install.md

Install TensorFlow Federated

There are a few ways to set up your environment to use TensorFlow Federated (TFF):

• The easiest way to learn and use TFF requires no installation; run the TensorFlow Federated tutorials directly in your browser using Google Colaboratory.
• To use TensorFlow Federated on a local machine, install the TFF package with Python's pip package manager.
• If you have a unique machine configuration, build the TFF package from source .

Install TensorFlow Federated using pip

1. Install the Python development environment.

sudo apt update
sudo apt install python3-dev python3-pip  # Python 3

2. Create a virtual environment.

python3 -m venv "venv"
source "venv/bin/activate"
pip install --upgrade "pip"

Note: To exit the virtual environment, run deactivate.

3. Install the released TensorFlow Federated Python package.

pip install --upgrade tensorflow-federated

4. Test Tensorflow Federated.

python -c "import tensorflow_federated as tff; print(tff.tensorflow_computation(lambda: 'Hello World')())"

Success: The latest TensorFlow Federated Python package is now installed.

Build the TensorFlow Federated Python package from source

Building a TensorFlow Federated Python package from source is helpful when you want to:

• Make changes to TensorFlow Federated and test those changes in a component that uses TensorFlow Federated before those changes are submitted or released.
• Use changes that have been submitted to TensorFlow Federated but have not been released.

1. Install the Python development environment.

sudo apt update
sudo apt install python3-dev python3-pip  # Python 3

2. Install Bazel.

Install Bazel, the build tool used to compile Tensorflow Federated.

3. Clone the Tensorflow Federated repository.

git clone https://github.com/google-parfait/tensorflow-federated.git
cd "tensorflow-federated"

4. Create a virtual environment.

python3 -m venv "venv"
source "venv/bin/activate"
pip install --upgrade "pip"
pip install numpy

5. Build the TensorFlow Federated Python package.

mkdir "/tmp/tensorflow_federated"
bazel run //tools/python_package:build_python_package -- \
    --output_dir="/tmp/tensorflow_federated"

6. Exit the virtual environment

deactivate

7. Create a new project.

mkdir "/tmp/project"
cd "/tmp/project"

8. Create a new virtual environment.

python3 -m venv "venv"
source "venv/bin/activate"
pip install --upgrade "pip"

Note: To exit the virtual environment, run deactivate.

9. Install the TensorFlow Federated Python package.

pip install --upgrade "/tmp/tensorflow_federated/"*".whl"

10. Test Tensorflow Federated.

python -c "import tensorflow_federated as tff; print(tff.tensorflow_computation(lambda: 'Hello World')())"

Success: A TensorFlow Federated Python package is now built from source and installed.