{"action":"closed","issue":{"url":"https://api.github.com/repos/abisee/pointer-generator/issues/25","repository_url":"https://api.github.com/repos/abisee/pointer-generator","labels_url":"https://api.github.com/repos/abisee/pointer-generator/issues/25/labels{/name}","comments_url":"https://api.github.com/repos/abisee/pointer-generator/issues/25/comments","events_url":"https://api.github.com/repos/abisee/pointer-generator/issues/25/events","html_url":"https://github.com/abisee/pointer-generator/issues/25","id":236723676,"number":25,"title":"Out of vocabulary word vectors","user":{"login":"Henry-E","id":12613144,"avatar_url":"https://avatars0.githubusercontent.com/u/12613144?v=3","gravatar_id":"","url":"https://api.github.com/users/Henry-E","html_url":"https://github.com/Henry-E","followers_url":"https://api.github.com/users/Henry-E/followers","following_url":"https://api.github.com/users/Henry-E/following{/other_user}","gists_url":"https://api.github.com/users/Henry-E/gists{/gist_id}","starred_url":"https://api.github.com/users/Henry-E/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Henry-E/subscriptions","organizations_url":"https://api.github.com/users/Henry-E/orgs","repos_url":"https://api.github.com/users/Henry-E/repos","events_url":"https://api.github.com/users/Henry-E/events{/privacy}","received_events_url":"https://api.github.com/users/Henry-E/received_events","type":"User","site_admin":false},"labels":[{"id":589780494,"url":"https://api.github.com/repos/abisee/pointer-generator/labels/question","name":"question","color":"cc317c","default":true}],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2017-06-18T14:16:17Z","updated_at":"2017-06-21T07:36:07Z","closed_at":"2017-06-21T07:36:07Z","body":"I'm interested in implementing something similar in a different framework. And I was wondering how out of vocabulary word vectors are handled. From the code I can see for each example there's a vocab size of 50k + number of unknown words in the article. I'm not super familiar with tensorflow and I was wondering what the out of vocabulary word vectors looked like. Is the vocab size really 50k + maximum number of unknown words in an article. Or are the word vectors for the unknowns set to zero / randomised for every example?\r\n"}}
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