Yes I am using BYOM.
I am hoping to pick up the BYOM project which I had already started when a series of error messages led me to reach out to you for guidance. However if there is something wrong with my resnet50 model I realise that I may need to begin the exercise again.
The resnet_50 hdf5 file from ngc is not an onnx model or pytorch model. We do not need to run BYOM against it.
BYOM is a Python-based package that converts any open-source ONNX model to a TAO-comaptible model. The TAO BYOM Converter provides a CLI to import an ONNX model and convert it to Keras. The converted model is stored in .tltb format, which is based on EFF.
If you want to run classification with resnet_50 hdf5 file from ngc, there is another notebook under classification folder. You can refer to it. The resnet_50.hdf5 file can be loaded as pretrained weights directly.
In previous TAO versions, only tao_voc is available because the BYOM feature is not available.
Since BYOM is available for classification in latest TAO 22.05, so we make a new notebook(BYOM_voc) for end user to get familiar with BYOM in classification.