XXX failure of TensorRT X.Y when running XXX on GPU XXX
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Description
Description
I get this this issue [08/31/2024-21:29:05] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +6, GPU +64, now:
Environment
TensorRT Version:8.5.2.2
NVIDIA GPU:Orin NX
NVIDIA Driver Version:
CUDA Version:11.4
CUDNN Version:
Operating System:Jetpack 5.1.2
Python Version (if applicable):
3.8
Tensorflow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if so, version):
Relevant Files
Model link:
Steps To Reproduce
Commands or scripts:
Have you tried the latest release?:
Can this model run on other frameworks? For example run ONNX model with ONNXRuntime (polygraphy run <model.onnx> --onnxrt):
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
No source file, test, model, command, or traceback is provided. Start by reproducing the reported TensorRT 8.5.2.2 behavior on an Orin NX with CUDA 11.4 and JetPack 5.1.2, then collect the missing commands and full error output; done means a minimal reproducible case and a confirmed resolution.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- embedded-iot, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100