code: def __init__(self, act_dim):
      super(AtariModel, self).__init__()
  
      self.conv1 = nn.Conv2D(
          in_channels=4,
          out_channels=16,
          kernel_size=4,
          stride=2,
          padding=1,
      )
      self.conv2 = nn.Conv2D(
          in_channels=16,
          out_channels=32,
          kernel_size=4,
          stride=2,
          padding=2,
      )
      self.conv3 = nn.Conv2D(
          in_channels=32,
          out_channels=256,
          kernel_size=11,
          stride=1,
          padding=0,
      )
  
      self.flatten = nn.Flatten()
  
      # Need to calc the size of the in_features according to the input image.
      # The default size of the input image is 42 * 42
      self.policy_fc = nn.Linear(
          in_features=256,
          out_features=act_dim,
          weight_attr=paddle.ParamAttr(
              initializer=paddle.nn.initializer.Normal()
          ),
          bias_attr=paddle.ParamAttr(
              initializer=paddle.nn.initializer.Normal()
          ),
      )
      self.value_fc = nn.Linear(
          in_features=256,
          out_features=1,
          weight_attr=paddle.ParamAttr(
              initializer=paddle.nn.initializer.Normal()
          ),
          bias_attr=paddle.ParamAttr(
              initializer=paddle.nn.initializer.Normal()
          ),
      )
  
file_path: PARL/examples/IMPALA/atari_model.py
imports: import paddle
  import parl
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new AtariModel object from inherited base classes: parl with example: obj = AtariModel(act_dim)