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import paddle

x = paddle.to_tensor([i for i in range(4)], dtype='float32', stop_gradient=False)
x

Tensor(shape=[4], dtype=float32, place=Place(gpu:0), stop_gradient=False, [0., 1., 2., 3.])

paddle.is_grad_enabled()

True

y = 2 * paddle.dot(x, x)
y

Tensor(shape=[1], dtype=float32, place=Place(gpu:0), stop_gradient=False, [28.])

paddle.autograd.backward(y, retain_graph=True)
x.grad

Tensor(shape=[4], dtype=float32, place=Place(gpu:0), stop_gradient=False, [0. , 4. , 8. , 12.])

x.grad == 4 * x

Tensor(shape=[4], dtype=bool, place=Place(gpu:0), stop_gradient=True, [True, True, True, True])

x.clear_grad()
y = x.sum()
paddle.autograd.backward(y, retain_graph=True)
x.grad

Tensor(shape=[4], dtype=float32, place=Place(gpu:0), stop_gradient=False, [1., 1., 1., 1.])

x.clear_grad()
y = x * x
paddle.autograd.backward(y.sum(), retain_graph=True)
x.grad

Tensor(shape=[4], dtype=float32, place=Place(gpu:0), stop_gradient=False, [0., 2., 4., 6.])

将计算移出记录的计算图

x.clear_grad()
y = x * x
u = y.detach()
z = u * x

paddle.autograd.backward(z.sum(), retain_graph=True)
x.grad == u

Tensor(shape=[4], dtype=bool, place=Place(gpu:0), stop_gradient=True, [True, True, True, True])

x.clear_grad()
paddle.autograd.backward(y.sum(), retain_graph=True)
x.grad == 2 * x

Tensor(shape=[4], dtype=bool, place=Place(gpu:0), stop_gradient=True, [True, True, True, True])

复杂工作流自动求导

def f(a):
    b = a * 2
    while b.norm() < 1000:
        b = b * 2
    if b.sum() > 0:
        c = b
    else:
        c = 100 * b
    return c  

a = paddle.randn(shape=((10,10)),dtype='float32')
a.stop_gradient = False
d = f(a)
paddle.autograd.backward(d, retain_graph=True)
  
a.grad == d / a

Tensor(shape=[10, 10], dtype=bool, place=Place(gpu:0), stop_gradient=True,
[[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True],
[True, True, True, True, True, True, True, True, True, True]])