplicator
  from allennlp.nn.util import find_embedding_layer
  from allennlp.training.callbacks.callback import TrainerCallback
  from allennlp.training.callbacks.backward import OnBackwardException
  from allennlp.training.gradient_descent_trainer import GradientDescentTrainer
label_desc: Use image node_id 8 for calling the AdversarialBiasMitigator obj's underlying member method code with example usage: obj.get_parameters_for_histogram_tensorboard_logging() and returns: self