{"action":"closed","issue":{"url":"https://api.github.com/repos/yunjey/pytorch-tutorial/issues/103","repository_url":"https://api.github.com/repos/yunjey/pytorch-tutorial","labels_url":"https://api.github.com/repos/yunjey/pytorch-tutorial/issues/103/labels{/name}","comments_url":"https://api.github.com/repos/yunjey/pytorch-tutorial/issues/103/comments","events_url":"https://api.github.com/repos/yunjey/pytorch-tutorial/issues/103/events","html_url":"https://github.com/yunjey/pytorch-tutorial/issues/103","id":307523981,"node_id":"MDU6SXNzdWUzMDc1MjM5ODE=","number":103,"title":"Train Process so slow","user":{"login":"khaerulumam42","id":35139151,"node_id":"MDQ6VXNlcjM1MTM5MTUx","avatar_url":"https://avatars1.githubusercontent.com/u/35139151?v=4","gravatar_id":"","url":"https://api.github.com/users/khaerulumam42","html_url":"https://github.com/khaerulumam42","followers_url":"https://api.github.com/users/khaerulumam42/followers","following_url":"https://api.github.com/users/khaerulumam42/following{/other_user}","gists_url":"https://api.github.com/users/khaerulumam42/gists{/gist_id}","starred_url":"https://api.github.com/users/khaerulumam42/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/khaerulumam42/subscriptions","organizations_url":"https://api.github.com/users/khaerulumam42/orgs","repos_url":"https://api.github.com/users/khaerulumam42/repos","events_url":"https://api.github.com/users/khaerulumam42/events{/privacy}","received_events_url":"https://api.github.com/users/khaerulumam42/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-03-22T06:43:31Z","updated_at":"2018-11-05T16:01:06Z","closed_at":"2018-11-05T16:01:06Z","author_association":"NONE","body":"I tried to run train.py in Ubuntu 16.04 which installed cuda 8.0, CUDnn, python 3.5, when i check using `torch.cuda.is_available()` show output is \r\n\r\n> True\r\n\r\n but when I try to add code to check if cuda available or not in like this \r\n`if torch.cuda.is_available():\r\n    encoder.cuda()\r\n    decoder.cuda()\r\n    print(\"cuda is available\")\r\nelse:\r\n    print(\"None of cuda cant use\")`\r\nand the output is \r\n\r\n> None of cuda cant use\r\n\r\nI also add os.environ['CUDA VISIBLE DEVICES'] = '1' after import all packages. \r\nIs it cuda unavailable or actually this training consume much times?\r\nThanks for your answer\r\n"}}
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