parameters: (self, X=None, y=None, groups=None)
return_statement: return cv.get_n_splits(X, y, groups) * self.n_repeats
docstring: Returns the number of splitting iterations in the cross-validator
  
          Parameters
          ----------
          X : object
              Always ignored, exists for compatibility.
              ``np.zeros(n_samples)`` may be used as a placeholder.
  
          y : object
              Always ignored, exists for compatibility.
              ``np.zeros(n_samples)`` may be used as a placeholder.
  
          groups : array-like, with shape (n_samples,), optional
              Group labels for the samples used while splitting the dataset into
              train/test set.
  
          Returns
          -------
          n_splits : int
              Returns the number of splitting iterations in the cross-validator.
docstring_summary: Returns the number of splitting iterations in the cross-validator
docstring_tokens: Returns the number of splitting iterations in the cross - validator
function: def get_n_splits(self, X=None, y=None, groups=None):
          """Returns the number of splitting iterations in the cross-validator
  
          Parameters
          ----------
          X : object
              Always ignored, exists for compatibility.
              ``np.zeros(n_samples)`` may be used as a placeholder.
  
          y : object
              Always ignored, exists for compatibility.
              ``np.zeros(n_samples)`` may be used as a placeholder.
  
          groups : array-like, with shape (n_samples,), optional
              Group labels for the samples used while splitting the dataset into
              train/test set.
  
          Returns
          -------
          n_splits : int
              Returns the number of splitting iterations in the cross-validator.
          """
          rng = check_random_state(self.random_state)
          cv = self.cv(random_state=rng, shuffle=True,
                       **self.cvargs)
          return cv.get_n_splits(X, y, groups) * self.n_repeats
function_tokens: def get_n_splits ( self , X = None , y = None , groups = None ) : rng = check_random_state ( self . random_state ) cv = self . cv ( random_state = rng , shuffle = True , * * self . cvargs ) return cv . get_n_splits ( X , y , groups ) * self . n_repeats