Introduces a third hardware mode alongside CUDA and CPU: ROCm (AMD GPU).
AMD GPUs present as CUDA devices under PyTorch ROCm, so the existing GPU
path is reused with minimal changes — the main additions are wheel management,
device detection, and suppressing flash_attn (unsupported on ROCm).
- server/vibevoice_server.py: extend _resolve_device() to recognise 'rocm'
(auto-detected via torch.version.hip); add _torch_device() helper that maps
'rocm' → 'cuda' for all PyTorch API calls; apply GPU optimisations for both
cuda and rocm in _init_model(); always use sdpa on ROCm; propagate
_torch_device() to _load_voice_presets() map_location.
- server/start.sh: add --rocm flag; sync .venv-rocm with uv sync --no-sources
then replace torch with the ROCm 6.2 wheel via uv pip install; set
VIBEPOD_DEVICE=rocm for uvicorn.
- server/pyproject.toml: register pytorch-rocm62 index (explicit); add
.venv-rocm to ruff excludes.
- package.json: add dev:rocm and dev:server:rocm scripts.
- README.md: document ROCm mode, prerequisites (RX 6000+, ROCm 6.2+, Linux),
and new commands; expand CUDA vs CPU section to CUDA vs CPU vs ROCm.
https://claude.ai/code/session_0168pSswiaoEf6LEx6UQWfBu
Claude
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