[人工智能]刘老师《PyTorch深度学习实践》完结合集（二）线性模型代码

原视频链接：《PyTorch深度学习实践》完结合集_哔哩哔哩_bilibili

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)**2

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)
outfile = open("datafile.txt",'w')
for i in range(len(w_list)):
    outfile.write(str(w_list[i]) + " ")
outfile.write("\n")
for i in range(len(mse_list)):
    outfile.write(str(mse_list[i]) + " ")
outfile.close()
plt.plot(w_list, mse_list)
plt.xlabel('w')
plt.ylabel('loss')
plt.show()

运行结果图：

代码只用于学习使用，无任何商业意图。