code: def dummyModelParams(perm):
      """This function can be used for Hypersearch algorithm development. When
      present, we don't actually run the CLA model in the OPF, but instead run
      a dummy model. This function returns the dummy model params that will be
      used. See the OPFDummyModelRunner class source code (in
      nupic.swarming.ModelRunner) for a description of the schema for
      the dummy model params.
      """
  
      errScore = 500
  
      if (
          not perm["modelParams"]["sensorParams"]["encoders"]["A"]
          is None
      ):
          errScore -= 40
      if (
          not perm["modelParams"]["sensorParams"]["encoders"]["B"]
          is None
      ):
          errScore -= 30
      if (
          not perm["modelParams"]["sensorParams"]["encoders"]["C"]
          is None
      ):
          errScore -= 20
      delay = 0
  
      # Make the best model in sprint 0 run slower so that we create more
      #  speculative models
      encoderCount = 0
      encoders = perm["modelParams"]["sensorParams"]["encoders"]
      for field, encoder in encoders.items():
          if encoder is not None:
              encoderCount += 1
  
      # NOTE: The _classifierInput is always present. It seems that speculation
      #  favors fields that are not done yet, so make the worse fields take
      #  longer so that the speculative particles choose them in the second
      #  sprint.
      if encoderCount == 2:
          delay = 0.1
  
      # Make speculative swarms that should be killed take longer...
      elif (
          encoderCount == 3
          and perm["modelParams"]["sensorParams"]["encoders"]["A"]
          is None
      ):
          delay = 0.2
  
      # Make the best possible combination take the longest so that we have
      #  an opportunity to kill other swarms before we finish
      elif encoderCount == 3:
          delay = 0.3
  
      dummyModelParams = dict(
          metricValue=errScore,
          metricFunctions=None,
          delay=delay,
      )
  
      return dummyModelParams
  
label_desc: Use image node_id 1 for calling a global function with example usage: dummyModelParams(perm) and returns: dummyModelParams