class_docstr: Class to evaluate absolute loss.
  
  Read more in the :ref:`User Guide <constraints_regression>`.
class_docstr_tok: ["Class","to","evaluate","absolute","loss",".","Read","more","in","the",":","ref",":","`","User","Guide","<","constraints_regression",">","`","."]
docstr: Evaluate the absolute loss for the given set of true and predicted values.
docstr_tok: ["Evaluate","the","absolute","loss","for","the","given","set","of","true","and","predicted","values","."]
code: def eval(self, y_true, y_pred):  # noqa: A003
      """Evaluate the absolute loss for the given set of true and predicted values."""
      return np.abs(
          np.clip(y_true, self.min_val, self.max_val)
          - np.clip(y_pred, self.min_val, self.max_val)
      )
  
imports: import numpy
  import pandas
  from fairlearn.utils._input_validation import _validate_and_reformat_input
  from .moment import _ALL, _GROUP_ID, _LABEL, _LOSS, _PREDICTION, LossMoment
label_desc: Use image node_id 2 for calling the AbsoluteLoss obj's underlying member method code with example usage: obj.eval(y_true, y_pred) and returns: np