{"action":"created","issue":{"url":"https://api.github.com/repos/fchollet/keras/issues/98","labels_url":"https://api.github.com/repos/fchollet/keras/issues/98/labels{/name}","comments_url":"https://api.github.com/repos/fchollet/keras/issues/98/comments","events_url":"https://api.github.com/repos/fchollet/keras/issues/98/events","html_url":"https://github.com/fchollet/keras/issues/98","id":73243556,"number":98,"title":"\"real time\" recurrent nets","user":{"login":"lemuriandezapada","id":11992601,"avatar_url":"https://avatars.githubusercontent.com/u/11992601?v=3","gravatar_id":"","url":"https://api.github.com/users/lemuriandezapada","html_url":"https://github.com/lemuriandezapada","followers_url":"https://api.github.com/users/lemuriandezapada/followers","following_url":"https://api.github.com/users/lemuriandezapada/following{/other_user}","gists_url":"https://api.github.com/users/lemuriandezapada/gists{/gist_id}","starred_url":"https://api.github.com/users/lemuriandezapada/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/lemuriandezapada/subscriptions","organizations_url":"https://api.github.com/users/lemuriandezapada/orgs","repos_url":"https://api.github.com/users/lemuriandezapada/repos","events_url":"https://api.github.com/users/lemuriandezapada/events{/privacy}","received_events_url":"https://api.github.com/users/lemuriandezapada/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":34,"created_at":"2015-05-05T08:14:05Z","updated_at":"2015-07-21T08:59:58Z","closed_at":null,"body":"Hey guys,\r\n\r\nI was wondering how are the initial internal states in a recurrent layer dealt with? So far it appears they are reset are every run. Is there any way to preserve them?\r\n\r\nI'd like to be able to feed a .predict_proba() function data one time step at a time for a time series task, as the points come in, without also feeding the entire history all over again. Is this somehow possible? Thanks"},"comment":{"url":"https://api.github.com/repos/fchollet/keras/issues/comments/123222277","html_url":"https://github.com/fchollet/keras/issues/98#issuecomment-123222277","issue_url":"https://api.github.com/repos/fchollet/keras/issues/98","id":123222277,"user":{"login":"fchollet","id":710255,"avatar_url":"https://avatars.githubusercontent.com/u/710255?v=3","gravatar_id":"","url":"https://api.github.com/users/fchollet","html_url":"https://github.com/fchollet","followers_url":"https://api.github.com/users/fchollet/followers","following_url":"https://api.github.com/users/fchollet/following{/other_user}","gists_url":"https://api.github.com/users/fchollet/gists{/gist_id}","starred_url":"https://api.github.com/users/fchollet/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fchollet/subscriptions","organizations_url":"https://api.github.com/users/fchollet/orgs","repos_url":"https://api.github.com/users/fchollet/repos","events_url":"https://api.github.com/users/fchollet/events{/privacy}","received_events_url":"https://api.github.com/users/fchollet/received_events","type":"User","site_admin":false},"created_at":"2015-07-21T08:59:58Z","updated_at":"2015-07-21T08:59:58Z","body":"@wxs the fact that the weights of the network are continuously changing (\"continuous\" is the keyword here: each batch brings an epsilon change) certainly does not negate the notion of state. In the same way that, in a FFWD network, after you applied some update to layer 1, the following layer 2 can still provide accurate predictions from the output of layer 1..."}}