cplx_adam_test.py 文件源码

def testTwoSessions(self):
    optimizer = ctf.train.CplxAdamOptimizer()
    g = tf.Graph()
    with g.as_default():
      with tf.Session():
        var0 = tf.Variable(np.array([1.0+1.0j, 2.0+2.0j], dtype=np.complex64),
                           name="v0")
        grads0 = tf.constant(np.array([0.1+0.1j, 0.1+0.1j], dtype=np.complex64))
        optimizer.apply_gradients([(grads0, var0)])

    gg = tf.Graph()
    with gg.as_default():
      with tf.Session():
        var0 = tf.Variable(np.array([1.0+1.0j, 2.0+2.0j], dtype=np.complex64),
                           name="v0")
        grads0 = tf.constant(np.array([0.1+0.1j, 0.1+0.1j], dtype=np.complex64))

        # If the optimizer saves any state not keyed by graph the following line
        # fails.
        optimizer.apply_gradients([(grads0, var0)])