def test_create_ndcg_lambda_weight(self):
sorted_labels = [[2.0, 1.0]]
lambda_weight = ranking_losses.create_ndcg_lambda_weight()
max_dcg = 3.0 / math.log(2.) + 1.0 / math.log(3.)
with self.cached_session():
self.assertAllClose(
lambda_weight.pair_weights(sorted_labels).eval(),
[[[0., 2. * (1. / math.log(2.) - 1. / math.log(3.)) / max_dcg],
[2. * (1. / math.log(2.) - 1. / math.log(3.)) / max_dcg, 0.]]])
def test_create_ndcg_lambda_weight(self):
with tf.Graph().as_default():
labels = [[2.0, 1.0]]
ranks = [[1, 2]]
lambda_weight = ranking_losses.create_ndcg_lambda_weight()
scale = 2.
max_dcg = 3.0 / math.log(2.) + 1.0 / math.log(3.)
with self.cached_session():
self.assertAllClose(
lambda_weight.pair_weights(labels, ranks).eval() / scale,
[[[0., 2. * (1. / math.log(2.) - 1. / math.log(3.)) / max_dcg],
[2. * (1. / math.log(2.) - 1. / math.log(3.)) / max_dcg, 0.]]])