class_docstr: Q-function output for discrete action space.
  
  Args:
      q_values (torch.Tensor):
          Array of Q values whose shape is (batchsize, n_actions)
class_docstr_tok: ["Q-function","output","for","discrete","action","space",".","Args",":","q_values","(","torch.Tensor",")",":","Array","of","Q","values","whose","shape","is","(","batchsize",",","n_actions",")"]
code: def compute_double_advantage(self, actions, argmax_actions):
      return self.evaluate_actions(actions) - self.evaluate_actions(
          argmax_actions
      )
  
imports: import warnings
  from abc import ABCMeta, abstractmethod, abstractproperty
  import torch
  import torch.nn.functional
  from torch.distributions.utils import lazy_property
label_desc: Use image node_id 6 for calling the DiscreteActionValue obj's underlying member method code with example usage: obj.compute_double_advantage(actions, argmax_actions) and returns: unknown