def METHOD_NAME() -> None:
    """Testing the batch reconstruction."""
    # Check(s)
    data = _get_test_data()
    original_batch_idx = data.batch
    # Perform coarsening
    coarsening = coarsening = AttributeCoarsening(
        attributes=["x0", "x1", "x2"],
        reduce="avg",
        transfer_attributes=False,
    )
    pooled_data = coarsening(data)
    # Check that the number of batches is as expected.
    assert len(torch.unique(original_batch_idx)) == len(
        torch.unique(pooled_data.batch)
    )
    # Check that each event can be recovered
    assert len(pooled_data.to_data_list()) == len(
        torch.unique(original_batch_idx)
    )
    assert all([pooled_data[ix] for ix in range(len(pooled_data))])