class_docstr: Base class for all loss functions.
docstr: Return the gradient with respect to y_pred.
  
  Parameters
  ----------
  y_true
      Ground truth(s).
  y_pred
      Prediction(s).
  
  Returns
  -------
  The gradient(s).
docstr_tok: ["Return","the","gradient","with","respect","to","y_pred",".","Parameters","--","--","--","--","--","y_true","Ground","truth","(","s",")",".","y_pred","Prediction","(","s",")",".","Returns","--","--","--","-","The","gradient","(","s",")","."]
code: def gradient(self, y_true, y_pred):
      """Return the gradient with respect to y_pred.
  
      Parameters
      ----------
      y_true
          Ground truth(s).
      y_pred
          Prediction(s).
  
      Returns
      -------
      The gradient(s).
  
      """
  
imports: from __future__ import annotations
  import abc
  import typing
  import numpy
  from river import base, optim, utils
label_desc: Use image node_id 3 for calling the Loss obj's underlying member method code with example usage: obj.gradient(y_true, y_pred) without return types