class_docstr: Integrated the analysis along a path
  
  This analyzer:
  * creates a path from input to reference image.
  * creates `steps` number of intermediate inputs and
    creates an analysis for them.
  * sums the analyses and multiplies them with the input-reference_input.
  
  This wrapper is used to implement Integrated Gradients.
  We refer to the paper for further information.
  
  :param subanalyzer: The analyzer to be wrapped.
  :param steps: Number of steps for integration.
  :param reference_inputs: The reference input.
code: def _reduce(self, Xs):
      tmp = super()._reduce(Xs)
      difference = self._keras_difference
      del self._keras_difference
  
      return [
          klayers.Multiply()([x, d]) for x, d in zip(tmp, difference)
      ]
  
imports: from __future__ import annotations
  import numpy
  import tensorflow.keras.backend
  import tensorflow.keras.layers
  import tensorflow.keras.models
  import innvestigate.backend
  import innvestigate.layers
  from innvestigate.analyzer.base import AnalyzerBase
  from innvestigate.analyzer.network_base import AnalyzerNetworkBase
  from innvestigate.backend.types import OptionalList, Tensor
label_desc: Use image node_id 6 for calling the PathIntegrator obj's underlying member method code with example usage: obj._reduce(Xs) and returns: unknown