def test_add_evaluation_step(self):
with tf.Graph().as_default():
# Given
final = tf.placeholder(tf.float32, [1], name="final")
gt = tf.placeholder(tf.float32, [1], name="gt")
# When
accuracy = evaluation.evaluate(final, gt)
# Then
self.assertIsNotNone(accuracy)
self.assertEqual(type(accuracy).__name__, "Tensor")
def test_run_evaluation(self):
with tf.Graph().as_default():
with tf.Session() as sess:
# Given
final = tf.Variable([[0.1, 0.9], [0.1, 0.9]], dtype=tf.float32)
gt = tf.Variable([[0.6, 0.4], [0.2, 0.8]], dtype=tf.float32)
# When
accuracy = evaluation.evaluate(final, gt)
tf.initialize_all_variables().run()
# Then
self.assertAllClose(sess.run(accuracy), 0.5)