class_docstr: Base class for value-based policies.
  
  Args:
      device (string): Device name
          (<span style="color:#00C000"><b>default</b></span>: inherit value of parent module).
      l2_regularization (float >= 0.0): Scalar controlling L2 regularization
          (<span style="color:#00C000"><b>default</b></span>: inherit value of parent module).
      name (string): <span style="color:#0000C0"><b>internal use</b></span>.
      states_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>.
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code: def input_signature(self, *, function):
      if function == "action_value":
          return SignatureDict(
              states=self.states_spec.signature(batched=True),
              horizons=TensorSpec(type="int", shape=(2,)).signature(
                  batched=True
              ),
              internals=self.internals_spec.signature(batched=True),
              auxiliaries=self.auxiliaries_spec.signature(batched=True),
              actions=self.actions_spec.signature(batched=True),
          )
  
      elif function == "action_values":
          return SignatureDict(
              states=self.states_spec.signature(batched=True),
              horizons=TensorSpec(type="int", shape=(2,)).signature(
                  batched=True
              ),
              internals=self.internals_spec.signature(batched=True),
              auxiliaries=self.auxiliaries_spec.signature(batched=True),
              actions=self.actions_spec.signature(batched=True),
          )
  
      elif function == "state_values":
          return SignatureDict(
              states=self.states_spec.signature(batched=True),
              horizons=TensorSpec(type="int", shape=(2,)).signature(
                  batched=True
              ),
              internals=self.internals_spec.signature(batched=True),
              auxiliaries=self.auxiliaries_spec.signature(batched=True),
          )
  
      else:
          try:
              return Policy.input_signature(
                  self=self, function=function
              )
          except NotImplementedError:
              try:
                  return StateValue.input_signature(
                      self=self, function=function
                  )
              except NotImplementedError:
                  return ActionValue.input_signature(
                      self=self, function=function
                  )
  
file_path: tensorforce/tensorforce/core/policies/value_policy.py
imports: import tensorflow
  from tensorforce.core import SignatureDict, TensorSpec, tf_function
  from tensorforce.core.policies import ActionValue, Policy, StateValue
label_desc: Use image node_id 2 for calling the ValuePolicy obj's underlying member method code with example usage: obj.input_signature() and returns: SignatureDict, SignatureDict, SignatureDict, Policy, StateValue, ActionValue