I have something different to say. First I agree that any serious works should be done on a workstation either a packed desktop or cloud server (with a A100 40GB/80GB conf). However, for prototyping or just playing models, mac with its large shared memory is excellent: there is not many laptops or even desktop gpu have more than 16 gb vram, meaning when you prototyping you are very much limited to batch size or smaller sized backbones. I have a m1 pro 32 gb, it can fit most of the models I want to play with. After I finished prototyping, I simply change the "device = 'mps' to 'cuda' and run it on cloud. I use pytorch mainly, i have encountered some issues with mps but nothing major. There are walkarounds.
I have something different to say. First I agree that any serious works should be done on a workstation either a packed desktop or cloud server (with a A100 40GB/80GB conf). However, for prototyping or just playing models, mac with its large shared memory is excellent: there is not many laptops or even desktop gpu have more than 16 gb vram, meaning when you prototyping you are very much limited to batch size or smaller sized backbones. I have a m1 pro 32 gb, it can fit most of the models I want to play with. After I finished prototyping, I simply change the "device = 'mps' to 'cuda' and run it on cloud. I use pytorch mainly, i have encountered some issues with mps but nothing major. There are walkarounds.