code: def _sample_from_distributions(x):
      def _convert(d):
          return (
              d.sample((), seed=1234)
              if isinstance(d, tfp.distributions.Distribution)
              else d
          )
  
      return tf.nest.map_structure(_convert, x)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import shutil
  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 q_network
  from tf_agents.networks import q_rnn_network
  from tf_agents.policies import actor_policy
  from tf_agents.policies import policy_saver
  from tf_agents.policies import q_policy
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling a global function with example usage: _sample_from_distributions(x) and returns: tf, unknown