# Error in link library

**URL:** https://community.konduit.ai/t/error-in-link-library/797
**Category:** SameDiff
**Created:** [August 19, 2020, 9:25am UTC](https://community.konduit.ai/t/error-in-link-library/797 "2020-08-19T09:25:34Z")
**Posts on this page:** 4
**Page:** 1

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### Author: ![Cpt\_Whittmann](https://avatars.discourse-cdn.com/v4/letter/c/e480ec/32.png) [@Cpt\_Whittmann](https://community.konduit.ai/u/Cpt_Whittmann)
#### Post date: [August 19, 2020, 9:25am UTC](https://community.konduit.ai/t/error-in-link-library/797/1 "2020-08-19T09:25:34Z")

</div>

libnd4jcpu.dylib+0x521c574] samediff:🎫:acquiredThreads(unsigned int)+0x4

I intemittently get this problematic frame as the error with no other real information on whats caused the error. I am not using SameDiff directly.

Anyone any ideas what this is pointing to?

Many thanks.

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<div class="post-metadata">

### Author: ![agibsonccc](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/agibsonccc/32/697_2.png) [@agibsonccc](https://community.konduit.ai/u/agibsonccc)
#### Post date: [August 27, 2020, 1:34am UTC](https://community.konduit.ai/t/error-in-link-library/797/2 "2020-08-27T01:34:27Z")

</div>

> [@Cpt\_Whittmann](#):
>
> Anyone any ideas what this is pointing

Hi @Cpt_Whittmann could you report more? Sorry this wasn’t really actionable.  
We’d need more input. Was there a particular method call that caused this?

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<div class="post-metadata">

### Author: ![Cpt\_Whittmann](https://avatars.discourse-cdn.com/v4/letter/c/e480ec/32.png) [@Cpt\_Whittmann](https://community.konduit.ai/u/Cpt_Whittmann)
#### Post date: [August 27, 2020, 1:11pm UTC](https://community.konduit.ai/t/error-in-link-library/797/3 "2020-08-27T13:11:51Z")

</div>

Hi,

I have setup a toy example with known regression approximation results that the network should produce quite easily. Mostly when i fit the network everything runs absolutely fine without any problems. Just occasionally my network runs into this same native error(and other associated ones) when fitting. Even if I change nothing and run the fit again quite often things work no problem.

I have been using the EarlyStopping mechanism and I have now taken this out as I have had problems with it regards scheduled learning rates. Ill test to see if this maybe the cause of the error.

Below are some error log files (stacktrace only):

