Enable -Wunused-value in vision/PACKAGE +1

Summary:
This diff enables compilation warning flags for the directory in question. Further details are in [this workplace post](https://fb.workplace.com/permalink.php?story_fbid=pfbid02XaWNiCVk69r1ghfvDVpujB8Hr9Y61uDvNakxiZFa2jwiPHscVdEQwCBHrmWZSyMRl&id=100051201402394).

This is a low-risk diff. There are **no run-time effects** and the diff has already been observed to compile locally. **If the code compiles, it work; test errors are spurious.**

Differential Revision: D70282347

fbshipit-source-id: e2fa55c002d7124b13450c812165d244b8a53f4e
This commit is contained in:
Richard Barnes 2025-03-04 17:49:30 -08:00 committed by Facebook GitHub Bot
parent 20bd8b33f6
commit 7e09505538
2 changed files with 8 additions and 4 deletions

View File

@ -8,6 +8,7 @@
#ifdef WITH_CUDA
#include <ATen/cuda/CUDAContext.h>
#include <c10/cuda/CUDAException.h>
#include <cuda_runtime_api.h>
#endif
#include <torch/extension.h>
@ -33,13 +34,13 @@ torch::Tensor sphere_ids_from_result_info_nograd(
.contiguous();
if (forw_info.device().type() == c10::DeviceType::CUDA) {
#ifdef WITH_CUDA
cudaMemcpyAsync(
C10_CUDA_CHECK(cudaMemcpyAsync(
result.data_ptr(),
tmp.data_ptr(),
sizeof(uint32_t) * tmp.size(0) * tmp.size(1) * tmp.size(2) *
tmp.size(3),
cudaMemcpyDeviceToDevice,
at::cuda::getCurrentCUDAStream());
at::cuda::getCurrentCUDAStream()));
#else
throw std::runtime_error(
"Copy on CUDA device initiated but built "

View File

@ -7,6 +7,7 @@
*/
#ifdef WITH_CUDA
#include <c10/cuda/CUDAException.h>
#include <cuda_runtime_api.h>
namespace pulsar {
@ -17,7 +18,8 @@ void cudaDevToDev(
const void* src,
const int& size,
const cudaStream_t& stream) {
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToDevice, stream);
C10_CUDA_CHECK(
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToDevice, stream));
}
void cudaDevToHost(
@ -25,7 +27,8 @@ void cudaDevToHost(
const void* src,
const int& size,
const cudaStream_t& stream) {
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToHost, stream);
C10_CUDA_CHECK(
cudaMemcpyAsync(trg, src, size, cudaMemcpyDeviceToHost, stream));
}
} // namespace pytorch