Path: blob/master/site/en-snapshot/federated/install.md
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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.
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.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.
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/tensorflow/federated.git
cd "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 //tensorflow_federated/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.federated_computation(lambda: 'Hello World')())"
Success: A TensorFlow Federated Python package is now built from source and installed.