{"action":"opened","issue":{"url":"https://api.github.com/repos/deeplearning4j/nd4j/issues/1501","repository_url":"https://api.github.com/repos/deeplearning4j/nd4j","labels_url":"https://api.github.com/repos/deeplearning4j/nd4j/issues/1501/labels{/name}","comments_url":"https://api.github.com/repos/deeplearning4j/nd4j/issues/1501/comments","events_url":"https://api.github.com/repos/deeplearning4j/nd4j/issues/1501/events","html_url":"https://github.com/deeplearning4j/nd4j/issues/1501","id":195203140,"number":1501,"title":"Exception when using AllocationModel.CACHE_HOST","user":{"login":"mjakobus","id":17254924,"avatar_url":"https://avatars.githubusercontent.com/u/17254924?v=3","gravatar_id":"","url":"https://api.github.com/users/mjakobus","html_url":"https://github.com/mjakobus","followers_url":"https://api.github.com/users/mjakobus/followers","following_url":"https://api.github.com/users/mjakobus/following{/other_user}","gists_url":"https://api.github.com/users/mjakobus/gists{/gist_id}","starred_url":"https://api.github.com/users/mjakobus/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mjakobus/subscriptions","organizations_url":"https://api.github.com/users/mjakobus/orgs","repos_url":"https://api.github.com/users/mjakobus/repos","events_url":"https://api.github.com/users/mjakobus/events{/privacy}","received_events_url":"https://api.github.com/users/mjakobus/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2016-12-13T09:35:32Z","updated_at":"2016-12-13T09:35:32Z","closed_at":null,"body":"Hi,\r\n\r\nwhen using the cuda 8.0 backend with AllocationModel.CACHE_HOST it is throwing an exception when trying to print the cache-statistics (host and device hit ratios) the first time.\r\n\r\n**System informations:**\r\nDeeplearning Version 0.7.1\r\nSystem Windows 10 64bit\r\nNvidia Geforce GTX 1080\r\n\r\n**Stacktrace:**\r\n```\r\nException in thread \"main\" java.lang.IndexOutOfBoundsException: Index: 0, Size: 0\r\n\tat java.util.ArrayList.rangeCheck(ArrayList.java:653)\r\n\tat java.util.ArrayList.get(ArrayList.java:429)\r\n\tat org.nd4j.jita.memory.impl.CudaCachingZeroProvider.printCacheStats(CudaCachingZeroProvider.java:200)\r\n\tat org.nd4j.jita.memory.impl.CudaCachingZeroProvider.malloc(CudaCachingZeroProvider.java:88)\r\n\tat org.nd4j.jita.handler.impl.CudaZeroHandler.alloc(CudaZeroHandler.java:219)\r\n\tat org.nd4j.jita.handler.impl.CudaZeroHandler.alloc(CudaZeroHandler.java:240)\r\n\tat org.nd4j.jita.allocator.impl.AtomicAllocator.allocateMemory(AtomicAllocator.java:386)\r\n\tat org.nd4j.jita.allocator.impl.AtomicAllocator.allocateMemory(AtomicAllocator.java:343)\r\n\tat org.nd4j.linalg.jcublas.buffer.BaseCudaDataBuffer.<init>(BaseCudaDataBuffer.java:144)\r\n\tat org.nd4j.linalg.jcublas.buffer.CudaFloatDataBuffer.<init>(CudaFloatDataBuffer.java:59)\r\n\tat org.nd4j.linalg.jcublas.buffer.factory.CudaDataBufferFactory.createFloat(CudaDataBufferFactory.java:251)\r\n\tat org.nd4j.linalg.factory.Nd4j.createBuffer(Nd4j.java:1304)\r\n\tat org.nd4j.linalg.api.ndarray.BaseNDArray.<init>(BaseNDArray.java:266)\r\n\tat org.nd4j.linalg.jcublas.JCublasNDArray.<init>(JCublasNDArray.java:114)\r\n\tat org.nd4j.linalg.jcublas.JCublasNDArrayFactory.createUninitialized(JCublasNDArrayFactory.java:229)\r\n\tat org.nd4j.linalg.factory.Nd4j.createUninitialized(Nd4j.java:4502)\r\n\tat org.nd4j.linalg.api.shape.Shape.toOffsetZeroCopyHelper(Shape.java:152)\r\n\tat org.nd4j.linalg.api.shape.Shape.toOffsetZeroCopy(Shape.java:108)\r\n\tat org.nd4j.linalg.api.ndarray.BaseNDArray.dup(BaseNDArray.java:1502)\r\n\tat org.nd4j.linalg.jcublas.JCublasNDArray.dup(JCublasNDArray.java:407)\r\n\tat org.nd4j.linalg.api.ndarray.BaseNDArray.mul(BaseNDArray.java:2644)\r\n\tat org.nd4j.linalg.learning.AdaDelta.getGradient(AdaDelta.java:91)\r\n\tat org.deeplearning4j.nn.updater.LayerUpdater.update(LayerUpdater.java:85)\r\n\tat org.deeplearning4j.nn.updater.MultiLayerUpdater.update(MultiLayerUpdater.java:120)\r\n\tat org.deeplearning4j.optimize.solvers.BaseOptimizer.updateGradientAccordingToParams(BaseOptimizer.java:294)\r\n\tat org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:161)\r\n\tat org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:54)\r\n\tat org.deeplearning4j.optimize.Solver.optimize(Solver.java:51)\r\n\tat org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:1503)\r\n\tat org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:1468)\r\n\tat org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:1547)\r\n\tat com.simple.example.MainSimpleExampleExtern.training(MainSimpleExampleExtern.java:341)\r\n\tat com.simple.example.MainSimpleExampleExtern.main(MainSimpleExampleExtern.java:57)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\r\n\tat java.lang.reflect.Method.invoke(Method.java:498)\r\n\tat com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)\r\n```"}}
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