如何在python中制作混淆矩阵来检验卷积神经网络模型？

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import confusion_matrix

# 假设测试数据为y_true，模型预测结果为y_pred
y_true = [0, 1, 2, 0, 1, 2, 0, 1, 2]
y_pred = [0, 1, 1, 0, 2, 1, 0, 1, 2]

# 使用sklearn库中的confusion_matrix函数计算混淆矩阵
cm = confusion_matrix(y_true, y_pred)

# 使用seaborn和matplotlib库绘制混淆矩阵的热力图
plt.figure(figsize=(8, 6))
sns.heatmap(cm, annot=True, cmap="Blues", fmt="d", xticklabels=["Class 0", "Class 1", "Class 2"], yticklabels=["Class 0", "Class 1", "Class 2"])
plt.xlabel("Predicted")
plt.ylabel("True")
plt.title("Confusion Matrix")
plt.show()