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pytorch學習筆記(一):線性模型

y=x*w

loss= (y_pred-y)^2

通過窮舉法來窮舉w,繪圖可以檢視到使Loss最小的w為2

(該方法提前知道w在0-4.1之間)

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)
plt.plot(w_list, mse_list)
plt.ylabel('Loss')
plt.xlabel('w')
plt.show()           

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pytorch學習筆記(一):線性模型