class_docstr: The Grad module is used to compute the gradients of a function.
class_docstr_tok: ["The","Grad","module","is","used","to","compute","the","gradients","of","a","function","."]
docstr: Returns the computed gradients for the first value returned by `f`.
  
  Returns:
      A list of input gradients, if any, followed by the variable gradients.
docstr_tok: ["Returns","the","computed","gradients","for","the","first","value","returned","by","`","f","`",".","Returns",":","A","list","of","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`.
  
      Returns:
          A list of 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 Grad obj's underlying member method code with example usage: obj.__call__() and returns: super