class_docstr: Base class for models which incorporate inFairness algorithms.
class_docstr_tok: ["Base","class","for","models","which","incorporate","inFairness","algorithms","."]
docstr: Perform a forward step using batched data and return the
  resulting loss.
  
  The module is set to be in evaluation mode (e.g. dropout is
  not applied).
  
  Parameters
  ----------
  batch
    A single batch returned by the data loader.
  
  **fit_params : dict
    Additional parameters passed to the ``forward`` method of
    the module and to the ``self.train_split`` call.
docstr_tok: ["Perform","a","forward","step","using","batched","data","and","return","the","resulting","loss",".","The","module","is","set","to","be","in","evaluation","mode","(","e.g",".","dropout","is","not","applied",")",".","Parameters","--","--","--","--","--","batch","A","single","batch","returned","by","the","data","loader",".","*","*","fit_params",":","dict","Additional","parameters","passed","to","the","``","forward","``","method","of","the","module","and","to","the","``","self.train_split","``","call","."]
code: def validation_step(self, batch, **fit_params):
      """Perform a forward step using batched data and return the
      resulting loss.
  
      The module is set to be in evaluation mode (e.g. dropout is
      not applied).
  
      Parameters
      ----------
      batch
        A single batch returned by the data loader.
  
      **fit_params : dict
        Additional parameters passed to the ``forward`` method of
        the module and to the ``self.train_split`` call.
  
      """
      step = super().validation_step(batch, **fit_params)
      return {"loss": step["loss"], "y_pred": step["y_pred"].y_pred}
  
imports: from inFairness import fairalgo
  from sklearn.preprocessing import LabelBinarizer
  from sklearn.utils.multiclass import type_of_target
  from sklearn.exceptions import NotFittedError
  from skorch import NeuralNet
  from skorch.dataset import unpack_data, Dataset
  from skorch.utils import is_pandas_ndframe
label_desc: Use image node_id 5 for calling the InFairnessNet obj's underlying member method code with example usage: obj.validation_step(batch) and returns: dict