I am working on Pose Estimation and I was thinking about trying to prune and quantize the 2 models I am using thanks to TLT.
So here’s the question: is there a way to import a tensorrt model to TLT as a pretrained model? Is there a way yo convert a model to the format .tlt?
Thanks in advance!
Could you please give an example of “a tensorrt model”?
I’ll be more specific, I am sorry if the question was malformed:
My objective is to prune the 2 models you can find over here: https://github.com/NVIDIA-AI-IOT/trt_pose
A densenet and a resnet. In that same link a utility called touch2trt manages the conversion from the format pytorch (.pth) to tensorflow.
I am trying to convert these models to then give them (one at a time) as input to tlt, specifying the path in a spec file. While trying to solve this I found out that all the pretrained models downloadable directly from tlt are in the hdf5 format.
Do I need to convert the 2 models mentioned above in said format to be able to read them inside tlt environment?
Thank you for the help!
Unfortunately these custom pre-trained models are not supported with TLT. With TLT you will have to use pre-trained weights from one of our models in ngc.
Hi Morganh, thank you for the answer!
I’m having trouble understanding your statement. So if I want to prune those 2 models using tlt-prune (because of its ease of use) there is NO WAY for me to import the models? What if I convert the pytorch files to hdf5?
Is the toolkit built to accept only what comes from NGC (maybe by doing a check or some cryptography) or is it possible for me to find a workaround by doing the right conversion??
I really need to shrink those models, pruning with TLT would be fantastic.
Thanks for your time
Those two models are not compatible with TLT process. In TLT training spec, user can set ngc models or tlt models as pretrained model.
Instead of NVIDIA provided pre-trained models, can I use TLT with my own or any open source pre-trained models?
No third party pre-trained models are supported by TLT. Only NVIDIA pre-trained models from NGC are currently supported which can be retrained with your custom data
For pruning, only tlt format model trained via TLT is accepted for the tool tlt-prune.