text: """Random policy implementation."""
  
  from rllib.util.neural_networks.utilities import get_batch_size
  
  from .abstract_policy import AbstractPolicy
  
  
  class RandomPolicy(AbstractPolicy):
      """Random Policy implementation of AbstractPolicy base class.
  
      This policy will always return a centered distribution with a unit scaling.
  
      """
  
      def __init__(self, *args, **kwargs):
          super().__init__(*args, **kwargs)
  
      def forward(self, state):
          """Get distribution over actions."""
          batch_size = get_batch_size(state, self.dim_state)
          if batch_size:
              return self.random(batch_size)
          else:
              return self.random()
  