class_docstr: Universal Transformer(https://arxiv.org/pdf/1807.03819.pdf) with ACT(https://arxiv.org/pdf/1603.08983.pdf).
docstr: Update the node states and edge states of the graph.
docstr_tok: ["Update","the","node","states","and","edge","states","of","the","graph","."]
code: def update_graph(self, g, eids, pre_pairs, post_pairs):
      "Update the node states and edge states of the graph."
      # Pre-compute queries and key-value pairs.
      for pre_func, nids in pre_pairs:
          g.apply_nodes(pre_func, nids)
      self.propagate_attention(g, eids)
      # Further calculation after attention mechanism
      for post_func, nids in post_pairs:
          g.apply_nodes(post_func, nids)
  
imports: from .attention import *
  from .layers import *
  from .functions import *
  from .embedding import *
  import dgl.function
  import torch
  import torch.nn.init
label_desc: Use image node_id 6 for calling the UTransformer obj's underlying member method code with example usage: obj.update_graph(g, eids, pre_pairs, post_pairs) without return types