class_docstr: Basic LRP decomposition rule (for layers with weight kernels),
  which considers the bias a constant input neuron.
class_docstr_tok: ["Basic","LRP","decomposition","rule","(","for","layers","with","weight","kernels",")",",","which","considers","the","bias","a","constant","input","neuron","."]
code: def __init__(self, layer: Layer, _state, bias: bool = True) -> None:
      self._layer_wo_act = igraph.copy_layer_wo_activation(
          layer, keep_bias=bias, name_template="reversed_kernel_%s"
      )
  
imports: from __future__ import annotations
  import numpy
  import tensorflow.keras.backend
  import tensorflow.keras.layers
  import innvestigate.analyzer.relevance_based.utils
  import innvestigate.backend
  import innvestigate.backend.graph
  import innvestigate.layers
  from innvestigate.backend.types import Layer, OptionalList, Tensor
label_desc: Use image node_id 1 to create a new ZRule object from inherited base classes: igraph with example: obj = ZRule(layer, _state, bias)