class_docstr: Base class for networks using Tensorforce layers.
code: def max_past_horizon(self, *, on_policy):
      past_horizons = [super().max_past_horizon(on_policy=on_policy)]
  
      def fn(layer):
          past_horizons.append(
              layer.max_past_horizon(on_policy=on_policy)
          )
  
      for layer in self.this_submodules:
          LayerbasedNetwork._recursive_temporal_layers(
              layer=layer, fn=fn
          )
  
      return max(past_horizons)
  
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 7 for calling the LayerbasedNetwork obj's underlying member method code with example usage: obj.max_past_horizon() and returns: max