class_docstr: A convolutional value and policy networks for SAC.
  
  This uses the SAC-AE network for processing images. For more information,
  view SACEncoderNetwork.
class_docstr_tok: ["A","convolutional","value","and","policy","networks","for","SAC",".","This","uses","the","SAC-AE","network","for","processing","images",".","For","more","information",",","view","SACEncoderNetwork","."]
code: def setup(self):
      self._encoder = SACEncoderNetwork()
      self._sac_network = continuous_networks.SACNetwork(
          self.action_shape,
          self.num_layers,
          self.hidden_units,
          self.action_limits,
      )
  
file_path: dopamine/dopamine/labs/sac_from_pixels/continuous_networks.py
imports: import dataclasses
  from typing import Optional, Tuple
  from dopamine.jax import continuous_networks
  from flax import linen
  import gin
  import jax
  from jax import numpy
label_desc: Use image node_id 1 for calling the SACConvNetwork obj's underlying member method code with example usage: obj.setup() without return types