def _prepare_tables(self):
        """Prepares two tables, both with three distinct rows.
        The first table has two columns:
        1.0, 2.0 | 3.0
        2.0, 0.0 | 1.0
        1.0, 3.0 | 4.0
        The second table has three columns:
        1.0 | 2.0 | 3.0
        2.0 | 0.0 | 1.0
        1.0 | 3.0 | 4.0
        Returns:
        SegmentedTensors with the tables.
        """
        values = tf.constant(
            [
                [[1.0, 2.0, 3.0], [2.0, 0.0, 1.0], [1.0, 3.0, 4.0]],
                [[1.0, 2.0, 3.0], [2.0, 0.0, 1.0], [1.0, 3.0, 4.0]],
            ]
        )
        row_index = IndexMap(
            indices=[
                [[0, 0, 0], [1, 1, 1], [2, 2, 2]],
                [[0, 0, 0], [1, 1, 1], [2, 2, 2]],
            ],
            num_segments=3,
            batch_dims=1,
        )
        col_index = IndexMap(
            indices=[
                [[0, 0, 1], [0, 0, 1], [0, 0, 1]],
                [[0, 1, 2], [0, 1, 2], [0, 1, 2]],
            ],
            num_segments=3,
            batch_dims=1,
        )
        return values, row_index, col_index
Prepares two tables, both with three distinct rows.
        The first table has two columns:
        1.0, 2.0 | 3.0
        2.0, 0.0 | 1.0
        1.0, 3.0 | 4.0
        The second table has three columns:
        1.0 | 2.0 | 3.0
        2.0 | 0.0 | 1.0
        1.0 | 3.0 | 4.0
        Returns:
        SegmentedTensors with the tables.
        
dpkd/transformers/tests/models/tapas/test_modeling_tf_tapas.py