import numpy as np
from numpy.random import normal, rand, randint

eps = lambda x: y(x-0.01) if x==0 else 0
y = lambda x: 1/(x + eps(x))

X_train = rand(1000)
y_train = rand(1000)

k = rand(100)


while True:
    for i in range(100):
        idx = randint(0,100,100)
        X = X_train[idx]
        yt = y_train[idx]
        f = k * X
        err = yt - f
        k += err
        print(np.sum(err**2))