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
我看您写的那个triplet loss那里,建立的模型最后一层是是一个dense,这是全连接层,为啥这里叫embedding层了?在keras里面有一个embedding的函数,但是不懂具体的实现,在tensorflow里面也有相关的,embedding_lookup的函数,想问这里为啥这里输出就是embedding了
The text was updated successfully, but these errors were encountered:
自己命名的,想让这64维的特征作为求距离的特征,和你说的函数没啥关系
Sorry, something went wrong.
No branches or pull requests
我看您写的那个triplet loss那里,建立的模型最后一层是是一个dense,这是全连接层,为啥这里叫embedding层了?在keras里面有一个embedding的函数,但是不懂具体的实现,在tensorflow里面也有相关的,embedding_lookup的函数,想问这里为啥这里输出就是embedding了
The text was updated successfully, but these errors were encountered: