code: def call(self, observations, step_type, network_state):
      action_means, network_state = super(
          DummyActionDistributionNet, self
      ).call(observations, step_type, network_state)
  
      def _action_distribution(action_mean):
          action_std = tf.ones_like(action_mean)
          return tfp.distributions.Normal(action_mean, action_std)
  
      return (
          tf.nest.map_structure(_action_distribution, action_means),
          network_state,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import network
  from tf_agents.policies import actor_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling the DummyActionDistributionNet obj's underlying member method code with example usage: obj.call(observations, step_type, network_state) and returns: tf,  network_state, tfp