class_docstr: Interface for wrappers around analyzers
  
  This class is the basic interface for wrappers around analyzers.
  
  :param subanalyzer: The analyzer to be wrapped.
code: def __init__(self, subanalyzer: AnalyzerBase, *args, **kwargs):
      if not isinstance(subanalyzer, AnalyzerNetworkBase):
          raise NotImplementedError("Keras-based subanalyzer required.")
  
      # To simplify serialization, additionaly passed models are popped
      # and the subanalyzer model is passed to `AnalyzerBase`.
      kwargs.pop("model", None)
      super().__init__(subanalyzer._model, *args, **kwargs)
  
      self._subanalyzer_name = subanalyzer.__class__.__name__
      self._subanalyzer = subanalyzer
  
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 1 to create a new WrapperBase object from inherited base classes: AnalyzerBase with example: obj = WrapperBase(subanalyzer)