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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.

On Ubuntu:

sudo apt update
sudo apt install python3-dev python3-pip  # Python 3
sudo pip3 install --user --upgrade virtualenv

On macOS:

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
export PATH="/usr/local/bin:/usr/local/sbin:$PATH"
brew update
brew install python  # Python 3
sudo pip3 install --user --upgrade virtualenv

2. Create a virtual environment.

virtualenv --python python3 "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

3 (alternative). Install the nightly TensorFlow Federated Python package.

pip install --upgrade tensorflow-federated-nightly

4. Test Tensorflow Federated.

python -c "import tensorflow_federated as tff; print(tff.federated_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.

Note: an easier approach to use the new feature not in the released package might be pip installing the nightly package

1. Install the Python development environment.

On Ubuntu:

sudo apt update
sudo apt install python3-dev python3-pip  # Python 3
sudo pip3 install --user --upgrade virtualenv

On macOS:

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
export PATH="/usr/local/bin:/usr/local/sbin:$PATH"
brew update
brew install python  # Python 3
sudo pip3 install --user --upgrade virtualenv

2. Install Bazel.

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

3. Clone the Tensorflow Federated repository.

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

4. Build the TensorFlow Federated Python package.

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

5. Create a new project.

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

6. Create a virtual environment.

virtualenv --python python3 "venv"
source "venv/bin/activate"
pip install --upgrade pip

Note: To exit the virtual environment run deactivate.

7. Install the TensorFlow Federated Python package.

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

8. Test Tensorflow Federated.

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

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