**1.**

C [libnd4jcpu.dylib+0x521c574] \_ZN8samediff6Ticket15acquiredThreadsEj+0x4  
C [libnd4jcpu.dylib+0x5218064] \_ZN8samediff10ThreadPool10tryAcquireEi+0xb4  
C [libnd4jcpu.dylib+0x521ab69] \_ZN8samediff7Threads11parallel\_doENSt3\_\_18functionIFvyyEEEy+0x39  
C [libnd4jcpu.dylib+0xf2a8] _ZN19NativeOpExecutioner19execTransformStrictEPN2sd13LaunchContextEiPKvPKxS4\_S6\_PvS6\_S7\_S6\_S7\_S6\_S6_+0x198  
C [libnd4jcpu.dylib+0x2a7d9] execTransformStrict+0x99  
C [libjnind4jcpu.dylib+0x11a47e] Java\_org\_nd4j\_nativeblas\_Nd4jCpu\_execTransformStrict\_\_Lorg\_bytedeco\_javacpp\_PointerPointer\_2ILorg\_nd4j\_nativeblas\_OpaqueDataBuffer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_nd4j\_nativeblas\_OpaqueDataBuffer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_bytedeco\_javacpp\_Pointer\_2+0x36e  
j org.nd4j.nativeblas.Nd4jCpu.execTransformStrict(Lorg/bytedeco/javacpp/PointerPointer;ILorg/nd4j/nativeblas/OpaqueDataBuffer;Lorg/bytedeco/javacpp/LongPointer;Lorg/bytedeco/javacpp/LongPointer;Lorg/nd4j/nativeblas/OpaqueDataBuffer;Lorg/bytedeco/javacpp/LongPointer;Lorg/bytedeco/javacpp/LongPointer;Lorg/bytedeco/javacpp/Pointer;)V+0  
J 4334 c1 org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(Lorg/nd4j/linalg/api/ops/TransformOp;Lorg/nd4j/linalg/api/ops/OpContext;)V (1440 bytes) @ 0x000000010fe6befc [0x000000010fe5e060+0x000000000000de9c]  
J 4331 c1 org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(Lorg/nd4j/linalg/api/ops/Op;Lorg/nd4j/linalg/api/ops/OpContext;)Lorg/nd4j/linalg/api/ndarray/INDArray; (143 bytes) @ 0x000000010fe5a95c [0x000000010fe59860+0x00000000000010fc]  
J 4330 c1 org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(Lorg/nd4j/linalg/api/ops/Op;)Lorg/nd4j/linalg/api/ndarray/INDArray; (7 bytes) @ 0x000000010fe593dc [0x000000010fe59340+0x000000000000009c]  
j org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.execAndReturn(Lorg/nd4j/linalg/api/ops/TransformOp;)Lorg/nd4j/linalg/api/ops/TransformOp;+2  
j org.nd4j.linalg.activations.impl.ActivationTanH.getActivation(Lorg/nd4j/linalg/api/ndarray/INDArray;Z)Lorg/nd4j/linalg/api/ndarray/INDArray;+11  
j org.deeplearning4j.nn.layers.BaseLayer.activate(ZLorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/linalg/api/ndarray/INDArray;+16  
j org.deeplearning4j.nn.layers.AbstractLayer.activate(Lorg/nd4j/linalg/api/ndarray/INDArray;ZLorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/linalg/api/ndarray/INDArray;+9  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.ffToLayerActivationsInWs(ILorg/deeplearning4j/nn/api/FwdPassType;ZLorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;)Ljava/util/List;+383  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore()V+238  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)V+1  
j org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/common/primitives/Pair;+13  
j org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Z+85  
j org.deeplearning4j.optimize.Solver.optimize(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)V+9  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fitHelper(Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;)V+287  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;)V+6  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(Lorg/nd4j/linalg/dataset/api/DataSet;)V+25  
j org.deeplearning4j.parallelism.trainer.DefaultTrainer.fit(Lorg/nd4j/linalg/dataset/api/DataSet;)V+64  
j org.deeplearning4j.parallelism.trainer.DefaultTrainer.run()V+643  
j java.util.concurrent.ThreadPoolExecutor.runWorker(Ljava/util/concurrent/ThreadPoolExecutor$Worker;)V+92 java.base@13.0.1  
j java.util.concurrent.ThreadPoolExecutor$Worker.run()V+5 java.base@13.0.1  
j org.deeplearning4j.parallelism.ParallelWrapper$2$1.run()V+28  
j java.lang.Thread.run()V+11 java.base@13.0.1

