{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/caffe/issues/512","repository_url":"https://api.github.com/repos/NVIDIA/caffe","labels_url":"https://api.github.com/repos/NVIDIA/caffe/issues/512/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/caffe/issues/512/comments","events_url":"https://api.github.com/repos/NVIDIA/caffe/issues/512/events","html_url":"https://github.com/NVIDIA/caffe/issues/512","id":325559546,"number":512,"title":"Difference with BVLC caffe","user":{"login":"mathmanu","id":2990503,"avatar_url":"https://avatars0.githubusercontent.com/u/2990503?v=4","gravatar_id":"","url":"https://api.github.com/users/mathmanu","html_url":"https://github.com/mathmanu","followers_url":"https://api.github.com/users/mathmanu/followers","following_url":"https://api.github.com/users/mathmanu/following{/other_user}","gists_url":"https://api.github.com/users/mathmanu/gists{/gist_id}","starred_url":"https://api.github.com/users/mathmanu/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mathmanu/subscriptions","organizations_url":"https://api.github.com/users/mathmanu/orgs","repos_url":"https://api.github.com/users/mathmanu/repos","events_url":"https://api.github.com/users/mathmanu/events{/privacy}","received_events_url":"https://api.github.com/users/mathmanu/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-05-23T05:59:47Z","updated_at":"2018-05-26T21:35:51Z","closed_at":null,"author_association":"NONE","body":"The following model works (gives good accuracy in BVLC caffe)\r\nhttps://github.com/cvjena/cnn-models/tree/master/ResNet_preact/ResNet10_cvgj\r\n\r\nHowever, it doesn't work on NVIDIA/caffe (top-1 accuracy is zero)\r\n\r\nIs blobs_[2] based scaling that is part of BVLC caffe implemented in NVIDIA/caffe? \r\nhttps://github.com/BVLC/caffe/blob/master/src/caffe/layers/batch_norm_layer.cu#L24\r\nCouldn't find it in NVIDIA/caffe.\r\n\r\nI suspect that this may not be the only reason for this mismatch.\r\n\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/NVIDIA/caffe/issues/comments/392289572","html_url":"https://github.com/NVIDIA/caffe/issues/512#issuecomment-392289572","issue_url":"https://api.github.com/repos/NVIDIA/caffe/issues/512","id":392289572,"user":{"login":"whria78","id":23740800,"avatar_url":"https://avatars0.githubusercontent.com/u/23740800?v=4","gravatar_id":"","url":"https://api.github.com/users/whria78","html_url":"https://github.com/whria78","followers_url":"https://api.github.com/users/whria78/followers","following_url":"https://api.github.com/users/whria78/following{/other_user}","gists_url":"https://api.github.com/users/whria78/gists{/gist_id}","starred_url":"https://api.github.com/users/whria78/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/whria78/subscriptions","organizations_url":"https://api.github.com/users/whria78/orgs","repos_url":"https://api.github.com/users/whria78/repos","events_url":"https://api.github.com/users/whria78/events{/privacy}","received_events_url":"https://api.github.com/users/whria78/received_events","type":"User","site_admin":false},"created_at":"2018-05-26T21:35:51Z","updated_at":"2018-05-26T21:35:51Z","author_association":"NONE","body":"I also fail to finetune ResNet-50. (CUDA 9,1, cuDNN 7)."}}
{"actor":{"display_login":"whria78"}}