PennyLane-Lightning requires Python version 3.7 and above. It can be installed using
$ pip install pennylane-lightning
To build PennyLane-Lightning from source you can run
$ pip install pybind11 pennylane-lightning --no-binary :all:
A C++ compiler such as
MSVC is required. On Debian-based systems, this
can be installed via
$ sudo apt install g++
The pybind11 library is also used for binding the C++ functionality to Python.
Alternatively, for development and testing, you can install by cloning the repository:
$ git clone https://github.com/PennyLaneAI/pennylane-lightning.git $ cd pennylane-lightning $ pip install -r requirements.txt $ pip install -e .
Note that subsequent calls to
pip install -e . will use cached binaries stored in the
build folder. Run
make clean if you would like to recompile.
You can also pass
cmake options with
$ python3 setup.py build_ext -i --define="ENABLE_OPENMP=OFF;ENABLE_NATIVE=ON"
and install the compilied library with
$ python3 setup.py develop
For GPU support, PennyLane-Lightning-GPU can be installed by providing the optional
$ pip install pennylane-lightning[gpu]
For more information, please refer to the PennyLane Lightning GPU documentation.
To test that the plugin is working correctly you can test the Python code within the cloned repository:
$ make test-python
while the C++ code can be tested with
$ make test-cpp
One can also build the plugin using CMake:
$ cmake -S. -B build $ cmake --build build
To test the C++ code:
$ mkdir build && cd build $ cmake -DBUILD_TESTS=ON -DCMAKE_BUILD_TYPE=Debug .. $ make
Other supported options are
Compile on Windows with MSVC¶
We recommend to use
[x64 (or x86)] Native Tools Command Prompt for VS [version] for compiling the library. Be sure that
python can be called within the prompt.
$ cmake --version $ python --version
Then a common command will work.
$ pip install -r requirements.txt $ pip install -e .
Note that OpenMP and BLAS are disabled in this setting.