code: def testSkipConstantSlicesOverall(self):
      original = numpy.ones([2, 2], dtype="float32")
  
      # Add singleton dimensions to trainsform the input vector into a tensor
      original = numpy.expand_dims(original, axis=[0, 1])
  
      result = TensorNormalize(
          scaler="standard", axis=-1, skipConstantSlices=False
      )(original)
  
      self.assertTrue(numpy.isnan(result).all())
  
imports: from essentia_test import *
  from sklearn.preprocessing import MinMaxScaler, StandardScaler
label_desc: Use image node_id 15 for calling the TestTensorNormalize obj's underlying member method code with example usage: obj.testSkipConstantSlicesOverall() without return types