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Save and Load Serialization. #67

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huynhvanvuong91 opened this issue Sep 23, 2017 · 7 comments
Closed

Save and Load Serialization. #67

huynhvanvuong91 opened this issue Sep 23, 2017 · 7 comments

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@huynhvanvuong91
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huynhvanvuong91 commented Sep 23, 2017

Current, I doing test program MnistDemo.GPU but when I Load file *.json them program error.
image

Please help me solution.

Thanks.

@huynhvanvuong91 huynhvanvuong91 changed the title Save and Load Save and Load Serialization. Sep 23, 2017
@cbovar
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cbovar commented Oct 4, 2017

I will look at that when I'll be back from holidays

cbovar added a commit that referenced this issue Oct 8, 2017
@cbovar
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cbovar commented Oct 8, 2017

Serialization tests should be made generic to detect such error earlier

@cbovar cbovar closed this as completed Oct 8, 2017
@Diapa
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Diapa commented Nov 19, 2017

I have this problem. How do I fix it? I installed with nuget and I use regressionlayer. The exception seems to come from

var t = Activator.CreateInstance(type, dico) as LayerBase<T>;

@cbovar
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cbovar commented Nov 20, 2017

Hi @Diapa ,
Could you try with the new nuget package (0.4.3) ?

@Diapa
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Diapa commented Nov 20, 2017

Yes it works now thank you, but using this version GPU doesn't work. I get the same problem, but only using GPU. Additionally I get an ArgumentNullException when adding a convolutional layer to the network (only GPU version). It comes from ConvNetSharp.Volume.GPU.Single.Volume.LoadKernels().

@cbovar
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cbovar commented Nov 21, 2017

Do you have a minimal code that reproduces this error?

@Diapa
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Diapa commented Nov 22, 2017

Maybe there's some problem with my CUDA/cudnn installation if you don't get this problem... But I was able to run GPU version with v0.4.2.

using ConvNetSharp.Core;
using ConvNetSharp.Core.Layers;
using ConvNetSharp.Volume.GPU.Single;

namespace m
{
    class Program
    {
        static void Main(string[] args)
        {
            BuilderInstance.Volume = new VolumeBuilder();

            Net<float> net = new Net<float>();
            net.AddLayer(new InputLayer<float>(20, 20, 3));
            net.AddLayer(new ConvLayer<float>(5, 5, 48)); //System.ArgumentNullException
            /*
            System.IO.StreamReader..ctor(Stream stream, Encoding encoding, Boolean detectEncodingFromByteOrderMarks, Int32 bufferSize, Boolean leaveOpen)
            System.IO.StreamReader..ctor(Stream stream)
            ConvNetSharp.Volume.GPU.KernelLoader`1.LoadKernel(String name, Stream stream)
            ConvNetSharp.Volume.GPU.Single.Volume.LoadKernels()
            ConvNetSharp.Volume.GPU.Single.VolumeBuilder.Random(Shape shape, Double mu, Double std)
            ConvNetSharp.Core.Layers.ConvLayer`1.UpdateOutputSize()
            ConvNetSharp.Core.Net`1.AddLayer(LayerBase`1 layer)
            [row 15 in this file]
            */
        }
    }
}

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