code: def fit(self, X):
          
          if X.ndim > 2:
              X = X.reshape((np.prod(X.shape[:-1]), X.shape[-1]))
          self.mean = X.mean(0)
          self.std = X.std(0)
          self.is_fit = True
          return self
docs: Fit the scaler based on some data.
  
          Takes the columnwise mean and standard deviation of the entire input
          array.
          If the array has more than 2 dimensions, it is flattened.
  
          Parameters
          ----------
          X : numpy array
  
          Returns
          -------
          scaled : numpy array
              A scaled version of said array.