code: def assign_features_to_blocks(blocks, g, textset, ntype):
      # For the first block (which is closest to the input), copy the features from
      # the original graph as well as the texts.
      assign_simple_node_features(blocks[0].srcdata, g, ntype)
      assign_textual_node_features(blocks[0].srcdata, textset, ntype)
      assign_simple_node_features(blocks[-1].dstdata, g, ntype)
      assign_textual_node_features(blocks[-1].dstdata, textset, ntype)
  
imports: import argparse
  import pickle
  import time
  import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.data import DataLoader, IterableDataset
  from ..None import utils
label_desc: Use image node_id 5 for calling a global function with example usage: assign_features_to_blocks(blocks, g, textset, ntype) without return types