convert onnx to tensorrt failured. INetworkDefinition::addGridsample: Error Code 3: ApI Usage Error
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Module:ONNX
- Dominant language
- C++
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Description
Log
data = torch.ones((1, 1, 512, 32, 32), dtype=torch.float32)
grid = torch.ones((1, 512, 32, 32, 3), dtype=torch.float32).cuda()
res = torch.nn.functional.grid_sample(img, grid)
The ONNX model performs inference correctly, but conversion to TensorRT fails. The error indicates that the GridSample operator does not support 5D input format.
Environment
**Windows 11
TensorRT Version: 10.6.0.26
NVIDIA GPU: 4070TIs
CUDA Version: 12.8
CUDNN Version: 9
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 with the Python reproduction in the issue and inspect TensorRT's GridSample support and related conversion path for 5D inputs. Compare the ONNX behavior with TensorRT 10.6.0.26 using the provided environment details; done means the failure is resolved or the unsupported case is clearly documented with a verified result.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- ai-infra-agents, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100