## Error: expression must have pointer-to-object type

I am trying to write my own CUDA function for pytorch according to @goldsborough tutorial: https://pytorch.org/tutorials/advanced/cpp_extension.html

I have to pass a 2D tensor `out_attribute`

to the kernel and access it’s values element wise:

```
template <typename scalar_t>
__global__ void sort_in_grid_forward_kernel(
const scalar_t* __restrict__ point_cloud,
scalar_t* __restrict__ out_attributes) {
const int i = (blockIdx.x * blockDim.x) + threadIdx.x;
const int j = (blockIdx.y * blockDim.y) + threadIdx.y;
// const int index = j*num_points +i;
if(i == j){
out_attributes[i][j]= -1;
}
else{
// ........... Do some processing with point cloud ....... //
out_attributes[i][j]= value;
}
}
at::Tensor sort_in_grid_forward(
at::Tensor point_cloud, //(2048, 3)
at::Tensor out_attributes //(2048, 2048)
) {
const dim3 threadsPerBlock(32, 32); // 1024 threads
const dim3 numBlocks(64,64);
AT_DISPATCH_FLOATING_TYPES(point_cloud.type(), "sort_in_grid_forward_cuda", ([&] {
sort_in_grid_forward_kernel<scalar_t><<<numBlocks, threadsPerBlock>>>(
point_cloud.data<scalar_t>(),
out_attributes.data<scalar_t>());
}));
return out_attributes;
}
```

I am having error on lines:

```
out_attributes[i][j]= -1;
out_attributes[i][j]= value;
```

Is there a easy way access the value of multi dimensional Tensor in kernel than to deal with memory allocations and pointer??

How can we convert ATen tensors to C++ STL vector and pass it to the kernel??