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 __init__(
      self,
      *,
      name=None,
      states_spec=None,
      internals_spec=None,
      auxiliaries_spec=None,
      actions_spec=None,
      reward_spec=None,
  ):
      super().__init__(
          name=name,
          states_spec=states_spec,
          internals_spec=internals_spec,
          auxiliaries_spec=auxiliaries_spec,
          actions_spec=actions_spec,
          reward_spec=reward_spec,
      )
  
      if not all(
          spec.type == "float" for spec in self.actions_spec.values()
      ):
          raise TensorforceError.value(
              name="DeterministicPolicyGradient",
              argument="actions",
              value=self.actions_spec,
              hint="is not a float action",
          )
  
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 1 to create a new DeterministicPolicyGradient object from inherited base classes: Objective with example: obj = DeterministicPolicyGradient()