《PyTorch深度学习实践》--2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):
    return x * w
 
def loss(x,y):
    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)
    l_sum = 0
    for x_val, y_val in zip(x_data, y_data) :
        y_pred_val = forward(x_val)
        loss_val = loss(x_val,y_val)
        l_sum += loss_val
        print('\t', x_val, y_val,y_pred_val,loss_val)
    print('MSE=',l_sum/3)
    w_list.append(w)
    mse_list.append(l_sum/3)
 
 
 
 
#画图
plt.plot(w_list, mse_list)
plt.ylabel('loss')
plt.xlabel('w')
plt.show()