code: def test_batch_with_sparse_tensor():
      x = SparseTensor.from_dense(torch.tensor([[1.0], [2.0], [3.0]]))
      edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]])
      adj = SparseTensor.from_edge_index(edge_index)
      data1 = Data(x=x, adj=adj)
  
      x = SparseTensor.from_dense(torch.tensor([[1.0], [2.0]]))
      edge_index = torch.tensor([[0, 1], [1, 0]])
      adj = SparseTensor.from_edge_index(edge_index)
      data2 = Data(x=x, adj=adj)
  
      x = SparseTensor.from_dense(
          torch.tensor([[1.0], [2.0], [3.0], [4.0]])
      )
      edge_index = torch.tensor(
          [[0, 1, 1, 2, 2, 3], [1, 0, 2, 1, 3, 2]]
      )
      adj = SparseTensor.from_edge_index(edge_index)
      data3 = Data(x=x, adj=adj)
  
      batch = Batch.from_data_list([data1])
      assert str(batch) == (
          "DataBatch(x=[3, 1, nnz=3], adj=[3, 3, nnz=4], "
          "batch=[3], ptr=[2])"
      )
      assert batch.num_graphs == len(batch) == 1
      assert batch.x.to_dense().tolist() == [[1], [2], [3]]
      assert batch.adj.coo()[0].tolist() == [0, 1, 1, 2]
      assert batch.adj.coo()[1].tolist() == [1, 0, 2, 1]
      assert batch.batch.tolist() == [0, 0, 0]
      assert batch.ptr.tolist() == [0, 3]
  
      batch = Batch.from_data_list([data1, data2, data3])
  
      assert str(batch) == (
          "DataBatch(x=[9, 1, nnz=9], adj=[9, 9, nnz=12], "
          "batch=[9], ptr=[4])"
      )
      assert batch.num_graphs == len(batch) == 3
      assert batch.x.to_dense().view(-1).tolist() == [
          1,
          2,
          3,
          1,
          2,
          1,
          2,
          3,
          4,
      ]
      assert batch.adj.coo()[0].tolist() == [
          0,
          1,
          1,
          2,
          3,
          4,
          5,
          6,
          6,
          7,
          7,
          8,
      ]
      assert batch.adj.coo()[1].tolist() == [
          1,
          0,
          2,
          1,
          4,
          3,
          6,
          5,
          7,
          6,
          8,
          7,
      ]
      assert batch.batch.tolist() == [0, 0, 0, 1, 1, 2, 2, 2, 2]
      assert batch.ptr.tolist() == [0, 3, 5, 9]
  
      assert str(batch[0]) == (
          "Data(x=[3, 1, nnz=3], adj=[3, 3, nnz=4])"
      )
      assert str(batch[1]) == (
          "Data(x=[2, 1, nnz=2], adj=[2, 2, nnz=2])"
      )
      assert str(batch[2]) == (
          "Data(x=[4, 1, nnz=4], adj=[4, 4, nnz=6])"
      )
  
      data_list = batch.to_data_list()
      assert len(data_list) == 3
  
      assert len(data_list[0]) == 2
      assert data_list[0].x.to_dense().tolist() == [[1], [2], [3]]
      assert data_list[0].adj.coo()[0].tolist() == [0, 1, 1, 2]
      assert data_list[0].adj.coo()[1].tolist() == [1, 0, 2, 1]
  
      assert len(data_list[1]) == 2
      assert data_list[1].x.to_dense().tolist() == [[1], [2]]
      assert data_list[1].adj.coo()[0].tolist() == [0, 1]
      assert data_list[1].adj.coo()[1].tolist() == [1, 0]
  
      assert len(data_list[2]) == 2
      assert data_list[2].x.to_dense().tolist() == [[1], [2], [3], [4]]
      assert data_list[2].adj.coo()[0].tolist() == [0, 1, 1, 2, 2, 3]
      assert data_list[2].adj.coo()[1].tolist() == [1, 0, 2, 1, 3, 2]
  
imports: import os.path
  import numpy
  import pytest
  import torch
  import torch_geometric
  from torch_geometric import EdgeIndex
  from torch_geometric.data import Batch, Data, HeteroData
  from torch_geometric.testing import get_random_edge_index, withPackage
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import to_edge_index, to_torch_sparse_tensor
label_desc: Use image node_id 3 for calling a global function with example usage: test_batch_with_sparse_tensor() without return types