code: def predict(self, X):
          
          check_is_fitted(self, "cluster_centers_")
          X = self._check_array(X)
          labels = pairwise_distances_argmin_min(X, self.cluster_centers_)[0].astype(
              np.int32
          )
          return labels
docs: Predict the closest cluster each sample in X belongs to.
          In the vector quantization literature, `cluster_centers_` is called
          the code book and each value returned by `predict` is the index of
          the closest code in the code book.
  
          Parameters
          ----------
          X : array-like, shape = [n_samples, n_features]
              New data to predict.
  
          Returns
          -------
          labels : array, shape [n_samples,]
              Index of the cluster each sample belongs to.