code: def get_collect_data_spec_from_policy_and_env(env, policy):
      """Returns collect data spec from policy and environment.
  
      Args:
        env: instance of the environment used for collection
        policy: policy for collection to get policy spec
  
      Meant to be used for collection jobs (i.e. Actors) without having to
      construct an agent instance but directly from a policy (which can be loaded
      from a saved model).
      """
      observation_tensor_spec = tensor_spec.from_spec(
          env.observation_spec()
      )
      time_step_tensor_spec = ts.time_step_spec(observation_tensor_spec)
      policy_step_tensor_spec = tensor_spec.from_spec(
          policy.policy_step_spec
      )
      collect_data_spec = trajectory.from_transition(
          time_step_tensor_spec,
          policy_step_tensor_spec,
          time_step_tensor_spec,
      )
      return collect_data_spec
  
imports: from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
label_desc: Use image node_id 2 for calling a global function with example usage: get_collect_data_spec_from_policy_and_env(env, policy) and returns: collect_data_spec