def testTrivialCompatibilityWithHinge(self):
# Tests compatibility with unweighted hinge loss.
x_shape = [55, 10]
logits = tf.constant(np.random.randn(*x_shape).astype(np.float32))
targets = tf.to_float(tf.constant(np.random.random_sample(x_shape) > 0.3))
weighted_loss = util.weighted_hinge_loss(targets, logits)
expected_loss = hinge_loss(targets, logits)
with self.test_session():
self.assertAllClose(expected_loss.eval(), weighted_loss.eval())
def testTrivialCompatibilityWithHinge(self):
# Tests compatibility with unweighted hinge loss.
x_shape = [55, 10]
logits = tf.constant(np.random.randn(*x_shape).astype(np.float32))
targets = tf.to_float(tf.constant(np.random.random_sample(x_shape) > 0.3))
weighted_loss = util.weighted_hinge_loss(targets, logits)
expected_loss = hinge_loss(targets, logits)
with self.test_session():
self.assertAllClose(expected_loss.eval(), weighted_loss.eval())
def testLessTrivialCompatibilityWithHinge(self):
# Tests compatibility with a constant weight for positives and negatives.
x_shape = [56, 11]
logits = tf.constant(np.random.randn(*x_shape).astype(np.float32))
targets = tf.to_float(tf.constant(np.random.random_sample(x_shape) > 0.7))
weight = 1.0 + 1.0/2 + 1.0/3 + 1.0/4 + 1.0/5 + 1.0/6 + 1.0/7
weighted_loss = util.weighted_hinge_loss(targets, logits, weight, weight)
expected_loss = hinge_loss(targets, logits) * weight
with self.test_session():
self.assertAllClose(expected_loss.eval(), weighted_loss.eval())
def testLessTrivialCompatibilityWithHinge(self):
# Tests compatibility with a constant weight for positives and negatives.
x_shape = [56, 11]
logits = tf.constant(np.random.randn(*x_shape).astype(np.float32))
targets = tf.to_float(tf.constant(np.random.random_sample(x_shape) > 0.7))
weight = 1.0 + 1.0/2 + 1.0/3 + 1.0/4 + 1.0/5 + 1.0/6 + 1.0/7
weighted_loss = util.weighted_hinge_loss(targets, logits, weight, weight)
expected_loss = hinge_loss(targets, logits) * weight
with self.test_session():
self.assertAllClose(expected_loss.eval(), weighted_loss.eval())
def test3DLogitsAndTargets(self):
# Tests correctness when logits is 3D and targets is 2D.
targets_shape = [30, 4]
logits_shape = [targets_shape[0], targets_shape[1], 3]
targets = tf.to_float(
tf.constant(np.random.random_sample(targets_shape) > 0.7))
logits = tf.constant(np.random.randn(*logits_shape).astype(np.float32))
weight_vector = [1.0, 1.0, 1.0]
loss = util.weighted_hinge_loss(targets, logits, weight_vector)
with self.test_session():
loss_value = loss.eval()
for i in range(len(weight_vector)):
expected = hinge_loss(targets, logits[:, :, i]).eval()
self.assertAllClose(loss_value[:, :, i], expected)
def test3DLogitsAndTargets(self):
# Tests correctness when logits is 3D and targets is 2D.
targets_shape = [30, 4]
logits_shape = [targets_shape[0], targets_shape[1], 3]
targets = tf.to_float(
tf.constant(np.random.random_sample(targets_shape) > 0.7))
logits = tf.constant(np.random.randn(*logits_shape).astype(np.float32))
weight_vector = [1.0, 1.0, 1.0]
loss = util.weighted_hinge_loss(targets, logits, weight_vector)
with self.test_session():
loss_value = loss.eval()
for i in range(len(weight_vector)):
expected = hinge_loss(targets, logits[:, :, i]).eval()
self.assertAllClose(loss_value[:, :, i], expected)
def testNontrivialCompatibilityWithHinge(self):
# Tests compatibility with different positive and negative weights.
x_shape = [23, 8]
logits_positives = tf.constant(np.random.randn(*x_shape).astype(np.float32))
logits_negatives = tf.constant(np.random.randn(*x_shape).astype(np.float32))
targets_positives = tf.ones(x_shape)
targets_negatives = tf.zeros(x_shape)
logits = tf.concat([logits_positives, logits_negatives], 0)
targets = tf.concat([targets_positives, targets_negatives], 0)
raw_loss = util.weighted_hinge_loss(targets,
logits,
positive_weights=3.4,
negative_weights=1.2)
loss = tf.reduce_sum(raw_loss, 0)
positives_hinge = hinge_loss(targets_positives, logits_positives)
negatives_hinge = hinge_loss(targets_negatives, logits_negatives)
expected = tf.add(tf.reduce_sum(3.4 * positives_hinge, 0),
tf.reduce_sum(1.2 * negatives_hinge, 0))
with self.test_session():
self.assertAllClose(loss.eval(), expected.eval())
def testNontrivialCompatibilityWithHinge(self):
# Tests compatibility with different positive and negative weights.
x_shape = [23, 8]
logits_positives = tf.constant(np.random.randn(*x_shape).astype(np.float32))
logits_negatives = tf.constant(np.random.randn(*x_shape).astype(np.float32))
targets_positives = tf.ones(x_shape)
targets_negatives = tf.zeros(x_shape)
logits = tf.concat([logits_positives, logits_negatives], 0)
targets = tf.concat([targets_positives, targets_negatives], 0)
raw_loss = util.weighted_hinge_loss(targets,
logits,
positive_weights=3.4,
negative_weights=1.2)
loss = tf.reduce_sum(raw_loss, 0)
positives_hinge = hinge_loss(targets_positives, logits_positives)
negatives_hinge = hinge_loss(targets_negatives, logits_negatives)
expected = tf.add(tf.reduce_sum(3.4 * positives_hinge, 0),
tf.reduce_sum(1.2 * negatives_hinge, 0))
with self.test_session():
self.assertAllClose(loss.eval(), expected.eval())