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[FEATURE] Rocm support for AMDGPU's / NCNN conversion for all GPU's #69

Description

@EmersonBiggons

Problem Statement

Support for onnxruntime-gpu exists but is exclusively for NVIDIA. The vast majority use AMD but there is no rocm support through use of onnxruntime-rocm. My CPU isn't bad, it's a 5800x but even doing a modest sized ePub file or text it takes hours. But if a GPU could be used instead then it can run real-time and potentially make even 500k word ePubs or longer take less than an hour.

Proposed Solution

  • Rocm support for GPU accelleration

Alternative Solutions

  • NCNN model conversion

Making an NCNN conversion of the model could work, I've seen it done on other AI models so it should be possible. NCNN has worked on my AMD GPU before so it could work as (AMD/intel) opensource-driver version.

User Impact

GPU acceleration on AMD GPU's which is 90% of the Linux user base.

Implementation Ideas

Theoretically it should be exactly the same as the process for NVIDIA (onnxruntime-gpu) but you use onnxruntime-rocm instead. You can even set the py project dependency line to have "kokoro-onnx[gpu]==0.3.9" be "kokoro-onnx[rocm]==0.3.9" instead.

You could even have the [gpu] part just detect if you have cuda or rocm installed and use that as a possible reference? But I am not sure.

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