class_docstr: Deterministic policy gradient objective (specification key: `det_policy_gradient`).
  
  Args:
      name (string): <span style="color:#0000C0"><b>internal use</b></span>.
      states_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
      internals_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
      auxiliaries_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
      actions_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
      reward_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
code: def reference(
      self, *, states, horizons, internals, auxiliaries, actions, policy
  ):
      # deterministic = tf_util.constant(value=True, dtype='bool')
      # return policy.act(
      #     states=states, horizons=horizons, internals=internals, auxiliaries=auxiliaries,
      #     deterministic=deterministic, independent=True
      # )
  
      return tf_util.zeros(
          shape=tf.shape(input=actions.value())[:1], dtype="float"
      )
  
file_path: tensorforce/tensorforce/core/objectives/deterministic_policy_gradient.py
imports: import tensorflow
  from tensorforce import TensorforceError
  from tensorforce.core import TensorSpec, tf_function, tf_util
  from tensorforce.core.objectives import Objective
label_desc: Use image node_id 5 for calling the DeterministicPolicyGradient obj's underlying member method code with example usage: obj.reference() and returns: tf_util