{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/472","labels_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/472/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/472/comments","events_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/472/events","html_url":"https://github.com/NVIDIA/DIGITS/issues/472","id":122021353,"number":472,"title":"Evaluating test data","user":{"login":"aabobakr","id":13028330,"avatar_url":"https://avatars.githubusercontent.com/u/13028330?v=3","gravatar_id":"","url":"https://api.github.com/users/aabobakr","html_url":"https://github.com/aabobakr","followers_url":"https://api.github.com/users/aabobakr/followers","following_url":"https://api.github.com/users/aabobakr/following{/other_user}","gists_url":"https://api.github.com/users/aabobakr/gists{/gist_id}","starred_url":"https://api.github.com/users/aabobakr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/aabobakr/subscriptions","organizations_url":"https://api.github.com/users/aabobakr/orgs","repos_url":"https://api.github.com/users/aabobakr/repos","events_url":"https://api.github.com/users/aabobakr/events{/privacy}","received_events_url":"https://api.github.com/users/aabobakr/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/NVIDIA/DIGITS/labels/duplicate","name":"duplicate","color":"cccccc"},{"url":"https://api.github.com/repos/NVIDIA/DIGITS/labels/enhancement","name":"enhancement","color":"84b6eb"}],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":3,"created_at":"2015-12-14T11:07:24Z","updated_at":"2015-12-15T01:55:58Z","closed_at":"2015-12-14T17:39:30Z","body":"While training a deep network, the framework displays the training and validation loss which is fine. After the training ends, I can test a single image or many images at once. \r\n\r\nI am wondering, how can I evaluate the overall loss over the test dataset? , Currently, I have to export the model and test it outside digits to compute the average loss on the test data. \r\n\r\nThe only option available in digits is to upload images and see the classification result one by one on the browser. Am I missing something?\r\n"},"comment":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/comments/164618015","html_url":"https://github.com/NVIDIA/DIGITS/issues/472#issuecomment-164618015","issue_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/472","id":164618015,"user":{"login":"aabobakr","id":13028330,"avatar_url":"https://avatars.githubusercontent.com/u/13028330?v=3","gravatar_id":"","url":"https://api.github.com/users/aabobakr","html_url":"https://github.com/aabobakr","followers_url":"https://api.github.com/users/aabobakr/followers","following_url":"https://api.github.com/users/aabobakr/following{/other_user}","gists_url":"https://api.github.com/users/aabobakr/gists{/gist_id}","starred_url":"https://api.github.com/users/aabobakr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/aabobakr/subscriptions","organizations_url":"https://api.github.com/users/aabobakr/orgs","repos_url":"https://api.github.com/users/aabobakr/repos","events_url":"https://api.github.com/users/aabobakr/events{/privacy}","received_events_url":"https://api.github.com/users/aabobakr/received_events","type":"User","site_admin":false},"created_at":"2015-12-15T01:55:58Z","updated_at":"2015-12-15T01:55:58Z","body":"@gheinrich Yes that is exactly what I am asking about. But, your REST API suggestion is fantastic. I will give it a try."}}