{"action":"closed","issue":{"url":"https://api.github.com/repos/vlfeat/matconvnet/issues/568","repository_url":"https://api.github.com/repos/vlfeat/matconvnet","labels_url":"https://api.github.com/repos/vlfeat/matconvnet/issues/568/labels{/name}","comments_url":"https://api.github.com/repos/vlfeat/matconvnet/issues/568/comments","events_url":"https://api.github.com/repos/vlfeat/matconvnet/issues/568/events","html_url":"https://github.com/vlfeat/matconvnet/issues/568","id":158923804,"number":568,"title":"cnn_train_dag example syntax error","user":{"login":"omair-kg","id":10205648,"avatar_url":"https://avatars.githubusercontent.com/u/10205648?v=3","gravatar_id":"","url":"https://api.github.com/users/omair-kg","html_url":"https://github.com/omair-kg","followers_url":"https://api.github.com/users/omair-kg/followers","following_url":"https://api.github.com/users/omair-kg/following{/other_user}","gists_url":"https://api.github.com/users/omair-kg/gists{/gist_id}","starred_url":"https://api.github.com/users/omair-kg/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/omair-kg/subscriptions","organizations_url":"https://api.github.com/users/omair-kg/orgs","repos_url":"https://api.github.com/users/omair-kg/repos","events_url":"https://api.github.com/users/omair-kg/events{/privacy}","received_events_url":"https://api.github.com/users/omair-kg/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":1,"created_at":"2016-06-07T13:32:12Z","updated_at":"2016-06-09T15:29:39Z","closed_at":"2016-06-09T15:29:39Z","body":"In the cnn_train_dag wrapper in the accumulate_gradients function there is a syntax error in the switch statement (line 288). \r\n\r\n```\r\n  switch net.params(p).trainMethod\r\n\r\n    case 'average' % mainly for batch normalization\r\n   ...\r\n    case 'gradient'\r\n   ...\r\n    case 'otherwise'\r\n    ...\r\n  end\r\n```\r\nInstead of case 'otherwise' it should be just 'otherwise'. I found out the hard way when my own training method was overwritten and the error wasn't caught since the switch was looking for otherwise as a case."}}
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