This code for Gradient Descent algorithm for one vector x and I attached the image of plots of the algorithm after run

I want to update the same code for two vectors (two Dimensions) with plots them """""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""

import numpy as np from matplotlib import pyplot as plt class GradientDescent: def __init__(self, function, gradient, initial_solution, learning_rate=0.1, max_iter=100, tolerance=0.0000001): self.function = function self.gradient= gradient self.solution = initial_solution self.learning_rate = learning_rate self.max_iter = max_iter self.tolerance = tolerance def run(self): t = 0 while t

def gradient1(x,y): return 2*x

bounds = [-3,3]

plt.figure()

x = np.linspace(bounds[0], bounds[1],100) plt.plot(x,fun1(x))

random_solution = np.random.uniform(bounds[0], bounds[1])

gd = GradientDescent(fun1, gradient1, random_solution)

best_solution,best_value = gd.run()