Skip to content
New issue

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

关于mixture2clean的keras和pytorch不同实现 #41

Open
only-yipie opened this issue Jul 4, 2019 · 4 comments
Open

关于mixture2clean的keras和pytorch不同实现 #41

only-yipie opened this issue Jul 4, 2019 · 4 comments

Comments

@only-yipie
Copy link

您好,我在运行代码的时候遇到这样一个问题。将keras版本的mixture2clean_dnn中的DNN模型直接替换为pytorch版本的DNN,其他配置一样,然后pytorch-DNN的效果要差很多。
请问这大概是什么原因呢?
期待您的回复,感谢!

@qiuqiangkong
Copy link
Collaborator

qiuqiangkong commented Jul 4, 2019 via email

@only-yipie
Copy link
Author

@qiuqiangkong 您好,不好意思,我想您可能误会了我的意思,我不是说pytorch版本的mixture2clean_dnn效果要差一些,而是我在keras版本的mixture2clean_dnn中,DNN模型使用pytorch实现效果要差一些,也就是说模型的输入是一样的,都是使用keras版本的mixture2clean_dnn中的代码,只有模型实现的框架不一样,然后效果差很多。我现在还没找到原因。
期待您的解答,感谢!

@bailiangze
Copy link

一样的输入,我改成tensorflow 训练,一样的loss函数,发现差别很大

@qiuqiangkong
Copy link
Collaborator

qiuqiangkong commented Jul 8, 2019 via email

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants