def testCrossEntropyLossAllCorrect(self):
with self.test_session():
logits = tf.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
labels = tf.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
loss = losses.cross_entropy_loss(logits, labels)
self.assertEqual(loss.op.name, 'CrossEntropyLoss/value')
self.assertAlmostEqual(loss.eval(), 0.0, 3)
def testCrossEntropyLossAllWrongWithWeight(self):
with self.test_session():
logits = tf.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
labels = tf.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
loss = losses.cross_entropy_loss(logits, labels, weight=0.5)
self.assertEqual(loss.op.name, 'CrossEntropyLoss/value')
self.assertAlmostEqual(loss.eval(), 5.0, 3)
def testCrossEntropyLossAllWrongWithWeight(self):
with self.test_session():
logits = tf.constant([[10.0, 0.0, 0.0],
[0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
labels = tf.constant([[0, 0, 1],
[1, 0, 0],
[0, 1, 0]])
loss = losses.cross_entropy_loss(logits, labels, weight=0.5)
self.assertEquals(loss.op.name, 'CrossEntropyLoss/value')
self.assertAlmostEqual(loss.eval(), 5.0, 3)
