clip_gradient_test.py 文件源码

def testOpClip(self):
    x = tf.placeholder(tf.float32, shape=[2, 1])
    y = snt.clip_gradient(x, 2, 3)
    z = tf.reduce_sum(y * y)
    dzdy = tf.gradients(z, y)[0]
    dzdx = tf.gradients(z, x)[0]

    x_np = np.array([[0.5], [2]])
    with self.test_session() as sess:
      y_np, dzdy_np, dzdx_np = sess.run([y, dzdy, dzdx], feed_dict={x: x_np})

      self.assertAllEqual(y_np, x_np)
      # We do not expect the gradients with respect to the output to be clipped.
      self.assertAllEqual(dzdy_np, np.array([[1], [4]]))
      # We expect the gradients with respect to the input to be clipped [2, 3].
      self.assertAllEqual(dzdx_np, np.array([[2], [3]]))