{"action":"closed","issue":{"url":"https://api.github.com/repos/MrGemy95/Tensorflow-Project-Template/issues/5","repository_url":"https://api.github.com/repos/MrGemy95/Tensorflow-Project-Template","labels_url":"https://api.github.com/repos/MrGemy95/Tensorflow-Project-Template/issues/5/labels{/name}","comments_url":"https://api.github.com/repos/MrGemy95/Tensorflow-Project-Template/issues/5/comments","events_url":"https://api.github.com/repos/MrGemy95/Tensorflow-Project-Template/issues/5/events","html_url":"https://github.com/MrGemy95/Tensorflow-Project-Template/issues/5","id":295490987,"number":5,"title":"I think might some problem here","user":{"login":"HannH","id":18132006,"avatar_url":"https://avatars0.githubusercontent.com/u/18132006?v=4","gravatar_id":"","url":"https://api.github.com/users/HannH","html_url":"https://github.com/HannH","followers_url":"https://api.github.com/users/HannH/followers","following_url":"https://api.github.com/users/HannH/following{/other_user}","gists_url":"https://api.github.com/users/HannH/gists{/gist_id}","starred_url":"https://api.github.com/users/HannH/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/HannH/subscriptions","organizations_url":"https://api.github.com/users/HannH/orgs","repos_url":"https://api.github.com/users/HannH/repos","events_url":"https://api.github.com/users/HannH/events{/privacy}","received_events_url":"https://api.github.com/users/HannH/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-02-08T12:17:30Z","updated_at":"2018-02-10T11:09:09Z","closed_at":"2018-02-10T11:09:09Z","author_association":"NONE","body":"https://github.com/MrGemy95/Tensorflow-Project-Template/blob/e873ec8c97dea7fee2c70fc7f5ace362a9d29339/models/example_model.py#L23\r\nI think it maybe not good idea writing optimizer there. Programer need to shrink the model size when release a well trained model. Sometimes we may want to save variables except optimizer like this:\r\n```\r\nnet = ExampleModel.build_model(...)#only net defines inside\r\nsaver = tf.train.Saver()\r\nwith tf.Session() as sess:\r\n    saver.restore(sess, model_path)\r\n    ...\r\n    do something to resave model for shrink size\r\n    ...\r\n``` \r\nIt will be trouble in such situation when you put the model defines and optmizer together\r\n\r\n\r\n"}}
{"actor":{"display_login":"MrGemy95"}}