payload: {"action":"created","issue":{"url":"https://api.github.com/repos/shamangary/FSA-Net/issues/8","repository_url":"https://api.github.com/repos/shamangary/FSA-Net","labels_url":"https://api.github.com/repos/shamangary/FSA-Net/issues/8/labels{/name}","comments_url":"https://api.github.com/repos/shamangary/FSA-Net/issues/8/comments","events_url":"https://api.github.com/repos/shamangary/FSA-Net/issues/8/events","html_url":"https://github.com/shamangary/FSA-Net/issues/8","id":451308374,"node_id":"MDU6SXNzdWU0NTEzMDgzNzQ=","number":8,"title":"The code's Normalization different with paper?","user":{"login":"TemiLee","id":8938339,"node_id":"MDQ6VXNlcjg5MzgzMzk=","avatar_url":"https://avatars2.githubusercontent.com/u/8938339?v=4","gravatar_id":"","url":"https://api.github.com/users/TemiLee","html_url":"https://github.com/TemiLee","followers_url":"https://api.github.com/users/TemiLee/followers","following_url":"https://api.github.com/users/TemiLee/following{/other_user}","gists_url":"https://api.github.com/users/TemiLee/gists{/gist_id}","starred_url":"https://api.github.com/users/TemiLee/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/TemiLee/subscriptions","organizations_url":"https://api.github.com/users/TemiLee/orgs","repos_url":"https://api.github.com/users/TemiLee/repos","events_url":"https://api.github.com/users/TemiLee/events{/privacy}","received_events_url":"https://api.github.com/users/TemiLee/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2019-06-03T06:12:07Z","updated_at":"2019-06-03T07:20:28Z","closed_at":"2019-06-03T07:18:31Z","author_association":"NONE","body":"In your code the normalization is use the K.sum :\r\n```\r\n# Very important!!! Without this training won't converge.\r\n# norm_S = Lambda(lambda x: K.tile(K.sum(x,axis=-1,keepdims=True),(1,1,64)))(S_matrix)\r\nnorm_S_s1 = Lambda(lambda x: K.tile(K.sum(x,axis=-1,keepdims=True),(1,1,64)))(S_matrix_s1)\r\nnorm_S_s2 = Lambda(lambda x: K.tile(K.sum(x,axis=-1,keepdims=True),(1,1,64)))(S_matrix_s2)\r\nnorm_S_s3 = Lambda(lambda x: K.tile(K.sum(x,axis=-1,keepdims=True),(1,1,64)))(S_matrix_s3)\r\n\r\n```\r\nBut in your paper section3.5:\r\n\r\n> L1 normamlization is performed for each row of Sk for more stable training\r\n\r\nwhy there have the different ? Does this include deeper considerations?"},"comment":{"url":"https://api.github.com/repos/shamangary/FSA-Net/issues/comments/498142037","html_url":"https://github.com/shamangary/FSA-Net/issues/8#issuecomment-498142037","issue_url":"https://api.github.com/repos/shamangary/FSA-Net/issues/8","id":498142037,"node_id":"MDEyOklzc3VlQ29tbWVudDQ5ODE0MjAzNw==","user":{"login":"TemiLee","id":8938339,"node_id":"MDQ6VXNlcjg5MzgzMzk=","avatar_url":"https://avatars2.githubusercontent.com/u/8938339?v=4","gravatar_id":"","url":"https://api.github.com/users/TemiLee","html_url":"https://github.com/TemiLee","followers_url":"https://api.github.com/users/TemiLee/followers","following_url":"https://api.github.com/users/TemiLee/following{/other_user}","gists_url":"https://api.github.com/users/TemiLee/gists{/gist_id}","starred_url":"https://api.github.com/users/TemiLee/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/TemiLee/subscriptions","organizations_url":"https://api.github.com/users/TemiLee/orgs","repos_url":"https://api.github.com/users/TemiLee/repos","events_url":"https://api.github.com/users/TemiLee/events{/privacy}","received_events_url":"https://api.github.com/users/TemiLee/received_events","type":"User","site_admin":false},"created_at":"2019-06-03T07:20:28Z","updated_at":"2019-06-03T07:20:28Z","author_association":"NONE","body":"@shamangary understood ， thanks"}}
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