Can I create a TRT runtime engine (serialized) using the python API and then use then use this same engine (so deserialzed it + infer) to perform an inference using the C++ API?
Environment
TensorRT Version: 7.1 GPU Type: Xavier Nvidia Driver Version: 460 CUDA Version: CUDNN Version: Operating System + Version: ubuntu 18.04 Python Version (if applicable): TensorFlow Version (if applicable): PyTorch Version (if applicable): Baremetal or Container (if container which image + tag):
Ok thanks for sharing this documentation. Actually, I didn’t really find an answer to my question inside.
My concerns is: I have already generated an .engine file using the python API. Is it possible to deserialize this .engine file using the C++ API and use this deserialized engine to perform the inference using the C++ API ? Or for using an .engine file with the C++ API, should I also generate the .engine file using the C++ API?