def METHOD_NAME():
    store = LocalFeatureStore()
    feat = torch.tensor([
        [0.0, 0.0, 0.0],
        [1.0, 1.0, 1.0],
        [2.0, 2.0, 2.0],
        [3.0, 3.0, 3.0],
        [4.0, 4.0, 4.0],
        [5.0, 5.0, 5.0],
        [6.0, 6.0, 6.0],
        [7.0, 7.0, 7.0],
        [8.0, 8.0, 8.0],
    ])
    paper_global_id = torch.tensor([1, 2, 3, 5, 8, 4])
    paper_feat = feat[paper_global_id]
    store.put_tensor(paper_feat, group_name='paper', attr_name='feat')
    assert len(store.get_all_tensor_attrs()) == 1
    attr = store.get_all_tensor_attrs()[0]
    assert attr.group_name == 'paper'
    assert attr.attr_name == 'feat'
    assert attr.index is None
    assert store.get_tensor_size(attr) == (6, 3)