docs: def remove_cpds(self, *cpds):
          """
          Removes the cpds that are provided in the argument.
  
          Parameters
          ----------
          *cpds : list, set, tuple (array-like)
              List of CPDs which are to be associated with the model. Each CPD
              should be an instance of `TabularCPD`.
  
          Examples
          --------
          >>> from pgmpy.models import DynamicBayesianNetwork as DBN
          >>> from pgmpy.factors.discrete import TabularCPD
          >>> dbn = DBN()
          >>> dbn.add_edges_from([(('D',0),('G',0)),(('I',0),('G',0)),(('D',0),('D',1)),(('I',0),('I',1))])
          >>> grade_cpd =  TabularCPD(('G',0), 3, [[0.3,0.05,0.9,0.5],
          ...                                      [0.4,0.25,0.8,0.03],
          ...                                      [0.3,0.7,0.02,0.2]], [('I', 0),('D', 0)],[2,2])
          >>> dbn.add_cpds(grade_cpd)
          >>> dbn.get_cpds()
          [<TabularCPD representing P(('G', 0):3 | ('I', 0):2, ('D', 0):2) at 0x3348ab0>]
          >>> dbn.remove_cpds(grade_cpd)
          >>> dbn.get_cpds()
          []
          """
          for cpd in cpds:
              if isinstance(cpd, (tuple, list)):
                  cpd = self.get_cpds(cpd)
              self.cpds.remove(cpd)