class_docstr: Single shared bias used in the Double DQN paper.
  
  You can add this link after a Linear layer with nobias=True to implement a
  Linear layer with a single shared bias parameter.
  
  See http://arxiv.org/abs/1509.06461.
class_docstr_tok: ["Single","shared","bias","used","in","the","Double","DQN","paper",".","You","can","add","this","link","after","a","Linear","layer","with","nobias=True","to","implement","a","Linear","layer","with","a","single","shared","bias","parameter",".","See","http",":","\/\/arxiv.org\/abs\/1509.06461","."]
code: def __init__(self):
      super().__init__()
      with self.init_scope():
          self.bias = chainer.Parameter(0, shape=1)
  
imports: import argparse
  import os
  import chainer
  from chainer import functions
  from chainer import links
  from chainer import optimizers
  import numpy
  import chainerrl
  from chainerrl.action_value import DiscreteActionValue
  from chainerrl import agents
  from chainerrl import experiments
  from chainerrl import explorers
  from chainerrl import links
  from chainerrl import misc
  from chainerrl.q_functions import DuelingDQN
  from chainerrl import replay_buffer
  from chainerrl.wrappers import atari_wrappers
label_desc: Use image node_id 1 to create a new SingleSharedBias object from inherited base classes: chainer with example: obj = SingleSharedBias()