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

why 10000 in your code,what's the meaning?Thanks!!! #48

Open
liuyishoua opened this issue Jun 4, 2021 · 2 comments
Open

why 10000 in your code,what's the meaning?Thanks!!! #48

liuyishoua opened this issue Jun 4, 2021 · 2 comments

Comments

@liuyishoua
Copy link

in l2 completion,you use codes like below. What is the meaning?And why you use 10000?Could you tell me some more detail?

other = tf.reduce_max((1-self.tlab)self.output - (self.tlab10000),1)

@fotinidelig
Copy link

(For anyone still interested)
I think it's just to make sure that this max values doesn't take into account the target label. 'Cause here you want to calculate the maximum logit of the predictions WITHOUT the target (a.k.a if the network is accurate enough, should correspond to the true label of the images).
Personally I'm not sure it makes any difference even if logit[tlab] = 1 and logit[label!=tlab] = 0.
Also note that tlab = [target label], real = [logit of target label] & other = [max logit between all other labels]

@liuyishoua
Copy link
Author

this help a lot,thank you

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

2 participants