{"action":"created","issue":{"url":"https://api.github.com/repos/flyyufelix/DenseNet-Keras/issues/5","repository_url":"https://api.github.com/repos/flyyufelix/DenseNet-Keras","labels_url":"https://api.github.com/repos/flyyufelix/DenseNet-Keras/issues/5/labels{/name}","comments_url":"https://api.github.com/repos/flyyufelix/DenseNet-Keras/issues/5/comments","events_url":"https://api.github.com/repos/flyyufelix/DenseNet-Keras/issues/5/events","html_url":"https://github.com/flyyufelix/DenseNet-Keras/issues/5","id":240795688,"number":5,"title":"Scale layer vs BatchNormalization in Keras v2","user":{"login":"vfdev-5","id":2459423,"avatar_url":"https://avatars0.githubusercontent.com/u/2459423?v=4","gravatar_id":"","url":"https://api.github.com/users/vfdev-5","html_url":"https://github.com/vfdev-5","followers_url":"https://api.github.com/users/vfdev-5/followers","following_url":"https://api.github.com/users/vfdev-5/following{/other_user}","gists_url":"https://api.github.com/users/vfdev-5/gists{/gist_id}","starred_url":"https://api.github.com/users/vfdev-5/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vfdev-5/subscriptions","organizations_url":"https://api.github.com/users/vfdev-5/orgs","repos_url":"https://api.github.com/users/vfdev-5/repos","events_url":"https://api.github.com/users/vfdev-5/events{/privacy}","received_events_url":"https://api.github.com/users/vfdev-5/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2017-07-05T22:37:26Z","updated_at":"2017-07-21T04:02:40Z","closed_at":null,"body":"Hi,\r\n\r\nAt first, thanks for this repo with DenseNet for Keras. As I understand you ported the architecture and weights from Caffe. I've just a question on actual purpose of your custom layer Scale after BatchNormalization in Keras v2 in the sense don't they perform the same work ?\r\n\r\n "},"comment":{"url":"https://api.github.com/repos/flyyufelix/DenseNet-Keras/issues/comments/316896595","html_url":"https://github.com/flyyufelix/DenseNet-Keras/issues/5#issuecomment-316896595","issue_url":"https://api.github.com/repos/flyyufelix/DenseNet-Keras/issues/5","id":316896595,"user":{"login":"flyyufelix","id":640082,"avatar_url":"https://avatars1.githubusercontent.com/u/640082?v=4","gravatar_id":"","url":"https://api.github.com/users/flyyufelix","html_url":"https://github.com/flyyufelix","followers_url":"https://api.github.com/users/flyyufelix/followers","following_url":"https://api.github.com/users/flyyufelix/following{/other_user}","gists_url":"https://api.github.com/users/flyyufelix/gists{/gist_id}","starred_url":"https://api.github.com/users/flyyufelix/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/flyyufelix/subscriptions","organizations_url":"https://api.github.com/users/flyyufelix/orgs","repos_url":"https://api.github.com/users/flyyufelix/repos","events_url":"https://api.github.com/users/flyyufelix/events{/privacy}","received_events_url":"https://api.github.com/users/flyyufelix/received_events","type":"User","site_admin":false},"created_at":"2017-07-21T04:02:40Z","updated_at":"2017-07-21T04:02:40Z","body":"Thanks for your detailed elaboration. Yes, I think your suggested method of directly copying the beta and gamma parameter from Caffe's scale layer directly to Keras' BatchNorm layer is completely valid. It just happened that I used a Caffe-to-Keras weight converter that defines a separate Scale layer to handle the scaling parameters. Both methods work.   "}}
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