梯度下降可视化

def solve():
    import numpy as np
    import matplotlib.pyplot as plt
    def loss(____):
        return x**____ - ____*x + ____
    def gradient(____):
        return ____*x - ____
    x = ____
    lr = ____
    x_history = [x]
    for _ in range(____):
        x = x - lr * gradient(____)
        x_history.append(____)
    x_range = np.linspace(____)
    plt.figure(figsize=(____, ____))
    plt.plot(x_range, loss(____), '____', label='____')
    plt.scatter(x_history, [loss(____) for x in x_history], color='____', s=____, zorder=____)
    plt.plot(x_history, [loss(____) for x in x_history], '____', alpha=____)
    plt.xlabel(____)
    plt.ylabel(____)
    plt.title(____)
    plt.legend()
    plt.grid(____)
    plt.show()