{"action":"closed","issue":{"url":"https://api.github.com/repos/tensorflow/tensorflow/issues/4709","repository_url":"https://api.github.com/repos/tensorflow/tensorflow","labels_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/4709/labels{/name}","comments_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/4709/comments","events_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/4709/events","html_url":"https://github.com/tensorflow/tensorflow/issues/4709","id":180467114,"number":4709,"title":"Is tensorflow consuming much more memory than torch?","user":{"login":"yxchng","id":10518587,"avatar_url":"https://avatars.githubusercontent.com/u/10518587?v=3","gravatar_id":"","url":"https://api.github.com/users/yxchng","html_url":"https://github.com/yxchng","followers_url":"https://api.github.com/users/yxchng/followers","following_url":"https://api.github.com/users/yxchng/following{/other_user}","gists_url":"https://api.github.com/users/yxchng/gists{/gist_id}","starred_url":"https://api.github.com/users/yxchng/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yxchng/subscriptions","organizations_url":"https://api.github.com/users/yxchng/orgs","repos_url":"https://api.github.com/users/yxchng/repos","events_url":"https://api.github.com/users/yxchng/events{/privacy}","received_events_url":"https://api.github.com/users/yxchng/received_events","type":"User","site_admin":false},"labels":[{"id":386191887,"url":"https://api.github.com/repos/tensorflow/tensorflow/labels/awaiting%20response","name":"awaiting response","color":"5319e7","default":false}],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":12,"created_at":"2016-10-01T16:53:29Z","updated_at":"2016-11-11T17:45:55Z","closed_at":"2016-11-11T17:45:55Z","body":"I am trying to replicate the stacked hourglass architecture which is implemented in torch, https://github.com/anewell/pose-hg-train/. However, I am unable to train it using settings in the opts.lua file which set the train batch size as 6, number of train iteration as 8000, test batch size as 1 and number of test iteration as 1000. I understand that I can reduce the batch size or iteration number to fit the network. However, I just want to know if tensorflow is consuming more memory than torch, if the same architecture and settings can be implemented in tensorflow.\n"}}
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