import numpy as np

def func(x):

    return (x[0] + x[1] - 1)**2 + (x[0] - x[1] - 2)**2

def gradient(x):

    return np.array([4 * x[0] - 6, 4 * x[1] + 2])

def gradient_descent(initialization, step_size, iterations):

    x = initialization
    for i in range(iterations):
        x = x[0] + step_size*gradient(x)
    return x

print(gradient_descent(np.array([0, 0]), 0.1, 5))
print(gradient_descent(np.array([0, 0]), 0.1, 100))