class_docstr: This `Model` implements a simple feedforward regression adversary.
  
  Registered as a `Model` with name "feedforward_regression_adversary".
  
  # Parameters
  
  vocab : `Vocabulary`
  feedforward : `FeedForward`
      A feedforward layer.
  initializer : `Optional[InitializerApplicator]`, optional (default=`InitializerApplicator()`)
      If provided, will be used to initialize the model parameters.
code: def __init__(
      self,
      vocab: Vocabulary,
      feedforward: FeedForward,
      initializer: Optional[
          InitializerApplicator
      ] = InitializerApplicator(),
      **kwargs,
  ) -> None:
      super().__init__(vocab, **kwargs)
  
      self._feedforward = feedforward
      self._loss = torch.nn.MSELoss()
      initializer(self)
  
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 1 to create a new FeedForwardRegressionAdversary object from inherited base classes: Model with example: obj = FeedForwardRegressionAdversary(vocab, feedforward, initializer)