old_contents: 
  from .base import *
  
  from .gradient_based import *
  from .misc import *
  from .pattern_based import *
  from .relevance_based import *
  
  
  def create_explainer(name,
                       output_layer, patterns=None, to_layer=None, **kwargs):
      return {
          # Gradient based
          "gradient": GradientExplainer,
          "deconvnet": DeConvNetExplainer,
          "guided": GuidedBackpropExplainer,
          "gradient.alt": AlternativeGradientExplainer,
  
          # Relevance based
          "lrp.z": LRPZExplainer,
          "lrp.eps": LRPEpsExplainer,
  
          # Pattern based
          "patternnet": PatternNetExplainer,
          "patternnet.guided": GuidedPatternNetExplainer,
          "patternlrp": PatternLRPExplainer,
      }[name](output_layer, patterns=patterns, to_layer=to_layer, **kwargs)
  
new_contents: 
  from .base import *
  
  from .gradient_based import *
  from .misc import *
  from .pattern_based import *
  from .relevance_based import *
  
  
  def create_explainer(name,
                       output_layer, patterns=None, to_layer=None, **kwargs):
      return {
          # Utility.
          "input": InputExplainer,
          "random": RandomExplainer,
  
          # Gradient based
          "gradient": GradientExplainer,
          "deconvnet": DeConvNetExplainer,
          "guided": GuidedBackpropExplainer,
          "gradient.alt": AlternativeGradientExplainer,
  
          # Relevance based
          "lrp.z": LRPZExplainer,
          "lrp.eps": LRPEpsExplainer,
  
          # Pattern based
          "patternnet": PatternNetExplainer,
          "patternnet.guided": GuidedPatternNetExplainer,
          "patternlrp": PatternLRPExplainer,
      }[name](output_layer, patterns=patterns, to_layer=to_layer, **kwargs)
  
subject: Add input and random explainer to utility function.