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avfilter/dnn_backend_torch: add CUDA/ROCm device support

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Add support for CUDA and ROCm (AMD GPU) devices in the LibTorch DNN
backend.

This works for both NVIDIA CUDA and AMD ROCm, as PyTorch exposes ROCm
through the CUDA-compatible API.

Usage:

./ffmpeg -i input.mp4 -vf scale=224:224,format=rgb24,dnn_processing=dnn_backend=torch:model=sr_model_torch.pt:device=cuda output.mp4

Reviewed-by: Guo Yejun <yejun.guo@intel.com>
Signed-off-by: younengxiao <steven.xiao@amd.com>
This commit is contained in:
stevxiao
2026-03-21 16:25:40 +08:00
committed by Guo Yejun
co-authored by Guo Yejun
parent 924cc51ffe
commit a077da895b
1 changed files with 7 additions and 0 deletions
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libavfilter/dnn/dnn_backend_torch.cpp
+7
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@@ -439,6 +439,13 @@ static DNNModel *dnn_load_model_th(DnnContext *ctx, DNNFunctionType func_type, A
#else
at::detail::getXPUHooks().initXPU();
#endif
} else if (device.is_cuda()) {
// CUDA device - works for both NVIDIA CUDA and AMD ROCm (which uses CUDA-compatible API)
if (!torch::cuda::is_available()) {
av_log(ctx, AV_LOG_ERROR, "CUDA/ROCm is not available\n");
goto fail;
}
av_log(ctx, AV_LOG_INFO, "Using CUDA/ROCm device: %s\n", device_name);
} else if (!device.is_cpu()) {
av_log(ctx, AV_LOG_ERROR, "Not supported device:\"%s\"\n", device_name);
goto fail;