{"action":"created","issue":{"url":"https://api.github.com/repos/mila-udem/blocks/issues/899","labels_url":"https://api.github.com/repos/mila-udem/blocks/issues/899/labels{/name}","comments_url":"https://api.github.com/repos/mila-udem/blocks/issues/899/comments","events_url":"https://api.github.com/repos/mila-udem/blocks/issues/899/events","html_url":"https://github.com/mila-udem/blocks/pull/899","id":114687962,"number":899,"title":"Convolutional network pooling improvements","user":{"login":"dwf","id":60206,"avatar_url":"https://avatars.githubusercontent.com/u/60206?v=3","gravatar_id":"","url":"https://api.github.com/users/dwf","html_url":"https://github.com/dwf","followers_url":"https://api.github.com/users/dwf/followers","following_url":"https://api.github.com/users/dwf/following{/other_user}","gists_url":"https://api.github.com/users/dwf/gists{/gist_id}","starred_url":"https://api.github.com/users/dwf/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dwf/subscriptions","organizations_url":"https://api.github.com/users/dwf/orgs","repos_url":"https://api.github.com/users/dwf/repos","events_url":"https://api.github.com/users/dwf/events{/privacy}","received_events_url":"https://api.github.com/users/dwf/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":7,"created_at":"2015-11-02T21:28:14Z","updated_at":"2015-11-04T20:36:20Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/mila-udem/blocks/pulls/899","html_url":"https://github.com/mila-udem/blocks/pull/899","diff_url":"https://github.com/mila-udem/blocks/pull/899.diff","patch_url":"https://github.com/mila-udem/blocks/pull/899.patch"},"body":"This pull request accomplishes a few things:\r\n* Most notably, an AveragePooling Brick (mentioned in #257), accomplished by refactoring MaxPooling into a base Pooling Brick and MaxPooling and AveragePooling descendants.\r\n  * Tests for AveragePooling's two modes w.r.t. padding.\r\n* More complete wrapping of Theano's `max_pool_2d` function (which, bizarrely, also handles average pooling)\r\n  * Basic tests for these.\r\n* Improvements to ConvolutionalSequence that let you use MaxPooling (and AveragePooling) without ConvolutionalLayer, and make the interface a bit more coherent (i.e. not directly querying `num_filters` for the number of output channels, which is not always the case e.g. with a convolutional maxout layer or something)\r\n* **Change the default `ignore_border` mode to `False`**, while exposing it in an option, with a warning in the docs that modifying it (with certain step configurations) can force computation onto the CPU.\r\n\r\nFixes #894, and an item in #257 that should be crossed off there."},"comment":{"url":"https://api.github.com/repos/mila-udem/blocks/issues/comments/153854936","html_url":"https://github.com/mila-udem/blocks/pull/899#issuecomment-153854936","issue_url":"https://api.github.com/repos/mila-udem/blocks/issues/899","id":153854936,"user":{"login":"dmitriy-serdyuk","id":2872615,"avatar_url":"https://avatars.githubusercontent.com/u/2872615?v=3","gravatar_id":"","url":"https://api.github.com/users/dmitriy-serdyuk","html_url":"https://github.com/dmitriy-serdyuk","followers_url":"https://api.github.com/users/dmitriy-serdyuk/followers","following_url":"https://api.github.com/users/dmitriy-serdyuk/following{/other_user}","gists_url":"https://api.github.com/users/dmitriy-serdyuk/gists{/gist_id}","starred_url":"https://api.github.com/users/dmitriy-serdyuk/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dmitriy-serdyuk/subscriptions","organizations_url":"https://api.github.com/users/dmitriy-serdyuk/orgs","repos_url":"https://api.github.com/users/dmitriy-serdyuk/repos","events_url":"https://api.github.com/users/dmitriy-serdyuk/events{/privacy}","received_events_url":"https://api.github.com/users/dmitriy-serdyuk/received_events","type":"User","site_admin":false},"created_at":"2015-11-04T20:36:20Z","updated_at":"2015-11-04T20:36:20Z","body":"Have you tried to run LeNet example or your convnet with these changes?"}}