class_docstr: Network consisting of Tensorforce layers (specification key: `custom` or `layered`), which can
  be specified as either a list of layer specifications in the case of a standard sequential
  layer-stack architecture, or as a list of list of layer specifications in the case of a more
  complex architecture consisting of multiple sequential layer-stacks. Note that the final
  action/value layer of the policy/baseline network is implicitly added, so the network output can
  be of arbitrary size and use any activation function, and is only required to be a rank-one
  embedding vector, or optionally have the same shape as the action in the case of a higher-rank
  action shape.
  
  Args:
      layers (iter[specification] | iter[iter[specification]]): Layers configuration, see the
          [layers documentation](../modules/layers.html)
          (<span style="color:#C00000"><b>required</b></span>).
      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>.
      inputs_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
      outputs (iter[string]): <span style="color:#0000C0"><b>internal use</b></span>.
code: def _recursive_get_architecture(*, layer):
      if isinstance(layer, list):
          return "----\n" + "\n".join(
              LayeredNetwork._recursive_get_architecture(layer=layer)
              for layer in layer
          )
  
      else:
          return layer.get_architecture()
  
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 LayeredNetwork obj's underlying member method code with example usage: obj._recursive_get_architecture() and returns: unknown, layer