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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def train_global(self, label_vector_description=None, N=None, limits=None, pivot=True, **kwargs):
 """ Train the model in a Cannon-like fashion using the grid points as labels and the intensities as normalised rest-frame fluxes. """


        lv = self._cannon_label_vector if label_vector_description is None else\
            self._interpret_label_vector(label_vector_description)
        lv_array, grid_indices, offsets = _build_label_vector_array(
            self.grid_points, lv, N, limits, pivot=pivot)
        return self._train(lv_array, grid_indices, offsets, lv, **kwargs)