code: def make_replay_buffer(policy):
      """Default replay buffer factory."""
      return tf_uniform_replay_buffer.TFUniformReplayBuffer(
          policy.trajectory_spec, batch_size=1
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Any
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.environments import py_environment
  from tf_agents.policies import py_policy
  from tf_agents.policies import tf_policy
  from tf_agents.replay_buffers import tf_uniform_replay_buffer
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
label_desc: Use image node_id 1 for calling a global function with example usage: make_replay_buffer(policy) and returns: tf_uniform_replay_buffer