Install TensorFlow Quantum

There are a few ways to set up your environment to use TensorFlow Quantum (TFQ):

  • The easiest way to learn and use TFQ requires no installation—run the TensorFlow Quantum tutorials directly in your browser using Google Colab.
  • To use TensorFlow Quantum on a local machine, install the TFQ package using Python's pip package manager.
  • Or build TensorFlow Quantum from source.

TensorFlow Quantum is supported on Python 3.10, 3.11, and 3.12 and depends directly on Cirq.

Pip package

Requirements

See the TensorFlow install guide to set up your Python development environment and an (optional) virtual environment.

Upgrade pip and install TensorFlow 

  pip install --upgrade pip
  pip install tensorflow==2.16.2

Install the package

Install the latest stable release of TensorFlow Quantum:

  pip install -U tensorflow-quantum

Build from source

The following steps are tested for Ubuntu-like systems.

1. Set up a Python 3 development environment

First we need the Python 3.10 development tools. 

  sudo apt update
  sudo apt-get install pkg-config zip g++ zlib1g-dev unzip python3.10
  sudo apt install python3.10 python3.10-dev python3.10-venv python3-pip
  python3.10 -m pip install --upgrade pip

2. Create a virtual environment

Go to your workspace directory and make a virtual environment for TFQ development. 

  python3.10 -m venv quantum_env
  source quantum_env/bin/activate

Make sure that the virtual environment is activated for the rest of the steps below, and every time you want to use TFQ in the future.

3. Install Bazel

As noted in the TensorFlow build from source guide, the Bazel build system will be required.

Our latest source builds use TensorFlow 2.16.2. To ensure compatibility we use bazel version 6.5.0. To remove any existing version of Bazel: 

  sudo apt-get remove bazel

Download and install bazel version 6.5.0:

  wget https://github.com/bazelbuild/bazel/releases/download/6.5.0/bazel_6.5.0-linux-x86_64.deb

  sudo dpkg -i bazel_6.5.0-linux-x86_64.deb

To prevent automatic updating of bazel to an incompatible version, run the following:

  sudo apt-mark hold bazel

Finally, confirm installation of the correct bazel version:

  bazel --version

4. Build TensorFlow from source

TensorFlow Quantum is compatible with TensorFlow version 2.16.2. To build TensorFlow from sources, download the TensorFlow source code by cloning the git repository, then switch to the r2.16 branch:

  git clone https://github.com/tensorflow/tensorflow.git
  cd tensorflow
  git checkout r2.16

Be sure the virtual environment you created in step 2 is activated, then follow the TensorFlow instructions for how to build and install the pip package on your system.

After the build is complete, and you have installed the pip package, leave the TensorFlow directory before moving on to step 5:

  cd ..

5. Download TensorFlow Quantum

We use the standard fork and pull request workflow for contributions. After forking from the TensorFlow Quantum GitHub page, download the source of your fork and install the requirements:

  git clone https://github.com/username/quantum.git
  cd quantum
  pip install -r requirements.txt

6. Build and install TensorFlow Quantum

Be sure the virtual environment you created in step 2 is activated. Then, run the command below to install the TensorFlow Quantum dependencies:

  pip install -r requirements.txt

Next, use TensorFlow Quantum's configure.sh script to configure the TFQ build:

  ./configure.sh

Now build TensorFlow Quantum:

  bazel build -c opt --cxxopt="-O3" --cxxopt="-march=native" release:build_pip_package

After the build is complete, run the next two commands to create a Python package for TensorFlow Quantum and write it to a temporary directory (we use /tmp/tfquantum/ in this example), then install it using pip:

  bazel-bin/release/build_pip_package /tmp/tfquantum/
  pip install /tmp/tfquantum/name_of_generated_wheel.whl

To confirm that TensorFlow Quantum has successfully been installed, you can run the tests: 

  ./scripts/test_all.sh