{"action":"opened","issue":{"url":"https://api.github.com/repos/apple/turicreate/issues/1274","repository_url":"https://api.github.com/repos/apple/turicreate","labels_url":"https://api.github.com/repos/apple/turicreate/issues/1274/labels{/name}","comments_url":"https://api.github.com/repos/apple/turicreate/issues/1274/comments","events_url":"https://api.github.com/repos/apple/turicreate/issues/1274/events","html_url":"https://github.com/apple/turicreate/issues/1274","id":394265044,"node_id":"MDU6SXNzdWUzOTQyNjUwNDQ=","number":1274,"title":"Boosted trees classifier crash for 100k plus entries","user":{"login":"allenc84","id":7831769,"node_id":"MDQ6VXNlcjc4MzE3Njk=","avatar_url":"https://avatars1.githubusercontent.com/u/7831769?v=4","gravatar_id":"","url":"https://api.github.com/users/allenc84","html_url":"https://github.com/allenc84","followers_url":"https://api.github.com/users/allenc84/followers","following_url":"https://api.github.com/users/allenc84/following{/other_user}","gists_url":"https://api.github.com/users/allenc84/gists{/gist_id}","starred_url":"https://api.github.com/users/allenc84/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/allenc84/subscriptions","organizations_url":"https://api.github.com/users/allenc84/orgs","repos_url":"https://api.github.com/users/allenc84/repos","events_url":"https://api.github.com/users/allenc84/events{/privacy}","received_events_url":"https://api.github.com/users/allenc84/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-12-27T00:42:55Z","updated_at":"2018-12-27T00:42:55Z","closed_at":null,"author_association":"NONE","body":"Hi, I'm running a simple Boosted Tree Classifier on a dataset that has 5 features. \r\n\r\nIt seems to run fine for small datasets (up to 50k entries), however, once I start to get to 100k and up it begins to crash.\r\n\r\nProblem is, my dataset is 13M lines, so 100k is a tiny subset of the data I'd like to go into the ml model (to export and use in Core ML).\r\n\r\nI'm using a high memory instance on google cloud (n1-highmem-64), which has 64 CPU cores, 416 GB of memory, and 200 GB of storage.\r\n\r\nAny idea what the issue is, and how I can get turicreate to build a model for a dataset w/ 13M lines?\r\n\r\nAlternatively, any guidance on how to utilize the GPU optimized instances of google cloud?\r\n\r\nParsing completed. Parsed 99999 lines in 0.112287 secs.\r\nPROGRESS: Creating a validation set from 5 percent of training data. This may take a while.\r\n          You can set ``validation_set=None`` to disable validation tracking.\r\n\r\nBoosted trees classifier:\r\n--------------------------------------------------------\r\nNumber of examples          : 75899\r\nNumber of classes           : 505\r\nNumber of feature columns   : 5\r\nNumber of unpacked features : 5\r\n+-----------+--------------+-------------------+---------------------+-------------------+---------------------+\r\n| Iteration | Elapsed Time | Training Accuracy | Validation Accuracy | Training Log Loss | Validation Log Loss |\r\n+-----------+--------------+-------------------+---------------------+-------------------+---------------------+\r\n| 1         | 13.308831    | 0.057563          | 0.051994            | 5.327710          | 5.400651            |\r\n| 2         | 22.218108    | 0.061872          | 0.054770            | 4.877129          | 4.990599            |\r\n| 3         | 31.183954    | 0.066206          | 0.054013            | 4.679235          | 4.826240            |\r\n| 4         | 40.197789    | 0.069579          | 0.055528            | 4.541399          | 4.710229            |\r\n| 5         | 49.406107    | 0.073506          | 0.059061            | 4.435775          | 4.627263            |\r\n| 7         | 68.160059    | 0.078789          | 0.059061            | 4.285475          | 4.513437            |\r\n| 8         | 77.481043    | 0.081121          | 0.060828            | 4.229251          | 4.474643            |\r\n| 9         | 86.975972    | 0.083005          | 0.062342            | 4.181239          | 4.443032            |\r\n| 10        | 96.488387    | 0.085535          | 0.061585            | 4.139843          | 4.416114            |\r\n+-----------+--------------+-------------------+---------------------+-------------------+---------------------+\r\ngot model\r\ngot predictions\r\nTraceback (most recent call last):\r\n  File \"weightReccor_classifier.py\", line 17, in <module>\r\n    results = model.evaluate(test_data)\r\n  File \"/home/allenchen/.local/lib/python2.7/site-packages/turicreate/toolkits/classifier/boosted_trees_classifier.py\", line 218, in evaluate\r\n    metric=metric)\r\n  File \"/home/allenchen/.local/lib/python2.7/site-packages/turicreate/toolkits/_supervised_learning.py\", line 158, in evaluate\r\n    dataset, missing_value_action, metric);\r\n  File \"/home/allenchen/.local/lib/python2.7/site-packages/turicreate/extensions.py\", line 290, in <lambda>\r\n    ret = lambda *args, **kwargs: self.__run_class_function(name, args, kwargs)\r\n  File \"/home/allenchen/.local/lib/python2.7/site-packages/turicreate/extensions.py\", line 274, in __run_class_function\r\n    ret = self._tkclass.call_function(fnname, argument_dict)\r\n  File \"turicreate/cython/cy_model.pyx\", line 35, in turicreate.cython.cy_model.UnityModel.call_function\r\n  File \"turicreate/cython/cy_model.pyx\", line 40, in turicreate.cython.cy_model.UnityModel.call_function\r\nIndexError: map::at\r\n\r\n"}}
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