class_docstr: Base class for networks using Tensorforce layers.
code: def output_spec(self):
      if self.outputs is None:
          return self._output_spec
      else:
          self.outputs = tuple(
              output
              for output in self.outputs
              if output in self.registered_tensors_spec
          )
          output_spec = TensorsSpec(embedding=self._output_spec)
          output_spec.update(self.registered_tensors_spec[self.outputs])
          return output_spec
  
imports: from collections import Counter
  import tensorflow
  from tensorforce import TensorforceError
  from tensorforce.core import ArrayDict, Module, SignatureDict, TensorDict, TensorSpec, TensorsSpec, tf_function, tf_util
  from tensorforce.core.layers import Block, Layer, layer_modules, MultiInputLayer, NondeterministicLayer, PreprocessingLayer, Register, Reuse, StatefulLayer, TemporalLayer
  from tensorforce.core.parameters import Parameter
label_desc: Use image node_id 3 for calling the LayerbasedNetwork obj's underlying member method code with example usage: obj.output_spec() and returns: self, output_spec