Getting TensorFlow install on Apple M1

I am getting started into Astroomy datasets. One of the first things I wanted to do is get adjusted and acquainted with TensorFlow. Since I have an Apple M1, I wanted to get tensorflow installed and using the integrated libraries so when the datasets are written, they are more native using the Apple Metal framework.

Here are the scratch notes.

1. Install Xcode Command Line Tools
2. Install Miniforge
3. Install Tensorflow 2.5 and its dependencies
4. Install Jupyter Notebook, Pandas
5. Run a Benchmark by training the MNIST dataset

Step 1: I have already installed Xcode Command Line Tools on my mac. If it’s not already installed in your system, you can install it by running the following command below in your terminal.

xcode-select --install

Step 2. Install Miniforge

Install miniforge for arm64 (Apple Silicon) from miniforge GitHub.

Miniforge enables installing python packages natively compiled for Apple Silicon.

After the installation of miniforge, by default, it gives us one base environment. You can turn off the default base env by running

conda config --set auto_activate_base true

Step 3. Installing Tensorflow-MacOS

Install the Tensorflow dependencies:

conda install -c apple tensorflow-deps

Install base TensorFlow:

pip install tensorflow-macos

Install metal plugin:

pip install tensorflow-metal

Step 4. Install Jupyter Notebook & Pandas

conda install -c conda-forge -y pandas jupyter

Step 5. Run a Benchmark by training the MNIST dataset

Let’s install Tensorflow Datasets

pip install tensorflow_datasets

Make sure conda environment is activated.

In your terminal run

jupyter notebook

It will open a browser window

Create a new python3 notebook

Let’s first import TensorFlow and check

import tensorflow as tfprint("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))

Let’s run a benchmark
I got the code snippet from TensorFlow Issues

Copy and paste code below in the new notebook

Examine the results.