{"action":"created","issue":{"url":"https://api.github.com/repos/fstrub95/Autoencoders_cf/issues/2","labels_url":"https://api.github.com/repos/fstrub95/Autoencoders_cf/issues/2/labels{/name}","comments_url":"https://api.github.com/repos/fstrub95/Autoencoders_cf/issues/2/comments","events_url":"https://api.github.com/repos/fstrub95/Autoencoders_cf/issues/2/events","html_url":"https://github.com/fstrub95/Autoencoders_cf/issues/2","id":127921418,"number":2,"title":"Data in .t7 format","user":{"login":"gheinrich","id":3889770,"avatar_url":"https://avatars.githubusercontent.com/u/3889770?v=3","gravatar_id":"","url":"https://api.github.com/users/gheinrich","html_url":"https://github.com/gheinrich","followers_url":"https://api.github.com/users/gheinrich/followers","following_url":"https://api.github.com/users/gheinrich/following{/other_user}","gists_url":"https://api.github.com/users/gheinrich/gists{/gist_id}","starred_url":"https://api.github.com/users/gheinrich/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gheinrich/subscriptions","organizations_url":"https://api.github.com/users/gheinrich/orgs","repos_url":"https://api.github.com/users/gheinrich/repos","events_url":"https://api.github.com/users/gheinrich/events{/privacy}","received_events_url":"https://api.github.com/users/gheinrich/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":1,"created_at":"2016-01-21T13:14:09Z","updated_at":"2016-01-21T15:25:12Z","closed_at":null,"body":"Hi and thanks for making this project online! I am trying to use branch `AutoEnc_1.1.0.0` to test the GPU implementation however I am not sure how to convert the MovieLens dataset from `.dat` to `.t7` format. I tried using the Jester dataset but got an error...\r\n\r\n```\r\n$ th main.lua -file ../data/jester/jester-full.t7 \r\nOptions: \t\r\n - gpu  \t : true\t\r\n - file  \t : ../data/jester/jester-full.t7\t\r\n - seed  \t : 1234\t\r\n - conf  \t : config.template.lua\t\r\nloading data...\t\r\n/home/greg/ws/torch/install/bin/luajit: /home/greg/ws/torch/install/share/lua/5.1/torch/File.lua:322: unknown object\r\nstack traceback:\r\n\t[C]: in function 'error'\r\n\t/home/greg/ws/torch/install/share/lua/5.1/torch/File.lua:322: in function 'readObject'\r\n\t/home/greg/ws/torch/install/share/lua/5.1/torch/File.lua:347: in function 'load'\r\n\tmain.lua:56: in main chunk\r\n\t[C]: in function 'dofile'\r\n\t...g/ws/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:145: in main chunk\r\n\t[C]: at 0x00406670\r\n```\r\n\r\nSorry if I missed the relevant bit in the documentation.\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/fstrub95/Autoencoders_cf/issues/comments/173605166","html_url":"https://github.com/fstrub95/Autoencoders_cf/issues/2#issuecomment-173605166","issue_url":"https://api.github.com/repos/fstrub95/Autoencoders_cf/issues/2","id":173605166,"user":{"login":"fstrub95","id":13366148,"avatar_url":"https://avatars.githubusercontent.com/u/13366148?v=3","gravatar_id":"","url":"https://api.github.com/users/fstrub95","html_url":"https://github.com/fstrub95","followers_url":"https://api.github.com/users/fstrub95/followers","following_url":"https://api.github.com/users/fstrub95/following{/other_user}","gists_url":"https://api.github.com/users/fstrub95/gists{/gist_id}","starred_url":"https://api.github.com/users/fstrub95/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fstrub95/subscriptions","organizations_url":"https://api.github.com/users/fstrub95/orgs","repos_url":"https://api.github.com/users/fstrub95/repos","events_url":"https://api.github.com/users/fstrub95/events{/privacy}","received_events_url":"https://api.github.com/users/fstrub95/received_events","type":"User","site_admin":false},"created_at":"2016-01-21T15:25:12Z","updated_at":"2016-01-21T15:25:12Z","body":"Hi, \r\nYou first need to turn the data into torch format with AutoEnc_1.0.0.0 with the data.lua file.\r\nIf you have your own data format, you need to create a new object that inherit from DataLoader.\r\n\r\n\r\nFor instance:\r\nStore Data for SDAE network for collaborative filtering\r\nOptions\r\n  -ratings  The relative path to your data file [../data/movieLens/ratings-1M.dat]\r\n  -metaUser The relative path to your metadata file for users [../data/movieLens/users-1M.dat]\r\n  -metaItem The relative path to your metadata file for items [../data/movieLens/movies-1M.dat]\r\n  -fileType The data file format (jester/movieLens/classic) [movieLens]\r\n  -out      The data file format (jester/movieLens/classic) [./movieLens-1M.t7]\r\n  -ratio    The training ratio [0.9]\r\n  -seed     The seed [1234]\r\n\r\nth -file ../data/MovieLens-10M/ratings.dat\r\n\r\nThen you can provide the data to main.lua .\r\n\r\nLearn SDAE network for collaborative filtering\r\nOptions\r\n  -file The relative path to your data file (torch format) [./movieLens-1M.t7]\r\n  -conf The relative path to the lua configuration file [config.template.lua]\r\n  -seed The seed [1234]\r\n  -gpu  use gpu [true]\r\n\r\nFor instance with movieLens-10M: \r\nThe following configuration provide a RMSE around 0.780.\r\n\r\nconfigV =\r\n{\r\n   useMetaData = false, --still under development\r\n   layer1 =\r\n   {\r\n      layerSize = 700,\r\n      {\r\n         criterion = nnsparse.SDAECriterionGPU(nn.MSECriterion(),\r\n         {\r\n            alpha = 1.10,\r\n            beta  = 0.828,\r\n            hideRatio = 0.224,\r\n         }),\r\n         noEpoch = 15,\r\n         miniBatchSize = 35,\r\n         learningRate = 0.04,\r\n         learningRateDecay = 0.225,\r\n         weightDecay = 0.08,\r\n      },\r\n\r\n   }\r\n}\r\n\r\nI takes about 6~8 minutes on a GTX 980. \r\n \r\nYet, this branch is still under development. We plan to send a paper for either ICML 2016 or KDD 2016. Thus, the code is not very clean and there are still some nasty hacks for fast prototyping.  \r\nIf you come back in 3/4 weeks. A final version of the code/paper will be pushed. \r\n\r\n "}}