I would like to convert an .etlt model into an .engine using tlt-converter and without using any kind of dockers, however I’m having a bunch of issues…
I’m working on a x86 machine with CUDA 11.4 and TensorRT 8.2.4
This configuration is not included in the table shown here ( TensorRT — Transfer Learning Toolkit 3.0 documentation ).
So I do not know what I’m supposed to do … Is it even possible to infer the models without docker ?
Could anyone help ?
Yes. it is possible.
For tao-converter, could you use https://developer.nvidia.com/cuda112-cudnn80-trt72 ?
Already tried, I get the following error :
error while loading shared libraries: libnvinfer.so.7: cannot open shared object file: No such file or directory
However that’s because my version of TensorRT is 8.2.4 and not 7.x.x
You can copy the converter from the docker.
The location is as below.
root@f2e487b0b17a:/workspace# which converter
There is no update from you for a period, assuming this is not an issue anymore.
Hence we are closing this topic. If need further support, please open a new one.
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