facebookresearch / facebookresearch/sonata
what is the best-practice of deploy?
- Dominant language
- Python
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- 795
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- 56
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Description
Hi thanks for this greak work.
If I want to deploy sonota/ point transformer to my NVIDIA CUDA device, what is the best practice and minimum requirements?
I see
- torch-scatter --find-links https://data.pyg.org/whl/torch-2.5.0+cu124.html
- git+https://github.com/Dao-AILab/flash-attention.git
- spconv-cu124
these packages used, so is it impossible to convert point transformer to something like JIT/onnx/tvm
Thank you
Contributor guide
Research direction
No file, test, or entry point is named. First clarify the supported NVIDIA CUDA requirements, deployment target, and whether JIT, ONNX, or TVM conversion is expected; done would be a documented, reproducible deployment path with minimum requirements and known limitations.
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Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100