查看“作业1答案，待完善”的源代码

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import numpy as np
import os
from PIL import Image

def loss(y_pred,y_true):#y_pred shape->vector
    return sum((y_pred - y_true)**2)

def df(x):
    pass

def random_init(shape):
    return np.random.rand(shape)

def load_dataset(path):
    ab = os.listdir(path)
    ba = [i for i in ab if 'jpg' in i]
    x = []
    y = []
    for i in range(len(ba)):
        xi = Image.open(os.path.join(path,ba[i])).convert('L')
        xii = np.array(xi)
        xii = xii[:200,:200]
        yi = sum(sum(xii))
        x.append(xii)
        y.append(yi)
    x = np.array(x)
    y = np.array(y)
    return x,y
      
def bp(w,b,c,yi,ai,lr):
    for i in range(len(w)):
        w[i] = w[i] - lr * 2*(yi-c)*ai[i]
    b = b - lr * 2*(yi-c)*1
    return w,b

def forword(x,w,b):
    return sum(x*w)+b

def train(x,y,w,b,lr):
    
    for i in range(x.shape[0]):
        c = forword(x[i],w,b)
        los = loss(c,y[i])
        w,b = bp(w,b,c,y[i],x[i],lr)
        print('Loss:\t',los)
    return w,b
    

def main():
    path = r'C:\Users\mtju\Desktop'
    lr = 0.01
    a , y= load_dataset(path)
    x = a.reshape(a.shape[0],-1)
    w = random_init(x.shape[1])
    b = random_init(1)
    for i in range(10):
        w1,b1 = train(x,y,w,b,lr)
    return w1,b1

# a = random_init(10)
# b = np.random.rand(10,20)
# b = b.reshape(5,5,-1)
# c = loss(a,b)
w , b = main()