Error an ILoopOutputLayer cannot be used to compute a shape tensor

Description

Our model is not able to run in TensorRT, I have tried both running in ORT with TensorrtExecutionProvider and using trtexec to convert it to a plan.

For compliance reason, I cannot share my full model, but I can build a mini one to repro my issue.

please check the model binary directly:
tiny_model.onnx (15.9 KB)
OR build from the script:
tiny_model_builder.py (1.1 KB)

  • Using ORT + TensorrtExecutionProvider reports error:

    Error Code 4: Internal Error ((Unnamed Layer* 23) [LoopOutput]: an ILoopOutputLayer cannot be used to compute a shape tensor)
    ORT_repro.py (690 Bytes)

  • Using trtexec --onnx=tiny_model.onnx --saveEngine=tiny_model.trt --memPoolSize=workspace:10000 --minShapes=input:1x1 --maxShapes=input:1x512 --optShapes=input:1x64 --device=0 --verbose will show below error:
    [02/21/2023-14:36:04] [E] Error[2]: [topSort.cpp::trivialChoice::314] Error Code 2: Internal Error (Assertion c != kNoColor failed. )
    [02/21/2023-14:36:04] [E] Error[2]: [builder.cpp::buildSerializedNetwork::738] Error Code 2: Internal Error (Assertion engine != nullptr failed. )

Environment

TensorRT Version: 8.5.0
GPU Type: T4
Nvidia Driver Version: 470.161.03
CUDA Version: 11.8
CUDNN Version:
Operating System + Version: Ubuntu20.04
Python Version (if applicable):
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):

Relevant Files

Please attach or include links to any models, data, files, or scripts necessary to reproduce your issue. (Github repo, Google Drive, Dropbox, etc.)

Steps To Reproduce

Please include:

  • Exact steps/commands to build your repro
  • Exact steps/commands to run your repro
  • Full traceback of errors encountered

Hi @niuzheng168 ,
Apologies for the delayed response.
Can you please share the verbose logs with us, meanwhile we are trying to reproduce the issue from our end.

Thanks