dl_unit_test.md

Unit Test for Deep Learning

Test all weights have been trained

def test_conv_net():
  image = tf.placeholder(tf.float32, (None, 100, 100, 3)
  model = Model(image)
  sess = tf.Session()
  sess.run(tf.global_variables_initializer())
  before = sess.run(tf.trainable_variables())
  _ = sess.run(model.train, feed_dict={
               image: np.ones((1, 100, 100, 3)),
               })
  after = sess.run(tf.trainable_variables())
  for b, a, n in zip(before, after):
      # Make sure something changed.
      assert (b != a).any()