layers_test.py 文件源码

def test_fractalnet_smoketest(self):
    input_placeholder = tf.placeholder(tf.float32, [None, 3])
    output_placeholder = tf.placeholder(tf.float32, [None, 3])
    fractal_net = tdl.FractalNet(3, 2, lambda name: tdl.FC(3, name=name))
    result = fractal_net(input_placeholder)
    loss = tf.nn.l2_loss(result - output_placeholder)
    optr = tf.train.GradientDescentOptimizer(0.001)
    trainer = optr.minimize(loss)

    dataset = np.random.standard_normal([10, 3])
    answers = np.random.standard_normal([10, 3])

    feed_dict = {input_placeholder: dataset, output_placeholder: answers}
    with self.test_session() as sess:
      sess.run(tf.global_variables_initializer())
      old_loss = loss.eval(feed_dict)
      for unused_iteration in range(20):
        sess.run([trainer], feed_dict)
      new_loss = loss.eval(feed_dict)
      self.assertLess(new_loss, old_loss)