{"action":"created","issue":{"url":"https://api.github.com/repos/fchollet/keras/issues/1857","repository_url":"https://api.github.com/repos/fchollet/keras","labels_url":"https://api.github.com/repos/fchollet/keras/issues/1857/labels{/name}","comments_url":"https://api.github.com/repos/fchollet/keras/issues/1857/comments","events_url":"https://api.github.com/repos/fchollet/keras/issues/1857/events","html_url":"https://github.com/fchollet/keras/issues/1857","id":137393058,"number":1857,"title":"fit_generator broken in 0.3.2?","user":{"login":"ttal","id":4337021,"avatar_url":"https://avatars.githubusercontent.com/u/4337021?v=3","gravatar_id":"","url":"https://api.github.com/users/ttal","html_url":"https://github.com/ttal","followers_url":"https://api.github.com/users/ttal/followers","following_url":"https://api.github.com/users/ttal/following{/other_user}","gists_url":"https://api.github.com/users/ttal/gists{/gist_id}","starred_url":"https://api.github.com/users/ttal/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ttal/subscriptions","organizations_url":"https://api.github.com/users/ttal/orgs","repos_url":"https://api.github.com/users/ttal/repos","events_url":"https://api.github.com/users/ttal/events{/privacy}","received_events_url":"https://api.github.com/users/ttal/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":6,"created_at":"2016-02-29T22:09:09Z","updated_at":"2016-03-01T19:16:35Z","closed_at":null,"body":"After upgrading to 0.3.2 I noticed that model fitting with fit_generator is slower than it used to be.  I tested this with a simple LSTM net (theano backed) on a single gpu core AWS instance, and found that 0.3.2 is about 20 times slower than 0.3.1.  Any ideas to why that is?  The differemce in speed is sort of similar to using cpu vs. gpu I think.\r\n\r\nAlso, somewhat related, the new nb_val_samples that recently appeared in the docs is not actually implemented in 0.3.2 (but is in the git version)."},"comment":{"url":"https://api.github.com/repos/fchollet/keras/issues/comments/190859165","html_url":"https://github.com/fchollet/keras/issues/1857#issuecomment-190859165","issue_url":"https://api.github.com/repos/fchollet/keras/issues/1857","id":190859165,"user":{"login":"ttal","id":4337021,"avatar_url":"https://avatars.githubusercontent.com/u/4337021?v=3","gravatar_id":"","url":"https://api.github.com/users/ttal","html_url":"https://github.com/ttal","followers_url":"https://api.github.com/users/ttal/followers","following_url":"https://api.github.com/users/ttal/following{/other_user}","gists_url":"https://api.github.com/users/ttal/gists{/gist_id}","starred_url":"https://api.github.com/users/ttal/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ttal/subscriptions","organizations_url":"https://api.github.com/users/ttal/orgs","repos_url":"https://api.github.com/users/ttal/repos","events_url":"https://api.github.com/users/ttal/events{/privacy}","received_events_url":"https://api.github.com/users/ttal/received_events","type":"User","site_admin":false},"created_at":"2016-03-01T19:16:35Z","updated_at":"2016-03-01T19:16:35Z","body":"@qdbp just for training - I load a subset into memory for validation so that I can compare side-by-side with memory-based training without validation being an issue."}}