nn_test.py 文件源码

def testL2Loss(self):
    with self.test_session():
      x = tf.constant([1.0, 0.0, 3.0, 2.0], shape=[2, 2], name="x")
      l2loss = tf.nn.l2_loss(x)
      value = l2loss.eval()
    self.assertAllClose(7.0, value)

  # def testGradient(self):
  #   x_shape = [20, 7, 3]
  #   np.random.seed(1)  # Make it reproducible.
  #   x_val = np.random.random_sample(x_shape).astype(np.float64)
  #   with self.test_session():
  #     x = tf.constant(x_val, name="x")
  #     output = tf.nn.l2_loss(x)
  #     err = tf.test.compute_gradient_error(x, x_shape, output, [1])
  #   print("L2Loss gradient err = %g " % err)
  #   err_tolerance = 1e-11
  #   self.assertLess(err, err_tolerance)