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

Are you sure about the value of "batch_norm_decay" is 0.1 ? #13

Open
dreambear1234 opened this issue Nov 14, 2017 · 3 comments
Open

Are you sure about the value of "batch_norm_decay" is 0.1 ? #13

dreambear1234 opened this issue Nov 14, 2017 · 3 comments

Comments

@dreambear1234
Copy link

According the official example of tensorflow,
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/slim/python/slim/nets/resnet_utils.py
in line 226, the decay value is 0.997;
I'm using a revised ENet in tensorflow, but I can't get the iou value as well as Torch, about 4 less than Torch, Appreciate for your reply!

@kwotsin
Copy link
Owner

kwotsin commented Nov 16, 2017

The value is different as it was based upon the original torch implementation of the ENet authors (see references in README).

@dreambear1234
Copy link
Author

@kwotsin ,Are you explain me that the hyper parameter "momentum"=0.9?
maybe it is a optimizer for training process(accelerate convergence) in back propagation;
But the decay of BN is used to get a statistics value of mean and var in forward propagation(moving mean, moving var).
they are two separate value(momentum, bn_decay).
Is it correct? Maybe I'm confused.
Thank you for your reply

@kwotsin
Copy link
Owner

kwotsin commented Dec 1, 2017

@dreambear1234 Unfortunately I've not yet have the time to test this out - have you experimented with the value you chosen and see if it results in a better performance? In your revised ENet, what did you change?

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