Hello fellow developers,
I am currently developing an application involving machine learning models, specifically CoreML models, and I have encountered an intriguing issue that I am hoping to get some insights on.
In my current scenario, I'm planning to create a simple application with minimal UI, possibly using PyQT or similar tools. Therefore, I'm seeking a way to utilize NeuralEngine and GPU for CoreML model inference in Python. I discovered the 'predict' API in CoreMLTools which allows for model inference, but I'm unsure if its performance is on par with that of a properly built MacOS application using Swift and Neural Engine.
Can anyone provide insights into whether there's a considerable difference in inference performance between these two methods? Is the performance of CoreMLTools 'predict' API comparable to that of a full-fledged Swift MacOS application leveraging the Neural Engine?
Any clarification or guidance on this matter would be greatly appreciated. Thanks!