code: def __init__(self, observation_shape, action_space, recurrent_policy):
      super().__init__()
  
      # Image input only for now...
      self.base = CNNBase(observation_shape[0], recurrent_policy)
  
      # Discrete space only for now...
      self.distribution = Categorical(
          self.base.output_size, action_space
      )
      self.state_size = self.base.state_size
  
file_path: SerpentAI/serpent/machine_learning/reinforcement_learning/ppo/policy.py
imports: import torch
  from .cnn_base import CNNBase
  from .distributions import Categorical
label_desc: Use image node_id 1 to create a new Policy object from inherited base classes: torch.nn with example: obj = Policy(observation_shape, action_space, recurrent_policy)