code: def compute_td_targets(
      next_q_values: types.Tensor,
      rewards: types.Tensor,
      discounts: types.Tensor,
  ) -> types.Tensor:
      return tf.stop_gradient(rewards + discounts * next_q_values)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import typing
  import gin
  import tensorflow
  from tf_agents.agents import data_converter
  from tf_agents.agents import tf_agent
  from tf_agents.networks import utils
  from tf_agents.policies import epsilon_greedy_policy
  from tf_agents.policies import qtopt_cem_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.typing import types
  from tf_agents.utils import common
  from tf_agents.utils import eager_utils
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 1 for calling a global function with example usage: compute_td_targets(next_q_values, rewards, discounts) and returns: tf