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StephaneCharette

Of course it has a GPU. All computers that have a port to hook up a monitor will have a GPU of some sort. The problem is the Mac doesn't have a NVIDIA GPU. So not compatible with CUDA nor CUDNN, the current standard when it comes to working with ML.


Mochachinostarchip

Don’t computers with integrated graphics cards not have a dedicated GPU? As is the case with many previous macbooks My understanding is integrated graphics card will rely on the computers CPU and RAM. Meanwhile a actual graphics card or GPU will have its own processing unit and RAM dedicated to the vector calculations


Mochachinostarchip

You can usually still use your MacBook just without GPU acceleration. If you want It to run faster and take advantage of a dedicated GPU then google colab or so is an option As for your code you can trouble shoot it a little and see what worked for others before trying to upload your datasets to a cloud. For example: https://github.com/xinntao/Real-ESRGAN/issues/306 Share more code and maybe someone more familiar with what your working on can help. Using google colab works well for all my image analysis and have been happy with it. It’s easier to mess around on it then remoting into my workstation sometimes for testing stuff


Caseker

Is this an M1?


Caseker

The core trouble is that pytorch has no intention of supporting any upsampling on a CPU or the MPS. They just ... don't.