We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
谢谢作者提供这么好的教程,有几个问题想要请教 1、在lstm.py代码,test函数中,调用backward函数,传入的第二个参数d是目标输出,最后是传给了delta_h,不知道为什么?delta_h命名的意思不应该是用目标输出d减去forward输入的h吗? 2、不太明白gradient_check()函数用意,因为教程未给出具体说明,所以不太明白这段代码的意思。个人理解,检查梯度是为了看看梯度计算情况,看有没有出现梯度爆炸或梯度消失的现象吗? 3、lstm代码中的测试例子有更新参数的函数update(),但是测试用例没有调用,lstm有个重要用途是预测,如果作者能给出一个较为完善的测试用例,能够打印出经过BPTT计算后参数更新的预测值就好啦
The text was updated successfully, but these errors were encountered:
No branches or pull requests
谢谢作者提供这么好的教程,有几个问题想要请教
1、在lstm.py代码,test函数中,调用backward函数,传入的第二个参数d是目标输出,最后是传给了delta_h,不知道为什么?delta_h命名的意思不应该是用目标输出d减去forward输入的h吗?
2、不太明白gradient_check()函数用意,因为教程未给出具体说明,所以不太明白这段代码的意思。个人理解,检查梯度是为了看看梯度计算情况,看有没有出现梯度爆炸或梯度消失的现象吗?
3、lstm代码中的测试例子有更新参数的函数update(),但是测试用例没有调用,lstm有个重要用途是预测,如果作者能给出一个较为完善的测试用例,能够打印出经过BPTT计算后参数更新的预测值就好啦
The text was updated successfully, but these errors were encountered: