Hi, I am deploying LPR model downloaded from NGC in python. When I load the engine trt_engine = load_engine(trt_runtime, trt_engine_path) it says: [TensorRT] ERROR: myelin/myelinGraphContext.h (26) - Myelin Error in MyelinGraphContext: 66 (myelinBinaryVersionMismatch : myelinGraphDeserializeBinar…

I cannot reproduce the error. My steps are as below. Can you double check again? Step: $ tlt lprnet run /bin/bash root@32b0be3ea045:/workspace/demo_2.0/lprnet# wget https://api.ngc.nvidia.com/v2/models/nvidia/tlt_lprnet/versions/deployable_v1.0/files/us_lprnet_baseline18_deployable.etlt root@32b…

You mention that you run everything in the container. Which container did you run?

The .etlt file is converted in the tlt container nvcr.io/nvidia/tlt-streamanalytics:v3.0-dp-py3 I deploy the .trt file in the tensorRT20.10 container nvcr.io/nvidia/tensorrt:20.10-py3

Please generate .trt file directly inside the tensorRT20.10 container. Firstly, copy .etlt file to that container and then download the tlt-converter according to Overview — TAO Toolkit 3.22.05 documentation

I accept your advice and converter the .etlt file in the tensorRT20.10 container by ./tlt-converter -k nvidia_tlt -p image_input,1x3x48x96,4x3x48x96,16x3x48x96 ./us_lprnet_baseline18_deployable.etlt -t int8 -e ./lpr_us_onnx_int8.trt However, I found the model size is wrong when deploying the .trt.…

Yes, the same issue. My inference code is the same as Python run LPRNet with TensorRT . And I test the code with the LPD model (downloaded from the NGC and convertered using tlt-converter in the way as the processing of LPR model) to make sure the inference code works well.

Can you reproduce my issue? Is it the problem of the LPR model or the tlt-converter tool?

For LPR model, it is not based on TLT detectnet_v2. So, it is different from LPD model. See Overview — TAO Toolkit 3.22.05 documentation So, for the trt engine you have generated, please use official inference command to check firstly. See LPRNet — Transfer Learning Toolkit 3.0 documentation

I do inference in the tlt3.0 container and show the same error: Using TensorFlow backend. WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them. Using TensorFlow backend. 2021-04-30 06:55:59,865 [INFO] /usr/local/lib/python3.6/dist-pac…

[image] 3204657659: I am afraid that there is something wrong with the us_lprnet_baseline18_deployable.etlt downloaded from the NGC. wget https://api.ngc.nvidia.com/v2/models/nvidia/tlt_lprnet/versions/deployable_v1.0/files/us_lprnet_baseline18_deployable.etlt I do not think so. The etlt fi…

Can't load trt engine and throwing an instance of 'nvinfer1::MyelinError'

Accelerated Computing Intelligent Video Analytics TAO Toolkit

Morganh April 28, 2021, 4:09pm 7

So, can I say that you meet the same issue as Python run LPRNet with TensorRT ? What is your inference code?

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Can't load trt engine and throwing an instance of 'nvinfer1::MyelinError'

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