About BatchSize failure of TensorRT-8.0.1.6 when running trtexec tool on NVIDIA Jetson Xavier NX

[ThomasCai]

Description

Error Info (When I run /usr/src/tensorrt/bin/trtexec --loadEngine=XXX.engine --batch=40 --warmUp=200 --iterations=2000)

Error[3]: [executionContext.cpp::enqueue::276] Error Code 3: Internal Error (Parameter check failed at: runtime/api/executionContext.cpp::enqueue::276, condition: batchSize > 0 && batchSize <= mEngine.getMaxBatchSize(). Note: Batch size was: 40, but engine max batch size was: 1
)
[12/12/2023-21:35:03] [E] Error occurred during inference

Here is my script to convert the engine according to https://docs.nvidia.com/deeplearning/tensorrt/archives/tensorrt-801/quick-start-guide/index.html

/usr/src/tensorrt/bin/trtexec --onnx=${1} --saveEngine=${2}  --buildOnly --workspace=10240 --explicitBatch --minShapes=input:1x3x224x224 --optShapes=input:40x3x224x224 --maxShapes=input:40x3x224x224 --fp16

Note: By the way, my Jetson has a fixed version, so I have to solve it in this version. I look forward to your reply, thank you.

Environment

TensorRT Version: 8.0.1.6

NVIDIA GPU: NVIDIA Jetson Xavier NX

CUDA Version: 10.2

CUDNN Version: 8.2.1.32

Operating System: ubuntu18.04

Jetpack: 4.6-b199

[zerollzeng]

Use /usr/src/tensorrt/bin/trtexec --loadEngine=xx.engine --shapes=input:40x3x224x224, because you are using explicit shape.

[ThomasCai]

Use /usr/src/tensorrt/bin/trtexec --loadEngine=xx.engine --shapes=input:40x3x224x224, because you are using explicit shape.

Thank you~ I'll have a try.

[ttyio]

closing since no activity for more than 3 weeks per our policy, thanks all!