{"action":"closed","issue":{"url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/388","labels_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/388/labels{/name}","comments_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/388/comments","events_url":"https://api.github.com/repos/deeplearning4j/deeplearning4j/issues/388/events","html_url":"https://github.com/deeplearning4j/deeplearning4j/issues/388","id":92425800,"number":388,"title":"improbable convolutional neural net score","user":{"login":"radiodee1","id":8641916,"avatar_url":"https://avatars.githubusercontent.com/u/8641916?v=3","gravatar_id":"","url":"https://api.github.com/users/radiodee1","html_url":"https://github.com/radiodee1","followers_url":"https://api.github.com/users/radiodee1/followers","following_url":"https://api.github.com/users/radiodee1/following{/other_user}","gists_url":"https://api.github.com/users/radiodee1/gists{/gist_id}","starred_url":"https://api.github.com/users/radiodee1/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/radiodee1/subscriptions","organizations_url":"https://api.github.com/users/radiodee1/orgs","repos_url":"https://api.github.com/users/radiodee1/repos","events_url":"https://api.github.com/users/radiodee1/events{/privacy}","received_events_url":"https://api.github.com/users/radiodee1/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":1,"created_at":"2015-07-01T16:21:53Z","updated_at":"2015-07-01T17:59:52Z","closed_at":"2015-07-01T17:59:52Z","body":"I took this segment from the convolutional neural network howto.\r\n\r\nSystem.out.println(\"Build model....\");\r\n        MultiLayerConfiguration conf2 = new NeuralNetConfiguration.Builder()\r\n                .nIn(numRows * numColumns)\r\n                .nOut(outputNum)\r\n                //.seed(seed)\r\n                .batchSize(batchSize)\r\n                .iterations(iterations)\r\n                .weightInit(WeightInit.UNIFORM)\r\n                .activationFunction(\"sigmoid\")\r\n                .filterSize(8, 1, numRows, numColumns)\r\n                .optimizationAlgo(OptimizationAlgorithm.LBFGS)\r\n                .constrainGradientToUnitNorm(true)\r\n                .list(3)\r\n                .hiddenLayerSizes(50)\r\n                .inputPreProcessor(0, new ConvolutionInputPreProcessor(numRows, numColumns))\r\n                .preProcessor(1, new ConvolutionPostProcessor())\r\n                .override(0, new ConfOverride() {\r\n                    public void overrideLayer(int i, NeuralNetConfiguration.Builder builder) {\r\n                        builder.layer(new ConvolutionLayer());\r\n                        builder.convolutionType(ConvolutionLayer.ConvolutionType.MAX);\r\n                        builder.featureMapSize(9, 9);\r\n                    }\r\n                }).override(1, new ConfOverride() {\r\n                    public void overrideLayer(int i, NeuralNetConfiguration.Builder builder) {\r\n                        builder.layer(new SubsamplingLayer());\r\n                    }\r\n                }).override(2, new ClassifierOverride())\r\n                .build();\r\n\r\nLater in the code the following is typically shown in the output window:\r\n\r\no.d.o.l.ScoreIterationListener - Score at iteration 0 is NaN\r\n\r\nMore than half the time the output is NaN, and the remainder of the time I get numbers like '-0.002879561...'. The latter output I find encouraging. It seems random. What am I doing wrong??"}}