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Custom rocm hip and c++ extensions
🚀 The feature, motivation and pitch
Dear PyTorch developers and community,
We have nice tutorial cpp_extension on custom cuda extensions written by Peter Goldsborough. I’m wondering if the same can be done but on AMD GPUs with kernels written using rocm HIP. I mean the following: call custom forward+backward hip kernel from pytorch and include it in deep learning pipeline. Is it currently supported and are there any limitations?
Does somebody have experience of writing custom hip/c++ kernels and using them in pytorch?
cc @sekyondaMeta @svekars @carljparker @NicolasHug @kit1980 @subramen @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport
@jeffdaily We have some internal documentation that highlights some of the differences in enabling PyTorch extensions for ROCm. Shall I put that together into something we can publish on the pytorch documentation?
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