class_docstr: DQN's head (NIPS workshop version)
class_docstr_tok: ["DQN","'s","head","(","NIPS","workshop","version",")"]
code: def __init__(
      self,
      n_input_channels=4,
      n_output_channels=256,
      activation=F.relu,
      bias=0.1,
  ):
      self.n_input_channels = n_input_channels
      self.activation = activation
      self.n_output_channels = n_output_channels
  
      layers = [
          L.Convolution2D(
              n_input_channels, 16, 8, stride=4, initial_bias=bias
          ),
          L.Convolution2D(16, 32, 4, stride=2, initial_bias=bias),
          L.Linear(2592, n_output_channels, initial_bias=bias),
      ]
  
      super(NIPSDQNHead, self).__init__(*layers)
  
file_path: chainerrl/chainerrl/links/dqn_head.py
imports: import chainer
  from chainer import functions
  from chainer import links
label_desc: Use image node_id 1 to create a new NIPSDQNHead object from inherited base classes: chainer with example: obj = NIPSDQNHead(n_input_channels, n_output_channels, activation, bias)