Instead of using Anaconda, you will use MiniForge, a lightweight Python interpreter with full access to the Conda ecosystem.Ĭonda is an open source package and environment management system that runs on Windows, Mac OS and Linux.įor Apple Silicon machines, you can directly download the MinForge installer from: I have listed the steps in the following sections. Installing TensorFlow on your Apple Silicon Mac is straight-forward. Steps to install TensorFlow on Apple Silicon Mac Note that without the tensorflow-metal package, your TensorFlow code would be still be able to run on your Apple Silicon Mac, just that TensorFlow won't be able to leverage the GPU of the M1 or M2 (it can only use the CPU). Essentially, this means your TensorFlow code is now able to take advantage of the powerful GPU available in the new Apple Silicon. The Metal framework gives your app direct access to a device’s graphics processing unit (GPU). tensorflow-metal - a plugin to ensure that TensorFlow is able to run on Metal. tensorflow-deps - the dependencies to run Tensorflow on arm64, e.g.The tensorflow-macospackage relies on two other packages: You can learn more about the PluggableDevice API of TensorFlow from Using the PluggableDevice API of Tensorflow, Apple is able to translate TensorFlow operations to code that the GPU of the Apple Silicon (M1 and M2) can understand.
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