ruankie / m1-tensorflow

Setting up a GPU-enabled Tensorflow development environment on the Apple M1 chip and Apple GPU

m1-tensorflow

Template setup of GPU-enabled Tensorflow development environment on the Apple M1 chip with Apple GPU This template development environment includes the following common data science packages:

- Tensorflow
- Pandas
- Numpy
- Seaborn
- Jupyter Lab

Usage

1. Start a new repo using this template
2. Update your LICENSE file.
3. Update your README.md file.
   1. Update description
   2. Update usage
   3. Update shields
4. Set up and activate conda environment
   1. Add/change any dependencies and their versions in the ./conda.yml file.
   2. Set up your conda environment and activate it by running:

      conda env create -f conda.yml
      conda activate tf-metal

5. Add your own scripts in ./src/
6. Add your own notebooks in ./notebooks/
7. Add your own data in ./data/

This template creates the following folder structure:

<your-repo-name>
├── LICENSE
├── README.md
├── conda.yml
├── data
├── notebooks
│   └── example.ipynb
├── setup.py
└── src
    ├── __init__.py
    └── utils.py

References

• https://www.tensorflow.org/
• https://developer.apple.com/metal/tensorflow-plugin/
• https://stackoverflow.com/questions/72964800/what-is-the-proper-way-to-install-tensorflow-on-apple-m1-in-2022