{"action":"created","issue":{"url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/6611","repository_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j","labels_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/6611/labels{/name}","comments_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/6611/comments","events_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/6611/events","html_url":"https://github.com/deeplearning4j/deeplearning4j/issues/6611","id":371725064,"node_id":"MDU6SXNzdWUzNzE3MjUwNjQ=","number":6611,"title":"Integer overflow on large number of parameters","user":{"login":"DanielWieczorek","id":654372,"node_id":"MDQ6VXNlcjY1NDM3Mg==","avatar_url":"https://avatars0.githubusercontent.com/u/654372?v=4","gravatar_id":"","url":"https://api.github.com/users/DanielWieczorek","html_url":"https://github.com/DanielWieczorek","followers_url":"https://api.github.com/users/DanielWieczorek/followers","following_url":"https://api.github.com/users/DanielWieczorek/following{/other_user}","gists_url":"https://api.github.com/users/DanielWieczorek/gists{/gist_id}","starred_url":"https://api.github.com/users/DanielWieczorek/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/DanielWieczorek/subscriptions","organizations_url":"https://api.github.com/users/DanielWieczorek/orgs","repos_url":"https://api.github.com/users/DanielWieczorek/repos","events_url":"https://api.github.com/users/DanielWieczorek/events{/privacy}","received_events_url":"https://api.github.com/users/DanielWieczorek/received_events","type":"User","site_admin":false},"labels":[{"id":934488384,"node_id":"MDU6TGFiZWw5MzQ0ODgzODQ=","url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/labels/DL4J","name":"DL4J","color":"98f2d7","default":false}],"state":"closed","locked":false,"assignee":{"login":"AlexDBlack","id":2360237,"node_id":"MDQ6VXNlcjIzNjAyMzc=","avatar_url":"https://avatars0.githubusercontent.com/u/2360237?v=4","gravatar_id":"","url":"https://api.github.com/users/AlexDBlack","html_url":"https://github.com/AlexDBlack","followers_url":"https://api.github.com/users/AlexDBlack/followers","following_url":"https://api.github.com/users/AlexDBlack/following{/other_user}","gists_url":"https://api.github.com/users/AlexDBlack/gists{/gist_id}","starred_url":"https://api.github.com/users/AlexDBlack/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/AlexDBlack/subscriptions","organizations_url":"https://api.github.com/users/AlexDBlack/orgs","repos_url":"https://api.github.com/users/AlexDBlack/repos","events_url":"https://api.github.com/users/AlexDBlack/events{/privacy}","received_events_url":"https://api.github.com/users/AlexDBlack/received_events","type":"User","site_admin":false},"assignees":[{"login":"AlexDBlack","id":2360237,"node_id":"MDQ6VXNlcjIzNjAyMzc=","avatar_url":"https://avatars0.githubusercontent.com/u/2360237?v=4","gravatar_id":"","url":"https://api.github.com/users/AlexDBlack","html_url":"https://github.com/AlexDBlack","followers_url":"https://api.github.com/users/AlexDBlack/followers","following_url":"https://api.github.com/users/AlexDBlack/following{/other_user}","gists_url":"https://api.github.com/users/AlexDBlack/gists{/gist_id}","starred_url":"https://api.github.com/users/AlexDBlack/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/AlexDBlack/subscriptions","organizations_url":"https://api.github.com/users/AlexDBlack/orgs","repos_url":"https://api.github.com/users/AlexDBlack/repos","events_url":"https://api.github.com/users/AlexDBlack/events{/privacy}","received_events_url":"https://api.github.com/users/AlexDBlack/received_events","type":"User","site_admin":false}],"milestone":null,"comments":1,"created_at":"2018-10-18T21:40:49Z","updated_at":"2018-11-25T06:38:38Z","closed_at":"2018-10-26T05:52:53Z","author_association":"NONE","body":"While experimenting with my NN configuration, I stumbled over a NullPointerException during initialization of the MultiLayerNetwork:\r\n\r\n```\r\njava.lang.NullPointerException: null\r\n\tat org.deeplearning4j.nn.multilayer.MultiLayerNetwork.init(MultiLayerNetwork.java:621) ~[deeplearning4j-nn-1.0.0-beta2.jar:?]