code: def test_temporal_dataloader(batch_size, drop_last):
      src = dst = t = torch.arange(10)
      msg = torch.randn(10, 16)
  
      data = TemporalData(src=src, dst=dst, t=t, msg=msg)
  
      loader = TemporalDataLoader(
          data,
          batch_size=batch_size,
          drop_last=drop_last,
      )
      assert len(loader) == 10 // batch_size
  
      for i, batch in enumerate(loader):
          assert len(batch) == batch_size
          arange = range(len(batch) * i, len(batch) * i + len(batch))
          assert batch.src.tolist() == data.src[arange].tolist()
          assert batch.dst.tolist() == data.dst[arange].tolist()
          assert batch.t.tolist() == data.t[arange].tolist()
          assert batch.msg.tolist() == data.msg[arange].tolist()
  
imports: import pytest
  import torch
  from torch_geometric.data import TemporalData
  from torch_geometric.loader import TemporalDataLoader
label_desc: Use image node_id 1 for calling a global function with example usage: test_temporal_dataloader(batch_size, drop_last) without return types