12345678910111213141516171819202122232425262728293031 |
- import torch
- from torch.autograd import Variable
- # 变量
- x = Variable(torch.ones(2, 2), requires_grad=True)
- print(x)
- y = x + 2
- print(y)
- z = y * y * 3
- out = z.mean()
- print(z)
- print(out)
- # 梯度
- out.backward()
- print(x.grad)
- a = torch.randn(3)
- a = Variable(a, requires_grad=True)
- b = a * 2
- while b.data.norm() < 1000:
- b = b * 2
- print(b)
- gradients = torch.FloatTensor([0.1, 1.0, 0.0001])
- b.backward(gradients)
- print(a.grad)
|