{"action":"created","issue":{"url":"https://api.github.com/repos/Element-Research/rnn/issues/60","labels_url":"https://api.github.com/repos/Element-Research/rnn/issues/60/labels{/name}","comments_url":"https://api.github.com/repos/Element-Research/rnn/issues/60/comments","events_url":"https://api.github.com/repos/Element-Research/rnn/issues/60/events","html_url":"https://github.com/Element-Research/rnn/issues/60","id":118191613,"number":60,"title":"Prefer if examples dont need dp","user":{"login":"hughperkins","id":123560,"avatar_url":"https://avatars.githubusercontent.com/u/123560?v=3","gravatar_id":"","url":"https://api.github.com/users/hughperkins","html_url":"https://github.com/hughperkins","followers_url":"https://api.github.com/users/hughperkins/followers","following_url":"https://api.github.com/users/hughperkins/following{/other_user}","gists_url":"https://api.github.com/users/hughperkins/gists{/gist_id}","starred_url":"https://api.github.com/users/hughperkins/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hughperkins/subscriptions","organizations_url":"https://api.github.com/users/hughperkins/orgs","repos_url":"https://api.github.com/users/hughperkins/repos","events_url":"https://api.github.com/users/hughperkins/events{/privacy}","received_events_url":"https://api.github.com/users/hughperkins/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":4,"created_at":"2015-11-21T11:46:03Z","updated_at":"2015-12-07T21:48:18Z","closed_at":null,"body":"I reckon it would be easier to use the examples if they didnt need one to learn dp to understand them fully.\r\n\r\nBasically, currently one has to kind of learn both rnn and dp together, to understand the examples.  I reckon it would be faster learning curve if the examples in rnn assumed only knowledge of rnn, and core Torch libraries, such as nn etc.\r\n"},"comment":{"url":"https://api.github.com/repos/Element-Research/rnn/issues/comments/162675116","html_url":"https://github.com/Element-Research/rnn/issues/60#issuecomment-162675116","issue_url":"https://api.github.com/repos/Element-Research/rnn/issues/60","id":162675116,"user":{"login":"jfsantos","id":5733,"avatar_url":"https://avatars.githubusercontent.com/u/5733?v=3","gravatar_id":"","url":"https://api.github.com/users/jfsantos","html_url":"https://github.com/jfsantos","followers_url":"https://api.github.com/users/jfsantos/followers","following_url":"https://api.github.com/users/jfsantos/following{/other_user}","gists_url":"https://api.github.com/users/jfsantos/gists{/gist_id}","starred_url":"https://api.github.com/users/jfsantos/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jfsantos/subscriptions","organizations_url":"https://api.github.com/users/jfsantos/orgs","repos_url":"https://api.github.com/users/jfsantos/repos","events_url":"https://api.github.com/users/jfsantos/events{/privacy}","received_events_url":"https://api.github.com/users/jfsantos/received_events","type":"User","site_admin":false},"created_at":"2015-12-07T21:48:18Z","updated_at":"2015-12-07T21:48:18Z","body":"Hi,\r\n\r\nsorry to get into the conversation, but I am working on a model which looks like char-rnn using rnn and want to use optim as well, so I think my comment is at least a bit relevant :)\r\n\r\nThe way char-rnn was initially implemented, the model does not predict a sequence, but a single character each time. Therefore, using nn.SequencerCriterion for the output does not work. One cannot use a `nn.___Criterion` as the behavior is different: models wrapped by rnn.Sequencer require a `gradOutput` table, not a single gradient vector. @nicholas-leonard, any tips on how to train such a model using rnn?"}}