にほんお - 経済統計練習帳

import numpy as np
import chainer
from chainer import cuda, Function, gradient_check, report, training, utils, Variable
from chainer import datasets, iterators, optimizers, serializers
from chainer import Link, Chain, ChainList
import chainer.functions as F
import chainer.links as L
from chainer.training import extensions
 
x_data = np.array([5], dtype=np.float32)
x = Variable(x_data)
y = x**2 - 2 * x + 1
z=y.data
y.backward()
k=x.grad
print(k)