{"action":"created","issue":{"url":"https://api.github.com/repos/tensorflow/tensorflow/issues/565","labels_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/565/labels{/name}","comments_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/565/comments","events_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/565/events","html_url":"https://github.com/tensorflow/tensorflow/issues/565","id":123135295,"number":565,"title":"Softmax Sampling Support","user":{"login":"wchan","id":1131892,"avatar_url":"https://avatars.githubusercontent.com/u/1131892?v=3","gravatar_id":"","url":"https://api.github.com/users/wchan","html_url":"https://github.com/wchan","followers_url":"https://api.github.com/users/wchan/followers","following_url":"https://api.github.com/users/wchan/following{/other_user}","gists_url":"https://api.github.com/users/wchan/gists{/gist_id}","starred_url":"https://api.github.com/users/wchan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/wchan/subscriptions","organizations_url":"https://api.github.com/users/wchan/orgs","repos_url":"https://api.github.com/users/wchan/repos","events_url":"https://api.github.com/users/wchan/events{/privacy}","received_events_url":"https://api.github.com/users/wchan/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":2,"created_at":"2015-12-20T05:31:28Z","updated_at":"2015-12-20T19:06:49Z","closed_at":null,"body":"I couldn't find all the pieces to do scheduled softmax sampling (Bengio et al, 2015), is that supported in TF atm? Is there an TensorOp that can sample from the previous layer?\r\n\r\nThanks!\r\n"},"comment":{"url":"https://api.github.com/repos/tensorflow/tensorflow/issues/comments/166147776","html_url":"https://github.com/tensorflow/tensorflow/issues/565#issuecomment-166147776","issue_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/565","id":166147776,"user":{"login":"wchan","id":1131892,"avatar_url":"https://avatars.githubusercontent.com/u/1131892?v=3","gravatar_id":"","url":"https://api.github.com/users/wchan","html_url":"https://github.com/wchan","followers_url":"https://api.github.com/users/wchan/followers","following_url":"https://api.github.com/users/wchan/following{/other_user}","gists_url":"https://api.github.com/users/wchan/gists{/gist_id}","starred_url":"https://api.github.com/users/wchan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/wchan/subscriptions","organizations_url":"https://api.github.com/users/wchan/orgs","repos_url":"https://api.github.com/users/wchan/repos","events_url":"https://api.github.com/users/wchan/events{/privacy}","received_events_url":"https://api.github.com/users/wchan/received_events","type":"User","site_admin":false},"created_at":"2015-12-20T19:06:49Z","updated_at":"2015-12-20T19:06:49Z","body":"I think that's a different \"sampled softmax\" ;) , the one I was referring to is to condition on a sample (either from the model, or from the ground truth; see Bengio et al, NIPS 2015), as opposed to the \"sampled softmax\" for estimating the partition function."}}