torch code

torch_test.py

# coding: utf-8
import torch

w_true = torch.Tensor([1, 2, 3])

X = torch.cat([torch.ones(100, 1), torch.randn(100, 2)], 1)
Y = torch.mv(X, w_true) + torch.randn(100) * 0.5
w = torch.randn(3, requires_grad=True)

lr = 0.1    


for epoc in range(100):
	w.grad = None
	y_pred = torch.mv(X, w)
	loss = torch.mean((Y - y_pred)**2)
	loss.backward()
	w.data = w.data - lr * w.grad.data
	if epoc%10==0:
		print('step: {}, loss = {:.4f}'.format(epoc,loss.item()))