{"action":"created","issue":{"url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/issues/99","repository_url":"https://api.github.com/repos/awslabs/keras-apache-mxnet","labels_url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/issues/99/labels{/name}","comments_url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/issues/99/comments","events_url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/issues/99/events","html_url":"https://github.com/awslabs/keras-apache-mxnet/issues/99","id":324446337,"node_id":"MDU6SXNzdWUzMjQ0NDYzMzc=","number":99,"title":"Keras-MXNet RNN CPU performance is slower","user":{"login":"sandeep-krishnamurthy","id":3403674,"node_id":"MDQ6VXNlcjM0MDM2NzQ=","avatar_url":"https://avatars1.githubusercontent.com/u/3403674?v=4","gravatar_id":"","url":"https://api.github.com/users/sandeep-krishnamurthy","html_url":"https://github.com/sandeep-krishnamurthy","followers_url":"https://api.github.com/users/sandeep-krishnamurthy/followers","following_url":"https://api.github.com/users/sandeep-krishnamurthy/following{/other_user}","gists_url":"https://api.github.com/users/sandeep-krishnamurthy/gists{/gist_id}","starred_url":"https://api.github.com/users/sandeep-krishnamurthy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/sandeep-krishnamurthy/subscriptions","organizations_url":"https://api.github.com/users/sandeep-krishnamurthy/orgs","repos_url":"https://api.github.com/users/sandeep-krishnamurthy/repos","events_url":"https://api.github.com/users/sandeep-krishnamurthy/events{/privacy}","received_events_url":"https://api.github.com/users/sandeep-krishnamurthy/received_events","type":"User","site_admin":false},"labels":[{"id":736929999,"node_id":"MDU6TGFiZWw3MzY5Mjk5OTk=","url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/labels/help%20wanted","name":"help wanted","color":"33aa3f","default":true},{"id":931911559,"node_id":"MDU6TGFiZWw5MzE5MTE1NTk=","url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/labels/performance","name":"performance","color":"0052cc","default":false}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-05-18T15:02:56Z","updated_at":"2018-10-10T16:56:49Z","closed_at":null,"author_association":"COLLABORATOR","body":"Keras-MXNet is slower on CPU.\r\nSee early benchmark results here - https://github.com/awslabs/keras-apache-mxnet/blob/master/benchmark/benchmark_result/RNN_result.md\r\n\r\nThis issue is likely due to:\r\n1. MXNet broadcast_add operator being slower on CPU - https://github.com/apache/incubator-mxnet/issues/8219\r\n2. MXNet dot operator being slower on CPU - https://github.com/apache/incubator-mxnet/issues/10881\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/issues/comments/428649570","html_url":"https://github.com/awslabs/keras-apache-mxnet/issues/99#issuecomment-428649570","issue_url":"https://api.github.com/repos/awslabs/keras-apache-mxnet/issues/99","id":428649570,"node_id":"MDEyOklzc3VlQ29tbWVudDQyODY0OTU3MA==","user":{"login":"sandeep-krishnamurthy","id":3403674,"node_id":"MDQ6VXNlcjM0MDM2NzQ=","avatar_url":"https://avatars1.githubusercontent.com/u/3403674?v=4","gravatar_id":"","url":"https://api.github.com/users/sandeep-krishnamurthy","html_url":"https://github.com/sandeep-krishnamurthy","followers_url":"https://api.github.com/users/sandeep-krishnamurthy/followers","following_url":"https://api.github.com/users/sandeep-krishnamurthy/following{/other_user}","gists_url":"https://api.github.com/users/sandeep-krishnamurthy/gists{/gist_id}","starred_url":"https://api.github.com/users/sandeep-krishnamurthy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/sandeep-krishnamurthy/subscriptions","organizations_url":"https://api.github.com/users/sandeep-krishnamurthy/orgs","repos_url":"https://api.github.com/users/sandeep-krishnamurthy/repos","events_url":"https://api.github.com/users/sandeep-krishnamurthy/events{/privacy}","received_events_url":"https://api.github.com/users/sandeep-krishnamurthy/received_events","type":"User","site_admin":false},"created_at":"2018-10-10T16:56:49Z","updated_at":"2018-10-10T16:56:49Z","author_association":"COLLABORATOR","body":"@pengzhao-intel - Thank you.\r\nUnfortunately, Keras engine has an implementation of these Layers using the low-level operators (broadcast_add, div, mul, split, zeros_like, dot etc...) from backends. For example, see here the rnn operator implementation in MXNet backend - https://github.com/awslabs/keras-apache-mxnet/blob/master/keras/backend/mxnet_backend.py#L2640 It mostly has information to use low-level operators to achieve the functionality.\r\n\r\nUsing high-level constructs like vRNN/LSTM/GRU from MXNet requires us to break Keras engine implementation and short circuit it to MXNet high-level operators.\r\n\r\n@roywei @kalyc "}}
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