docs: def get_labels(self):
          """
          Returns a list of strings representing the values about
          which the discretization method calculates the probabilty
          masses.
  
          Default value is the points -
          [low, low+step, low+2*step, ......... , high-step]
          unless the method is overridden by a subclass.
  
          Examples
          --------
          >>> from pgmpy.factors import ContinuousNode
          >>> from pgmpy.discretize import BaseDiscretizer
          >>> class ChildDiscretizer(BaseDiscretizer):
          ...     def get_discrete_values(self):
          ...         pass
          >>> from scipy.stats import norm
          >>> node = ContinuousNode(norm(0).pdf)
          >>> child = ChildDiscretizer(node, -5, 5, 20)
          >>> chld.get_labels()
          ['x=-5.0', 'x=-4.5', 'x=-4.0', 'x=-3.5', 'x=-3.0', 'x=-2.5',
           'x=-2.0', 'x=-1.5', 'x=-1.0', 'x=-0.5', 'x=0.0', 'x=0.5', 'x=1.0',
           'x=1.5', 'x=2.0', 'x=2.5', 'x=3.0', 'x=3.5', 'x=4.0', 'x=4.5']
  
          """
          step = (self.high - self.low) / self.cardinality
          labels = ['x={i}'.format(i=str(i)) for i in np.round(
              np.arange(self.low, self.high, step), 3)]
          return labels