import torch
print(torch.__version__)
import numpy as np
import matplotlib.pyplot as plt
x_data = [1, 2, 3]
y_data = [2, 4, 6]
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(0,4.1,0.1):
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)
len(w_list)
len(mse_list)
plt.plot(w_list,mse_list)