code: def create_analyzer(
      name: str, model: Model, **kwargs
  ) -> AnalyzerBase:
      """Instantiates the analyzer with the name 'name'
  
      This convenience function takes an analyzer name
      creates the respective analyzer.
  
      Alternatively analyzers can be created directly by
      instantiating the respective classes.
  
      :param name: Name of the analyzer.
      :param model: The model to analyze, passed to the analyzer's __init__.
      :param kwargs: Additional parameters for the analyzer's .
      :return: An instance of the chosen analyzer.
      :raise KeyError: If there is no analyzer with the passed name.
      """
      try:
          analyzer_class = analyzers[name]
      except KeyError:
          raise KeyError(
              f"No analyzer with the name '{name}' could be found."
              f" All possible names are: {list(analyzers.keys())}"
          )
      return analyzer_class(model, **kwargs)
  
file_path: innvestigate/src/innvestigate/analyzer/__init__.py
imports: from __future__ import annotations
  from innvestigate.analyzer.base import AnalyzerBase
  from innvestigate.analyzer.deeptaylor import BoundedDeepTaylor, DeepTaylor
  from innvestigate.analyzer.gradient_based import BaselineGradient, Deconvnet, Gradient, GuidedBackprop, InputTimesGradient, IntegratedGradients, SmoothGrad
  from innvestigate.analyzer.misc import Input, Random
  from innvestigate.analyzer.relevance_based.relevance_analyzer import LRP, LRPZ, BaselineLRPZ, LRPAlpha1Beta0, LRPAlpha1Beta0IgnoreBias, LRPAlpha2Beta1, LRPAlpha2Beta1IgnoreBias, LRPAlphaBeta, LRPEpsilon, LRPFlat, LRPSequentialPresetA, LRPSequentialPresetAFlat, LRPSequentialPresetB, LRPSequentialPresetBFlat, LRPSequentialPresetBFlatUntilIdx, LRPWSquare, LRPZPlus, LRPZPlusFast
  from innvestigate.analyzer.wrapper import AugmentReduceBase
  from innvestigate.analyzer.wrapper import GaussianSmoother
  from innvestigate.analyzer.wrapper import PathIntegrator
  from innvestigate.analyzer.wrapper import WrapperBase
  from innvestigate.backend.types import Model
label_desc: Use image node_id 1 for calling a global function with example usage: create_analyzer(name, model) and returns: analyzer_class