**2.**  
C [libnd4jcpu.dylib+0x521c574] samediff:🎫:acquiredThreads(unsigned int)+0x4  
C [libnd4jcpu.dylib+0x5218064] samediff::ThreadPool::tryAcquire(int)+0xb4  
C [libnd4jcpu.dylib+0x521ab69] samediff::Threads::parallel\_do(std::\_\_1::function\<void (unsigned long long, unsigned long long)\>, unsigned long long)+0x39  
C [libnd4jcpu.dylib+0xec28] NativeOpExecutioner::execTransformAny(sd::LaunchContext\*, int, void const\*, long long const\*, void const\*, long long const\*, void\*, long long const\*, void\*, long long const\*, void\*, long long const\*, long long const\*, bool)+0x258  
C [libnd4jcpu.dylib+0x2a6b1] execTransformAny+0xa1  
C [libjnind4jcpu.dylib+0x11966e] Java\_org\_nd4j\_nativeblas\_Nd4jCpu\_execTransformAny\_\_Lorg\_bytedeco\_javacpp\_PointerPointer\_2ILorg\_nd4j\_nativeblas\_OpaqueDataBuffer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_nd4j\_nativeblas\_OpaqueDataBuffer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_bytedeco\_javacpp\_LongPointer\_2Lorg\_bytedeco\_javacpp\_Pointer\_2+0x36e  
j org.nd4j.nativeblas.Nd4jCpu.execTransformAny(Lorg/bytedeco/javacpp/PointerPointer;ILorg/nd4j/nativeblas/OpaqueDataBuffer;Lorg/bytedeco/javacpp/LongPointer;Lorg/bytedeco/javacpp/LongPointer;Lorg/nd4j/nativeblas/OpaqueDataBuffer;Lorg/bytedeco/javacpp/LongPointer;Lorg/bytedeco/javacpp/LongPointer;Lorg/bytedeco/javacpp/Pointer;)V+0  
J 4097 c1 org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(Lorg/nd4j/linalg/api/ops/TransformOp;Lorg/nd4j/linalg/api/ops/OpContext;)V (1440 bytes) @ 0x000000010e451aec [0x000000010e44d960+0x000000000000418c]  
J 3876 c1 org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(Lorg/nd4j/linalg/api/ops/Op;Lorg/nd4j/linalg/api/ops/OpContext;)Lorg/nd4j/linalg/api/ndarray/INDArray; (143 bytes) @ 0x000000010e407d7c [0x000000010e4077e0+0x000000000000059c]  
J 3875 c1 org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(Lorg/nd4j/linalg/api/ops/Op;)Lorg/nd4j/linalg/api/ndarray/INDArray; (7 bytes) @ 0x000000010e4073c4 [0x000000010e407340+0x0000000000000084]  
J 4092 c1 org.nd4j.linalg.api.ndarray.BaseNDArray.assign(Lorg/nd4j/linalg/api/ndarray/INDArray;)Lorg/nd4j/linalg/api/ndarray/INDArray; (104 bytes) @ 0x000000010e44aaac [0x000000010e44a3e0+0x00000000000006cc]  
j org.nd4j.linalg.api.ndarray.BaseNDArray.mmuli(Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;)Lorg/nd4j/linalg/api/ndarray/INDArray;+475  
j org.deeplearning4j.nn.layers.BaseLayer.preOutputWithPreNorm(ZZLorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/common/primitives/Pair;+305  
j org.deeplearning4j.nn.layers.BaseLayer.preOutput(ZLorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/linalg/api/ndarray/INDArray;+4  
j org.deeplearning4j.nn.layers.BaseOutputLayer.preOutput2d(ZLorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/linalg/api/ndarray/INDArray;+3  
j org.deeplearning4j.nn.layers.BaseOutputLayer.backpropGradient(Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/common/primitives/Pair;+9  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.calcBackpropGradients(Lorg/nd4j/linalg/api/ndarray/INDArray;ZZZ)Lorg/nd4j/common/primitives/Pair;+708  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore()V+384  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)V+1  
j org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Lorg/nd4j/common/primitives/Pair;+13  
j org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)Z+85  
j org.deeplearning4j.optimize.Solver.optimize(Lorg/deeplearning4j/nn/workspace/LayerWorkspaceMgr;)V+9  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fitHelper(Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;)V+287  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;Lorg/nd4j/linalg/api/ndarray/INDArray;)V+6  
j org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(Lorg/nd4j/linalg/dataset/api/DataSet;)V+25  
j org.deeplearning4j.parallelism.trainer.DefaultTrainer.fit(Lorg/nd4j/linalg/dataset/api/DataSet;)V+64  
j org.deeplearning4j.parallelism.trainer.DefaultTrainer.run()V+643  
j java.util.concurrent.ThreadPoolExecutor.runWorker(Ljava/util/concurrent/ThreadPoolExecutor$Worker;)V+92 java.base@13.0.1  
j java.util.concurrent.ThreadPoolExecutor$Worker.run()V+5 java.base@13.0.1  
j org.deeplearning4j.parallelism.ParallelWrapper$2$1.run()V+28  
j java.lang.Thread.run()V+11 java.base@13.0.1

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<div class="post-metadata">

### Author: ![agibsonccc](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/agibsonccc/32/697_2.png) [@agibsonccc](https://community.konduit.ai/u/agibsonccc)
#### Post date: [August 29, 2020, 12:04pm UTC](https://community.konduit.ai/t/error-in-link-library/797/4 "2020-08-29T12:04:58Z")

</div>

Sorry, still need more than this. Would you mind giving me a code snippet that reproduces this? Thanks!
