To run data/models on an Apple Silicon GPU, use the PyTorch device name 'mps' with. Note: See more on running MPS as a backend in the PyTorch documentation.ġ1. Is MPS (Metal Performance Shader) built? True If it all worked, you should see something like: PyTorch version: 1.12.0 Print(f'PyTorch version: ')ĭevice = 'mps' if _available() else 'cpu' Create a new notebook by 'New' -> 'Notebook: Python 3 (ipykernel)' and run the following code to verfiy all the dependencies are available and check PyTorch version/GPU access. conda install jupyter pandas numpy matplotlib scikit-learn tqdmġ0. This will install the following: Installing collected packages: urllib3, typing-extensions, pillow, numpy, idna, charset-normalizer, certifi, torch, requests, torchvision, torchaudioĨ. pip3 install torch torchvision torchaudio Install PyTorch 1.12.0+ default version for Mac with pip from the PyTorch getting started page. Note: Python 3.8 is the most stable for using the following setup. Create a directory to setup a PyTorch environment. Sh ~/Downloads/Miniforge3-MacOSX-arm64.shĥ.

Open Terminal and run these commands to install Miniforge3 into home directory.Ĭhmod +x ~/Downloads/Miniforge3-MacOSX-arm64.sh.Download Miniforge3 (Conda installer) for macOS arm64 chips (M1, M1 Pro, M1 Max, M1 Ultra, M2).Follow the steps it prompts you to go through after installation. macOS 12.3+ (PyTorch will work on previous versions but the GPU on your Mac won't get used, this means slower code).PyTorch 1.12.0+ (v1.12.0 is the minimum PyTorch version for running accelerated training on Mac).Apple Silicon Mac (M1, M2, M1 Pro, M1 Max, M1 Ultra, etc).Setup a machine learning environment with PyTorch on Mac (short version) Note: As of June 30 2022, accelerated PyTorch for Mac (PyTorch using the Apple Silicon GPU) is still in beta, so expect some rough edges. See the video walkthrough version of this article on YouTube:.Want to set up TensorFlow? See my article for setting up TensorFlow on Mac.Got a problem? Create an issue on GitHub.We'll also be getting PyTorch to run on the Apple Silicon GPU for (hopefully) faster computing. This blog post: Helps you install various software tools such as Homebrew and Miniforge3 to use to install various data science and machine learning tools such as PyTorch. You: Have an Apple Silicon Mac (any of the M1 or M2 chip variants) and would like to set it up for data science and machine learning. 8 min read PyTorch can now leverage the Apple Silicon GPU for accelerated training.

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