\r\n\tat org.deeplearning4j.nn.multilayer.MultiLayerNetwork.init(MultiLayerNetwork.java:530) ~[deeplearning4j-nn-1.0.0-beta2.jar:?]\r\n\tat de.wieczorek.rss.advisor.business.TradingNeuralNetwork.buildNetwork(TradingNeuralNetwork.java:123) ~[classes/:?]\r\n\tat de.wieczorek.nn.AbstractNeuralNetwork.train(AbstractNeuralNetwork.java:31) ~[classes/:?]\r\n\tat de.wieczorek.rss.advisor.business.TradingNeuralNetwork$Proxy$_$$_WeldClientProxy.train(Unknown Source) ~[classes/:?]\r\n\tat de.wieczorek.rss.advisor.business.TrainingTimer.run(TrainingTimer.java:47) [classes/:?]\r\n\tat de.wieczorek.rss.advisor.business.TrainingTimer$Proxy$_$$_WeldClientProxy.run(Unknown Source) [classes/:?]\r\n\tat de.wieczorek.rss.core.timer.RecurrentTaskRunner.run(RecurrentTaskRunner.java:42) [classes/:?]\r\n\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:514) [?:?]\r\n\tat java.util.concurrent.FutureTask.run(FutureTask.java:264) [?:?]\r\n\tat java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:299) [?:?]\r\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1167) [?:?]\r\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:641) [?:?]\r\n\tat java.lang.Thread.run(Thread.java:844) [?:?]\r\n```\r\n\r\nApparently the number of parameters was too large. This code segment looks a bit fishy:\r\n```            \r\n            int paramLength = 0;\r\n            val nParamsPerLayer = new long[nLayers];\r\n            for (int i = 0; i < nLayers; i++) {\r\n                NeuralNetConfiguration conf = layerWiseConfigurations.getConf(i);\r\n                nParamsPerLayer[i] = conf.getLayer().initializer().numParams(conf);\r\n                paramLength += nParamsPerLayer[i];\r\n            }\r\n```\r\n\r\nThe parameters are collected in a list of longs and accumulated in an int. Also the subsequent handling does not regard values < 0 for _paramLength_. This causes that _flattenedParams_ is never initialized since it is assumed that there are no parameters. \r\n\r\nNo matter if my config makes sense, I would expect an Exception telling me to rethink my network design.\r\n"},"comment":{"url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/comments/441419087","html_url":"https://github.com/deeplearning4j/deeplearning4j/issues/6611#issuecomment-441419087","issue_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/6611","id":441419087,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0MTQxOTA4Nw==","user":{"login":"lock[bot]","id":33595554,"node_id":"MDM6Qm90MzM1OTU1NTQ=","avatar_url":"https://avatars1.githubusercontent.com/in/6672?v=4","gravatar_id":"","url":"https://api.github.com/users/lock%5Bbot%5D","html_url":"https://github.com/apps/lock","followers_url":"https://api.github.com/users/lock%5Bbot%5D/followers","following_url":"https://api.github.com/users/lock%5Bbot%5D/following{/other_user}","gists_url":"https://api.github.com/users/lock%5Bbot%5D/gists{/gist_id}","starred_url":"https://api.github.com/users/lock%5Bbot%5D/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/lock%5Bbot%5D/subscriptions","organizations_url":"https://api.github.com/users/lock%5Bbot%5D/orgs","repos_url":"https://api.github.com/users/lock%5Bbot%5D/repos","events_url":"https://api.github.com/users/lock%5Bbot%5D/events{/privacy}","received_events_url":"https://api.github.com/users/lock%5Bbot%5D/received_events","type":"Bot","site_admin":false},"created_at":"2018-11-25T06:38:38Z","updated_at":"2018-11-25T06:38:38Z","author_association":"NONE","body":"This thread has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs.\n"}}
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