from tensorflow.python.framework import constant_op

        'batch2-FC1-F1_X_batch2-FC2-F1', 'batch2-FC1-F1_X_batch2-FC2-F2',
        'batch2-FC1-F2_X_batch2-FC2-F1', 'batch2-FC1-F2_X_batch2-FC2-F2'
    ]])
    with self.test_session() as sess:
      self._assert_sparse_tensor_equals(expected_out, sess.run(op))

  def test_dense(self):
    """Tests only dense inputs.
    """
    op = sparse_feature_cross_op.sparse_feature_cross([
        constant_op.constant([['batch1-FC1-F1', 'batch1-FC1-F2'],
                              ['batch2-FC1-F1', 'batch2-FC1-F2']],
                             dtypes.string),
        constant_op.constant([['batch1-FC2-F1', 'batch1-FC2-F2'],
                              ['batch2-FC2-F1', 'batch2-FC2-F2']],
                             dtypes.string),
    ])
    expected_out = self._sparse_tensor([[
        'batch1-FC1-F1_X_batch1-FC2-F1', 'batch1-FC1-F1_X_batch1-FC2-F2',
        'batch1-FC1-F2_X_batch1-FC2-F1', 'batch1-FC1-F2_X_batch1-FC2-F2'
    ], [
        'batch2-FC1-F1_X_batch2-FC2-F1', 'batch2-FC1-F1_X_batch2-FC2-F2',
        'batch2-FC1-F2_X_batch2-FC2-F1', 'batch2-FC1-F2_X_batch2-FC2-F2'
    ]])
    with self.test_session() as sess:
      self._assert_sparse_tensor_equals(expected_out, sess.run(op))
