code: def test_pad_data_non_tensor_attr():
      data = fake_data()
      batch_size = 13
      data.batch_size = batch_size
  
      transform = Pad(max_num_nodes=100)
      padded = transform(data)
      assert padded.batch_size == batch_size
  
      exclude_transform = Pad(
          max_num_nodes=101, exclude_keys=("batch_size",)
      )
      padded = exclude_transform(data)
      assert "batch_size" not in padded.keys()
  
imports: import numbers
  from typing import Dict, Generator, List, Optional, Tuple, Union
  import pytest
  import torch
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.datasets import FakeDataset, FakeHeteroDataset
  from torch_geometric.transforms import Pad
  from torch_geometric.transforms.pad import AttrNamePadding, EdgeTypePadding, NodeTypePadding, Padding, UniformPadding
  from torch_geometric.typing import EdgeType, NodeType
label_desc: Use image node_id 23 for calling a global function with example usage: test_pad_data_non_tensor_attr() without return types