{"action":"opened","issue":{"url":"https://api.github.com/repos/caffe2/caffe2/issues/1906","repository_url":"https://api.github.com/repos/caffe2/caffe2","labels_url":"https://api.github.com/repos/caffe2/caffe2/issues/1906/labels{/name}","comments_url":"https://api.github.com/repos/caffe2/caffe2/issues/1906/comments","events_url":"https://api.github.com/repos/caffe2/caffe2/issues/1906/events","html_url":"https://github.com/caffe2/caffe2/issues/1906","id":295135194,"number":1906,"title":"Using previous output as input? (RNN?)","user":{"login":"Heightened","id":1674507,"avatar_url":"https://avatars0.githubusercontent.com/u/1674507?v=4","gravatar_id":"","url":"https://api.github.com/users/Heightened","html_url":"https://github.com/Heightened","followers_url":"https://api.github.com/users/Heightened/followers","following_url":"https://api.github.com/users/Heightened/following{/other_user}","gists_url":"https://api.github.com/users/Heightened/gists{/gist_id}","starred_url":"https://api.github.com/users/Heightened/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Heightened/subscriptions","organizations_url":"https://api.github.com/users/Heightened/orgs","repos_url":"https://api.github.com/users/Heightened/repos","events_url":"https://api.github.com/users/Heightened/events{/privacy}","received_events_url":"https://api.github.com/users/Heightened/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-02-07T13:21:21Z","updated_at":"2018-02-07T13:21:21Z","closed_at":null,"author_association":"NONE","body":"I've got a convolutional neural network which is trying to figure out the state of some persistent model based on the input image.\r\nWhen using video input, I would like to use the previous prediction of the network as input in the next iteration.\r\nNow I can manually fetch the output and feed it back into the network but would like to avoid moving the data between GPU and CPU.\r\nWhat would be a more straight-forward way to achieve the desired effect?\r\n\r\nI suspect there must be some RNN related operators which may be useful but I'm unfamiliar with them at the moment.\r\nAre there any useful examples?\r\n\r\nThanks in advance,\r\nCarl"}}
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