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Workspaces/config are not independent between networks #4337

AlexDBlack opened this issue Nov 28, 2017 · 3 comments


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commented Nov 28, 2017

Note the scope panic exception on net2.output(...) - but net2 is configured to not use any workspaces...

    public void debug() {

        int depthIn = 2;
        int depthOut = 2;
        int nOut = 2;

        MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder().weightInit(WeightInit.XAVIER)
                .layer(0, new ConvolutionLayer.Builder().nIn(depthIn).nOut(depthOut).kernelSize(2, 2)
                        .stride(1, 1).activation(Activation.TANH).build())
                .layer(1, new OutputLayer.Builder(LossFunctions.LossFunction.MCXENT)

        MultiLayerNetwork net = new MultiLayerNetwork(conf.clone());

        MultiLayerNetwork net2 = new MultiLayerNetwork(conf.clone());

        INDArray in = Nd4j.rand(new int[]{1,2,5,5});

        net2.output(in);    //Op [add_scalar] X argument uses leaked workspace pointer from workspace [LOOP_EXTERNAL]

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commented Nov 28, 2017

Using this is very likely the fix - will implement + test soon.


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commented Nov 29, 2017

@AlexDBlack AlexDBlack closed this Nov 29, 2017


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commented Sep 24, 2018

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.

@lock lock bot locked and limited conversation to collaborators Sep 24, 2018

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