class_docstr: Deconvnet analyzer.
  
  Applies the "deconvnet" algorithm to analyze the model.
  
  :param model: A Keras model.
class_docstr_tok: ["Deconvnet","analyzer",".","Applies","the","``","deconvnet","''","algorithm","to","analyze","the","model",".",":","param","model",":","A","Keras","model","."]
code: def _create_analysis(self, *args, **kwargs):
      self._add_conditional_reverse_mapping(
          lambda layer: ichecks.contains_activation(layer, "relu"),
          DeconvnetReverseReLULayer,
          name="deconvnet_reverse_relu_layer",
      )
  
      return super()._create_analysis(*args, **kwargs)
  
imports: from __future__ import annotations
  import tensorflow
  import tensorflow.keras.backend
  import tensorflow.keras.layers
  import innvestigate.backend
  import innvestigate.backend.checks
  import innvestigate.backend.graph
  from innvestigate.analyzer.network_base import AnalyzerNetworkBase
  from innvestigate.analyzer.reverse_base import ReverseAnalyzerBase
  from innvestigate.analyzer.wrapper import GaussianSmoother, PathIntegrator
  from innvestigate.backend.types import List, OptionalList, Tensor
label_desc: Use image node_id 2 for calling the Deconvnet obj's underlying member method code with example usage: obj._create_analysis() and returns: super