Instructions to use rowandwhelan/tensorrt-emblayernorm-cuseqlens-oob-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use rowandwhelan/tensorrt-emblayernorm-cuseqlens-oob-poc with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
TensorRT EmbLayerNorm cumulative-sequence write PoC
This repository contains a benign reproduction for unchecked cu_seqlens values in TensorRT's current variable-sequence EmbLayerNorm v4 and v5 plugins.
The local proof writes synthetic values into controlled CUDA guard space. The Triton proof changes only a synthetic co-resident victim model's numeric output. It does not execute code or access real user data.
See REPORT.md for the technical write-up and triton_repeatability.txt for three fresh-server runs.
Reproduce
Local TensorRT proof:
python make_engine.py
python run_probe.py emb_cuseqlens_hface_fp16.engine
Triton service proof (after adapting start_triton.sh to the local Triton installation if necessary):
bash start_triton.sh
python triton_probe.py load
python triton_probe.py race 20 50
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