Running environment with following details:
Python: 3.11.4 | packaged by Anaconda, Inc. | (main, Jul 5 2023, 13:38:37) [MSC v.1916 64 bit (AMD64)]
I am trying to profile and deploy a simple TensorFlow SVC (Support Vector Classifier) using the following command:
profile = ei.model.profile(model = model, device = ‘cortex-m4f-80mhz’)
And the resulting debug output from Edge Impulse using Spyder 5.4.3 is:
edgeimpulse.exceptions.InvalidModelException: Was unable to load_model of type <class ‘sklearn.svm._classes.SVC’> with exception Unexpected model type
I am not sure where my mistake is. Please help!
Edge Impulse does not support support vector machines (SVM) at this time. Only TFLite operations for neural networks are supported. If you are looking to deploy to a microcontroller, only a subset of those operations are supported (for a reference, please see this documentation).
Thank you Shawn for the quick response. It is most appreciated.
Any idea if there any converters out there that can take an TensorFlow SVC and provide C/C++ code (deploy) as well as show RAM/FLASH/Inference Execution time (profile)? Thank you again.
I do not off the top of my head, but Google turned up some results that might be useful:
Thank you Shawn. I have looked through those provided links before, but thank you nonetheless.