Passing CuPy CUDA device pointer to pybind11

I am trying to instantiate an array in GPU memory using CuPy and then pass the pointer to this array to C++ using pybind11.

A minimal example of the problem I am running into is shown below.

Python

import demolib #compiled pybind11 library
import cupy as cp

x = cp.ones(100000)
y = cp.ones(100000)

demolib.pyadd(len(x),x.data.ptr,y.data.ptr)

C++/CUDA

#include <iostream>
#include <math.h>
#include <cuda_runtime.h>
#include <pybind11/pybind11.h>
#include <pybind11/numpy.h>

namespace py = pybind11;

// Error Checking Function
#define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort=true)
{
   if (code != cudaSuccess)
   {
      fprintf(stderr,"GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
      if (abort) exit(code);
   }
}

// Simple CUDA kernel
__global__
void cuadd(int n, float *x, float *y)
{
  int index = blockIdx.x * blockDim.x + threadIdx.x;
  int stride = blockDim.x * gridDim.x;
  for (int i = index; i < n; i += stride)
    y[i] = x[i] + y[i];
}

// Simple wrapper function to be exposed to Python
int pyadd(int N, float *x, float *y)
{

  // Run kernel on 1M elements on the GPU
  int blockSize = 256;
  int numBlocks = (N + blockSize - 1) / blockSize;
  cuadd<<<numBlocks, blockSize>>>(N,x,y);

  // Wait for GPU to finish before accessing on host
  gpuErrchk( cudaPeekAtLastError() );
  gpuErrchk( cudaDeviceSynchronize() );

  return 0;
}

PYBIND11_MODULE(demolib, m) {
        m.doc() = "pybind11 example plugin"; // optional module docstring
        m.def("pyadd", &pyadd, "A function which adds two numbers");
}

The code throws the following error:

GPUassert: an illegal memory access was encountered /home/tbm/cuda/add_pybind.cu 47

I realize that this specific example could be implemented using a cupy user defined kernel, but the end goal is to be able to do zero-copy passes of cupy arrays into a larger codebase which would be prohibitive to rewrite in this paradigm.

I have also located this GitHub Issue, which is the the reverse of what I'm trying to do.