mrdbourke/m1-ml-setup.md

## m1-ml-setup.md

      
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              m1-ml-setup.md
            
          
    How to setup a TensorFlow environment on M1, M1 Pro, M1 Max using Miniforge

You: have a new M1, M1 Pro, M1 Max machine and would like to get started doing machine learning and data science on it.
This page: goes through a list of steps to install package managers and common machine learning and data science packages (software) on your machine and make sure they run using sample code.
Steps


Download and install Homebrew from https://brew.sh. Follow the steps it prompts you to go through after installed.
Download Miniforge3 (Conda installer) for macOS arm64 chips (M1, M1 Pro, M1 Max).
Install Miniforge3 into home directory.

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

Restart terminal.
Create directory to setup TensorFlow environment.

mkdir tensorflow-test
cd tensorflow-test

Make and activate Conda environment.

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

Install TensorFlow dependencies from Apple Conda channel.

conda install -c apple tensorflow-deps

Install base TensorFlow (Apple's fork of TensorFlow is called tensorflow-macos).

python -m pip install tensorflow-macos

Install Apple's tensorflow-metal to leverage Apple Metal (Apple's GPU framework) for M1, M1 Pro, M1 Max GPU acceleration.

python -m pip install tensorflow-metal

(Optional) Install TensorFlow Datasets to run benchmarks included in this repo.

python -m pip install tensorflow-datasets

Install common data science packages.

conda install jupyter pandas numpy matplotlib scikit-learn

Start Jupyter Notebook.

jupyter notebook

Import dependencies and check TensorFlow version/GPU access.

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__}")
If it all worked, you should see something like:
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
Resources


Apple's TensorFlow Metal Plugin - https://developer.apple.com/metal/tensorflow-plugin/
Conda Miniforge - https://github.com/conda-forge/miniforge

If you have any issues, leave a comment below so others can see.