code: def describe_data(data):
      g = data[0]
  
      n_edges = g.number_of_edges()
      num_classes = data.num_classes
  
      train_mask = g.ndata["train_mask"]
      val_mask = g.ndata["val_mask"]
      test_mask = g.ndata["test_mask"]
  
      description = textwrap.dedent(
          f"""
          ----Data statistics----
          Edges           {n_edges:,.0f}
          Classes         {num_classes:,.0f}
          Train samples   {_sum_boolean_tensor(train_mask):,.0f}
          Val samples     {_sum_boolean_tensor(val_mask):,.0f}
          Test samples    {_sum_boolean_tensor(test_mask):,.0f}
          """
      )
      return description
  
imports: import argparse
  import textwrap
  import tensorflow
  import tensorflow_addons
  from dgl.data import CiteseerGraphDataset, CoraGraphDataset, PubmedGraphDataset
  from dgl.nn.tensorflow.conv import SGConv
label_desc: Use image node_id 3 for calling a global function with example usage: describe_data(data) and returns: description