{"action":"created","issue":{"url":"https://api.github.com/repos/tadax/glcic/issues/6","repository_url":"https://api.github.com/repos/tadax/glcic","labels_url":"https://api.github.com/repos/tadax/glcic/issues/6/labels{/name}","comments_url":"https://api.github.com/repos/tadax/glcic/issues/6/comments","events_url":"https://api.github.com/repos/tadax/glcic/issues/6/events","html_url":"https://github.com/tadax/glcic/issues/6","id":293830227,"number":6,"title":"Batch normalization module","user":{"login":"JingleiSHI","id":18230898,"avatar_url":"https://avatars0.githubusercontent.com/u/18230898?v=4","gravatar_id":"","url":"https://api.github.com/users/JingleiSHI","html_url":"https://github.com/JingleiSHI","followers_url":"https://api.github.com/users/JingleiSHI/followers","following_url":"https://api.github.com/users/JingleiSHI/following{/other_user}","gists_url":"https://api.github.com/users/JingleiSHI/gists{/gist_id}","starred_url":"https://api.github.com/users/JingleiSHI/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/JingleiSHI/subscriptions","organizations_url":"https://api.github.com/users/JingleiSHI/orgs","repos_url":"https://api.github.com/users/JingleiSHI/repos","events_url":"https://api.github.com/users/JingleiSHI/events{/privacy}","received_events_url":"https://api.github.com/users/JingleiSHI/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-02-02T09:50:13Z","updated_at":"2018-02-04T08:11:27Z","closed_at":null,"author_association":"NONE","body":"Hello, \r\nThank you very much for your work, that really helps me a lot. I have noticed that the batch normalization function didn't work very well in my models: with batch normalization it will be trained slower and converge at the wrong point. But we I substitute the 'gamma' and 'beta's  <truncated_normal_initializer> with <zeros/ones_initializer>, your batch normalization module works very well and converges at the right point. As I am a tensorflow beginner, I don't understand well the differences it brings.  Could you please explain to me why you choose these initializers and why they bring such a difference? Thank you very much!\r\n\r\nBest wishes,\r\nJ. SHI"},"comment":{"url":"https://api.github.com/repos/tadax/glcic/issues/comments/362888989","html_url":"https://github.com/tadax/glcic/issues/6#issuecomment-362888989","issue_url":"https://api.github.com/repos/tadax/glcic/issues/6","id":362888989,"user":{"login":"tadax","id":12031802,"avatar_url":"https://avatars2.githubusercontent.com/u/12031802?v=4","gravatar_id":"","url":"https://api.github.com/users/tadax","html_url":"https://github.com/tadax","followers_url":"https://api.github.com/users/tadax/followers","following_url":"https://api.github.com/users/tadax/following{/other_user}","gists_url":"https://api.github.com/users/tadax/gists{/gist_id}","starred_url":"https://api.github.com/users/tadax/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tadax/subscriptions","organizations_url":"https://api.github.com/users/tadax/orgs","repos_url":"https://api.github.com/users/tadax/repos","events_url":"https://api.github.com/users/tadax/events{/privacy}","received_events_url":"https://api.github.com/users/tadax/received_events","type":"User","site_admin":false},"created_at":"2018-02-04T08:11:27Z","updated_at":"2018-02-04T08:11:27Z","author_association":"OWNER","body":"@JingleiSHI Actually, I have no particular reason for using truncated normal distribution. I not sure why your model doesn't wok (zeros/ones initializer are used in [tf.layers.batch_normalization](https://www.tensorflow.org/api_docs/python/tf/layers/batch_normalization))."}}
{"actor":{"display_login":"tadax"}}