class_docstr: The GradValues module is used to compute the gradients of a function.
class_docstr_tok: ["The","GradValues","module","is","used","to","compute","the","gradients","of","a","function","."]
docstr: Returns the computed gradients for the first value returned by `f` and the values returned by `f`.
  Returns:
      A tuple (gradients, values of f), where gradients is a list containing
      the input gradients, if any, followed by the variable gradients.
docstr_tok: ["Returns","the","computed","gradients","for","the","first","value","returned","by","`","f","`","and","the","values","returned","by","`","f","`",".","Returns",":","A","tuple","(","gradients",",","values","of","f",")",",","where","gradients","is","a","list","containing","the","input","gradients",",","if","any",",","followed","by","the","variable","gradients","."]
code: def __call__(self, *args, **kwargs):
      """Returns the computed gradients for the first value returned by `f` and the values returned by `f`.
      Returns:
          A tuple (gradients, values of f), where gradients is a list containing
          the input gradients, if any, followed by the variable gradients.
      """
      return super().__call__(*args, **kwargs)
  
imports: import inspect
  from typing import List, Optional, Callable, Tuple, Dict, Union
  import jax
  from objax.module import Function, Module
  from objax.typing import JaxArray
  from objax.util import repr_function, class_name
  from objax.variable import BaseState, TrainVar, VarCollection
label_desc: Use image node_id 2 for calling the GradValues obj's underlying member method code with example usage: obj.__call__() and returns: super