我该如何处理多处理？

Question

I try to tune the learning rate parameter in XGBoost by using this part of program:

model = XGBClassifier()
learning_rate = [0.0001, 0.001, 0.01, 0.1, 0.2, 0.3]
param_grid = dict(learning_rate=learning_rate)
kfold = StratifiedKFold(n_splits=10, shuffle=True, random_state=7)
grid_search = GridSearchCV(model, param_grid, scoring="neg_log_loss", n_jobs=-1, cv=kfold)
grid_result = grid_search.fit(X, label_encoded_y)

but an error occurring in that line GridSearchCV: ImportError: [joblib] Attempting to do parallel computing without protecting your import on a system that does not support forking. To use parallel-computing in a script, you must protect your main loop using 'if name == ' main '.

but when I change the value of n_jobs=-1 to n_jobs=1 the error goes out but I want it to run using all cores. please, how I can overcome this error?

Answer 1

将你的主循环（连同任何额外的必要代码）放在一个名为 main() 的函数中，并在你的脚本末尾放置if __name__ == '__main__': main()这样你就可以防止循环在以下情况下意外启动您将脚本内容导入其他程序。