test_optimizer.py 文件源码

def test_migrad():
    sess = tf.Session()
    x = tf.Variable(np.float64(2), name='x')
    sess.run(tf.initialize_variables([x]))
    optimizer = MigradOptimizer(session=sess)
    # With gradient
    results = optimizer.minimize([x], x**2, [2 * x])
    assert results.success
    # Without gradient
    results = optimizer.minimize([x], x**2)
    assert results.success
    @raises(ValueError)
    def test_illegal_parameter_as_variable1():
        optimizer.minimize([42], x**2)
    test_illegal_parameter_as_variable1()
    @raises(ValueError)
    def test_illegal_parameter_as_variable2():
        optimizer.minimize(42, x**2)
    test_illegal_parameter_as_variable2()