NVIDIA / NVIDIA/TensorRT

[graphShapeAnalyzer.cpp::checkCalculationStatusSanity::1916] Error Code 2: Internal Error (Assertion !isInFlight(p.second.symbolicRep) failed. )

Open
#4,126 2 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Module:ONNX triaged
Dominant language
C++
Stars
13.4k
Forks
2.4k
Avg merge
5d 3h
Merged PRs (30d)
2

Description

Description

Environment

TensorRT Version: 10.4.0.26-1+cuda12.6 (upgrading from 10.3)

NVIDIA GPU: V100

NVIDIA Driver Version:

CUDA Version:
Cuda compilation tools, release 12.5, V12.5.82
CUDNN Version: 9

Operating System:

Python Version (if applicable):

Tensorflow Version (if applicable):

PyTorch Version (if applicable):

Baremetal or Container (if so, version): nvidia/cuda:12.5.1-cudnn-devel-ubuntu20.04

Relevant Files

Model link:

Steps To Reproduce

Build onnxruntime

Commands or scripts:
In built directory
python onnxruntime_test_python_nested_control_flow_op.py

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

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Run onnxruntime_test_python_nested_control_flow_op.py from the built directory to reproduce the assertion, then inspect graphShapeAnalyzer.cpp around checkCalculationStatusSanity at line 1916. Determine why the nested control-flow test reaches the in-flight symbolic representation assertion; done means the test completes without the internal error.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp, python
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.