code: def _normalize(mx):
      """Row-normalize sparse matrix"""
      rowsum = np.asarray(mx.sum(1))
      mask = np.equal(rowsum, 0.0).flatten()
      rowsum[mask] = np.nan
      r_inv = np.power(rowsum, -1).flatten()
      r_inv[mask] = 0.0
      r_mat_inv = sp.diags(r_inv)
      return r_mat_inv.dot(mx)
  
imports: from __future__ import absolute_import
  import os, sys
  import pickle
  import warnings
  import networkx
  import numpy
  import scipy.sparse
  from ..None import backend, batch, convert
  from ..convert import from_networkx, graph, to_networkx
  from ..transforms import reorder_graph
  from .dgl_dataset import DGLBuiltinDataset
  from .utils import _get_dgl_url, deprecate_function, deprecate_property, generate_mask_tensor, load_graphs, load_info, makedirs, save_graphs, save_info
label_desc: Use image node_id 8 for calling a global function with example usage: _normalize(mx) and returns: r_mat_inv