[C++ exception]: c10::Error at memory location

C++
1

Hi,

I’m trying to convert my network trained in Tensorflow to libtorch for inference. However, I run into this c++ exception:

Unhandled exception at 0x00007FFCA0F0A839 in Inference.exe: Microsoft C++ exception: c10::Error at memory location 0x000000E75FCFCFC0.

Here is a piece of code for testing:

#include <torch/torch.h>

using namespace torch;

struct ConvNet : nn::Module
{
    ConvNet()
        :conv1(nn::Conv2dOptions(2, 10, { 1 , 1 }).stride(1).padding(1).with_bias(true))
    {
        register_module("Conv1", conv1);
    }

    Tensor forward(Tensor input)
    {
        auto x = conv1->forward(input);  // <--- where exception happens.
        return x;
    }

    nn::Conv2d conv1{nullptr};
};

int main()
{
    Tensor input = torch::randn({ 2, 3, 3, 2 });
    input = input.cuda();
    std::cout << input << std::endl;

    std::shared_ptr<ConvNet> mNet = std::make_shared<ConvNet>();
    std::cout << mNet->forward(input) << std::endl;
    
    return 0;
}

Why did this happen? Could anyone help? Thx in advance!

2

Additional info:
OS: Windows 10
Libtorch: 1.3.1
CUDA: 10.1
cudnn: 7.6.5
VS: 2017

The memory layout in my code is NHWC. I just found that it only support NCHW format in libtorch. So, the updated code:

#include <torch/torch.h>

using namespace torch;

struct ConvNet : nn::Module
{
    ConvNet()
        :conv1(nn::Conv2dOptions(2, 10, { 1 , 1 }).stride(1).padding(0).with_bias(true))
    {
        register_module("Conv1", conv1);
    }

    Tensor forward(Tensor input)
    {
        auto x = conv1->forward(input);  // <--- where exception happens.
        return x;
    }

    nn::Conv2d conv1{nullptr};
};

int main()
{
    Tensor input = torch::randn({ 2, 2, 3, 3 });
    input = input.cuda();
    std::cout << input << std::endl;

    std::shared_ptr<ConvNet> mNet = std::make_shared<ConvNet>();
    std::cout << mNet->forward(input) << std::endl;
    
    return 0;
}

The exception still exists.

3

After some research and debugging work, I just figure out what’s wrong. Basically I forgot to make my network cuda enable. Just add one line of code and it works fine now. Source code:

#include <torch/torch.h>

using namespace torch;

struct ConvNet : nn::Module
{
    ConvNet()
        :conv1(nn::Conv2dOptions(2, 10, { 1 , 1 }).stride(1).padding(0).with_bias(true))
    {
        register_module("Conv1", conv1);
    }

    Tensor forward(Tensor input)
    {
        auto x = conv1->forward(input);  // <--- where exception happens.
        return x;
    }

    nn::Conv2d conv1{nullptr};
};

int main()
{
    Tensor input = torch::randn({ 2, 2, 3, 3 });
    input = input.cuda();
    std::cout << input << std::endl;

    std::shared_ptr<ConvNet> mNet = std::make_shared<ConvNet>();
    mNet->to(kCUDA);
    std::cout << mNet->forward(input) << std::endl;
    
    return 0;
}