TensorFlow Setup on Apple Silicon Mac (M1, M1 Pro, M1 Max)

If you’re looking to get started with TensorFlow on your shiny new M1, M1 Pro, M1 Max, M1 Ultra, or M2 Mac, I’ve got you covered! 🚀 Here’s a simple step-by-step guide to get you up and running in no time(Github):

1. Download and install Homebrew from https://brew.sh (follow the instructions after installation).
2. Get Miniforge3, the Conda installer for macOS arm64 chips (M1, M1 Pro, M1 Max). You can download it [here](https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh).
3. Install Miniforge3 by running the following commands in Terminal:

chmod +x ~/Downloads/Miniforge3-MacOSX-arm64.sh
sh ~/Downloads/Miniforge3-MacOSX-arm64.sh
source ~/miniforge3/bin/activate

4. Restart Terminal.
5. Create a directory for your TensorFlow environment:

mkdir tensorflow-test
cd tensorflow-test

6. Set up a Conda environment and activate it:

conda create --prefix ./env python
conda activate ./env

7. Install TensorFlow dependencies from the Apple Conda channel:

conda install -c apple tensorflow-deps

8. Install base TensorFlow (Apple’s fork) and leverage Apple Metal for GPU acceleration:

python -m pip install tensorflow-macos
python -m pip install tensorflow-metal

9. (Optional) Install TensorFlow Datasets for running included benchmarks:

python -m pip install tensorflow-datasets

10. Install common data science packages:

conda install jupyter pandas numpy matplotlib scikit-learn

11. Launch Jupyter Notebook:

jupyter notebook

12. Import dependencies and check TensorFlow version/GPU access in the first cell:

import numpy as np
import pandas as pd
import sklearn
import tensorflow as tf
import matplotlib.pyplot as plt

# Check for TensorFlow GPU access
print(f"TensorFlow has access to the following devices:\n{tf.config.list_physical_devices()}")

# See TensorFlow version
print(f"TensorFlow version: {tf.__version__}")

13. If it all worked, you should see something like (Expected Output):

TensorFlow has access to the following devices:
[PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU'),
PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
TensorFlow version: 2.5.0

That’s it! You’re all set to dive into the exciting world of TensorFlow on your M1 Mac. Feel free to explore the provided notebooks and compare your results with the benchmarks. Happy coding! 💻🎉

For more detailed checkout this : Github

#TensorFlow #M1Mac #MachineLearning #AppleSilicon