code: def test_paddedbatch(device):
      from speechbrain.dataio.batch import PaddedBatch
  
      batch = PaddedBatch(
          [
              {
                  "id": "ex1",
                  "foo": torch.Tensor([1.0]).to(device),
                  "bar": torch.Tensor([1.0, 2.0, 3.0]).to(device),
              },
              {
                  "id": "ex2",
                  "foo": torch.Tensor([2.0, 1.0]).to(device),
                  "bar": torch.Tensor([2.0]).to(device),
              },
          ]
      )
      batch.to(dtype=torch.half)
      assert batch.foo.data.dtype == torch.half
      assert batch["foo"][1].dtype == torch.half
      assert batch.bar.lengths.dtype == torch.half
      assert batch.foo.data.shape == torch.Size([2, 2])
      assert batch.bar.data.shape == torch.Size([2, 3])
      ids, foos, bars = batch
      assert ids == ["ex1", "ex2"]
  
imports: import pytest
  import torch
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: test_paddedbatch(device) without return types