pytorch线性模型

import numpy as np
import matplotlib.pyplot as plt
x_data = [1.0, 2.0, 3.0]
y_data = [2.0, 4.0, 6.0]

def forward (x,w) :#前向传播
  return x * w


def loss (x,y) :#损失函数
  y_pred = forward(x)
  return (y_pred - y) * (y_pred - y)

w_list =[]
mse_list =[]
for w in np.arange(0.0,4.1,0.1) :
  print('w',w)
  1_sum = 0
  for x_val, y_val in zip(x_data, y_data) :
    y_pred_val = forward(x_val,w)
    loss_val = loss(x_val, y_val)
    1_sum += loss_val
    print('\t',x_val,y_val,y_pred_val,loss_val)
    print('MSE=',1_sum/3)#mean square error 平均方差误差
    w_list.append(w)
    mse_list.append(1_sum/3)
pit.plot(w_list,mse_list)
plt.ylabel('Loss')
plt.xlabel('w')
plt.show()