code: def test_NonFittableAnomalyScorer(self):
      for scorer in list_NonFittableAnomalyScorer:
          # Check if trainable is False, being a NonFittableAnomalyScorer
          assert not scorer.trainable
  
          # checks for score_from_prediction()
          # input must be Timeseries or sequence of Timeseries
          with pytest.raises(ValueError):
              scorer.score_from_prediction(self.train, "str")
          with pytest.raises(ValueError):
              scorer.score_from_prediction(
                  [self.train, self.train], [self.modified_train, "str"]
              )
          # score on sequence with series that have different width
          with pytest.raises(ValueError):
              scorer.score_from_prediction(
                  self.train, self.modified_mts_train
              )
          # input sequences have different length
          with pytest.raises(ValueError):
              scorer.score_from_prediction(
                  [self.train, self.train], [self.modified_train]
              )
          # two inputs must have a non zero intersection
          with pytest.raises(ValueError):
              scorer.score_from_prediction(
                  self.train[:50], self.train[55:]
              )
          # every pairwise element must have a non zero intersection
          with pytest.raises(ValueError):
              scorer.score_from_prediction(
                  [self.train, self.train[:50]],
                  [self.train, self.train[55:]],
              )
  
imports: from typing import Sequence
  import numpy
  import pytest
  import sklearn
  from pyod.models.knn import KNN
  from scipy.stats import cauchy, expon, gamma, laplace, norm, poisson
  from darts import TimeSeries
  from darts.ad.scorers import CauchyNLLScorer
  from darts.ad.scorers import DifferenceScorer
  from darts.ad.scorers import ExponentialNLLScorer, GammaNLLScorer, GaussianNLLScorer, KMeansScorer, LaplaceNLLScorer
  from darts.ad.scorers import NormScorer
  from darts.ad.scorers import PoissonNLLScorer, PyODScorer, WassersteinScorer
  from darts.models import MovingAverageFilter
label_desc: Use image node_id 4 for calling the TestADAnomalyScorer obj's underlying member method code with example usage: obj.test_NonFittableAnomalyScorer() without return types