9/12/2023 0 Comments Metal gpu mac![]() ![]() We have to install the following pip packages: tensorflow-macos and tensorflow-metal. We then activate the environment conda activate tf-metal Install Metal enabled TensorFlow We first create a new conda environment named tf-metal with Python 3.8 conda create -n tf-metal python=3.8 I personally prefer miniconda, but other environment managers such as anaconda and virtualenv should also work in a similar fashion. In addition, I train a simple CNN image classifier on my MacBook Pro, equipped with an AMD Radeon Pro 560X, to demonstrate the accelerated performance. In this mini-guide, I will walk through how to install tensorflow-metal to enable dGPU training on Intel MacBook Pro and iMac. ![]() With the recent public release of macOS Monterey, Apple has added Metal support for the PluggableDevice architecture, hence, it is now possible to train TensorFlow models with the dedicated GPU (dGPU) on MacBook Pros and iMacs with ease (sort of). AMD ROCm port) and can purely focus on the communication layers between TensorFlow and device-level operations. More importantly, hardware manufacturers no longer have to fork and implement their own version of TensorFlow (e.g. This allows users to enjoy accelerated training on non-CUDA devices with minimal modification in their code. GPUs, TPUs, NPUs) into the TensorFlow ecosystem. TensorFlow introduced PluggableDevice in mid-2021 which enables hardware manufacturers to seamlessly integrate their accelerators (e.g. Photo by Nikolay Tarashchenko on Unsplash ![]()
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