🐛 [Bug] Encountered bug when using Torch-TensorRT Performance gap between ONNIX-TRT and Torch-TRT for Vision Models
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bug
story: Performance & Benchmarking
- Dominant language
- Python
- Stars
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- Merged PRs (30d)
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Description
Bug Description
To Reproduce
Steps to reproduce the behavior:
Expected behavior
Environment
Build information about Torch-TensorRT can be found by turning on debug messages
- Torch-TensorRT Version (e.g. 1.0.0):
- PyTorch Version (e.g. 1.0):
- CPU Architecture:
- OS (e.g., Linux):
- How you installed PyTorch (
conda,pip,libtorch, source): - Build command you used (if compiling from source):
- Are you using local sources or building from archives:
- Python version:
- CUDA version:
- GPU models and configuration:
- Any other relevant information:
Additional context
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by filling in the missing reproduction steps, performance measurements, model details, and environment information requested in the issue template. Compare the ONNX-TRT and Torch-TRT results for the same vision model; this issue is ready when the performance gap is reproducible and its scope or cause is documented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pytorch
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100