arbiter-error.txt

INFO  [2016-12-12 19:11:54,220] org.deeplearning4j.arbiter.optimize.runner.listener.runner.LoggingOptimizationRunnerStatusListener: Optimization runner: Initialized.
WARN  [2016-12-12 19:13:31,720] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Task failed
! java.lang.OutOfMemoryError: Physical memory usage is too high (21339664384 > Pointer.maxPhysicalBytes)
! at org.bytedeco.javacpp.Pointer.deallocator(Pointer.java:547)
! at org.bytedeco.javacpp.Pointer.init(Pointer.java:121)
! at org.bytedeco.javacpp.PointerPointer.allocateArray(Native Method)
! at org.bytedeco.javacpp.PointerPointer.<init>(PointerPointer.java:118)
! ... 21 common frames omitted
! Causing: java.lang.OutOfMemoryError: Cannot allocate new PointerPointer(4), totalBytes = 167141998, physicalBytes = 21169049600
! at org.bytedeco.javacpp.PointerPointer.<init>(PointerPointer.java:126)
! at org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(NativeOpExecutioner.java:517)
! at org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(NativeOpExecutioner.java:62)
! at org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.execAndReturn(DefaultOpExecutioner.java:210)
! at org.deeplearning4j.nn.layers.recurrent.LSTMHelpers.activateHelper(LSTMHelpers.java:165)
! at org.deeplearning4j.nn.layers.recurrent.GravesLSTM.activateHelper(GravesLSTM.java:147)
! at org.deeplearning4j.nn.layers.recurrent.GravesLSTM.rnnActivateUsingStoredState(GravesLSTM.java:203)
! at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.rnnActivateUsingStoredState(MultiLayerNetwork.java:2352)
! at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(MultiLayerNetwork.java:1870)
! at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:149)
! at org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:54)
! at org.deeplearning4j.optimize.Solver.optimize(Solver.java:51)
! at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.doTruncatedBPTT(MultiLayerNetwork.java:1245)
! at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:1079)
! at org.deeplearning4j.arbiter.task.MultiLayerNetworkTaskCreator$DL4JLearningTask.call(MultiLayerNetworkTaskCreator.java:132)
! at org.deeplearning4j.arbiter.task.MultiLayerNetworkTaskCreator$DL4JLearningTask.call(MultiLayerNetworkTaskCreator.java:68)
! at com.google.common.util.concurrent.TrustedListenableFutureTask$TrustedFutureInterruptibleTask.runInterruptibly(TrustedListenableFutureTask.java:108)
! at com.google.common.util.concurrent.InterruptibleTask.run(InterruptibleTask.java:41)
! at com.google.common.util.concurrent.TrustedListenableFutureTask.run(TrustedListenableFutureTask.java:77)
! at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
! at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
! ... 1 common frames omitted
! Causing: java.util.concurrent.ExecutionException: java.lang.OutOfMemoryError: Cannot allocate new PointerPointer(4), totalBytes = 167141998, physicalBytes = 21169049600
! at com.google.common.util.concurrent.AbstractFuture.getDoneValue(AbstractFuture.java:476)
! at com.google.common.util.concurrent.AbstractFuture.get(AbstractFuture.java:357)
! at com.google.common.util.concurrent.AbstractFuture$TrustedFuture.get(AbstractFuture.java:84)
! at org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner.processReturnedTask(BaseOptimizationRunner.java:190)
! at org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner.execute(BaseOptimizationRunner.java:132)