{"action":"created","issue":{"url":"https://api.github.com/repos/PaddlePaddle/Paddle/issues/14278","repository_url":"https://api.github.com/repos/PaddlePaddle/Paddle","labels_url":"https://api.github.com/repos/PaddlePaddle/Paddle/issues/14278/labels{/name}","comments_url":"https://api.github.com/repos/PaddlePaddle/Paddle/issues/14278/comments","events_url":"https://api.github.com/repos/PaddlePaddle/Paddle/issues/14278/events","html_url":"https://github.com/PaddlePaddle/Paddle/pull/14278","id":377807545,"node_id":"MDExOlB1bGxSZXF1ZXN0MjI4NjYxMDk0","number":14278,"title":"add mkldnn prop_kind phase for inference-only case to pooling and activations","user":{"login":"sfraczek","id":17185347,"node_id":"MDQ6VXNlcjE3MTg1MzQ3","avatar_url":"https://avatars1.githubusercontent.com/u/17185347?v=4","gravatar_id":"","url":"https://api.github.com/users/sfraczek","html_url":"https://github.com/sfraczek","followers_url":"https://api.github.com/users/sfraczek/followers","following_url":"https://api.github.com/users/sfraczek/following{/other_user}","gists_url":"https://api.github.com/users/sfraczek/gists{/gist_id}","starred_url":"https://api.github.com/users/sfraczek/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/sfraczek/subscriptions","organizations_url":"https://api.github.com/users/sfraczek/orgs","repos_url":"https://api.github.com/users/sfraczek/repos","events_url":"https://api.github.com/users/sfraczek/events{/privacy}","received_events_url":"https://api.github.com/users/sfraczek/received_events","type":"User","site_admin":false},"labels":[{"id":831909412,"node_id":"MDU6TGFiZWw4MzE5MDk0MTI=","url":"https://api.github.com/repos/PaddlePaddle/Paddle/labels/Intel","name":"Intel","color":"53a9d1","default":false}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":4,"created_at":"2018-11-06T11:35:47Z","updated_at":"2018-11-13T11:42:40Z","closed_at":null,"author_association":"CONTRIBUTOR","pull_request":{"url":"https://api.github.com/repos/PaddlePaddle/Paddle/pulls/14278","html_url":"https://github.com/PaddlePaddle/Paddle/pull/14278","diff_url":"https://github.com/PaddlePaddle/Paddle/pull/14278.diff","patch_url":"https://github.com/PaddlePaddle/Paddle/pull/14278.patch"},"body":"This PR adds is_test flag to two operators: pooling and activations and fixes convolution to use it also.\r\nIt adds a capi pass that sets is_test to true.\r\nIt adds a test for that capi pass.\r\nIt adds a transpiler pass with the same functionality."},"comment":{"url":"https://api.github.com/repos/PaddlePaddle/Paddle/issues/comments/438237136","html_url":"https://github.com/PaddlePaddle/Paddle/pull/14278#issuecomment-438237136","issue_url":"https://api.github.com/repos/PaddlePaddle/Paddle/issues/14278","id":438237136,"node_id":"MDEyOklzc3VlQ29tbWVudDQzODIzNzEzNg==","user":{"login":"sfraczek","id":17185347,"node_id":"MDQ6VXNlcjE3MTg1MzQ3","avatar_url":"https://avatars1.githubusercontent.com/u/17185347?v=4","gravatar_id":"","url":"https://api.github.com/users/sfraczek","html_url":"https://github.com/sfraczek","followers_url":"https://api.github.com/users/sfraczek/followers","following_url":"https://api.github.com/users/sfraczek/following{/other_user}","gists_url":"https://api.github.com/users/sfraczek/gists{/gist_id}","starred_url":"https://api.github.com/users/sfraczek/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/sfraczek/subscriptions","organizations_url":"https://api.github.com/users/sfraczek/orgs","repos_url":"https://api.github.com/users/sfraczek/repos","events_url":"https://api.github.com/users/sfraczek/events{/privacy}","received_events_url":"https://api.github.com/users/sfraczek/received_events","type":"User","site_admin":false},"created_at":"2018-11-13T11:42:40Z","updated_at":"2018-11-13T11:42:40Z","author_association":"CONTRIBUTOR","body":"@tpatejko , regarding reorders, I've run resnet50 and the only reorder happens before softmax at the end. Is this how it should be?\r\n```\r\nmkldnn_verbose,exec,convolution,jit:avx512_common,forward_inference,fsrc:nChw16c fwei:OIhw16i16o fbia:x fdst:nChw16c,alg:convolution_direct,mb32_g1ic512oc512_ih7oh7kh3sh1dh0ph1_iw7ow7kw3sw1dw0pw1,39.439\r\nmkldnn_verbose,exec,convolution,jit_1x1:avx512_common,forward_inference,fsrc:nChw16c fwei:OIhw16i16o fbia:x fdst:nChw16c,alg:convolution_direct,mb32_g1ic512oc2048_ih7oh7kh1sh1dh0ph0_iw7ow7kw1sw1dw0pw0,22.2341\r\nmkldnn_verbose,exec,pooling,jit:avx512_common,forward_inference,fdata:nChw16c fws:undef,alg:pooling_avg_exclude_padding,mb32ic2048_ih7oh1kh7sh1ph0_iw7ow1kw7sw1pw0,1.88989\r\nmkldnn_verbose,create,reorder,jit:uni,undef,in:f32_nChw16c out:f32_nchw,num:1,32x2048x1x1,0.129883\r\nmkldnn_verbose,exec,reorder,jit:uni,undef,in:f32_nChw16c out:f32_nchw,num:1,32x2048x1x1,0.0480957\r\nmkldnn_verbose,exec,softmax,ref:any,forward_inference,fdata:nc fdiff:undef,,mb32ic1000ih2075383169iw-32765,0.321045\r\nIteration: 3, accuracy: 0.812500, latency: 1.67097 s, fps: 19.150597\r\n```"}}
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