Install from source

Caution

Users who have issues about installing k2 from source are mostly installing PyTorch with conda install.

We suggest that you install PyTorch using pip install.

Hint

It supports Linux (CPU + CUDA), macOS (CPU), and Windows (CPU + CUDA).

Hint

You can pass the option -DK2_WITH_CUDA=OFF to cmake to build a CPU only version of k2. In that case, you have to install a CPU version of PyTorch; otherwise, you will get a CMake configuration error, saying that cuDNN cannot be found.

Before compiling k2, some preparation work has to be done:

Have a compiler supporting at least C++14, e.g., GCC >= 7.0, Clang >= 3.4.

Install CMake. CMake 3.11.0 and 3.18.0 are known to work.

Install Python3. Please pass --enabled-shared to ./configure if you install Python from source.

Install PyTorch.

Install CUDA toolkit and cuDNN. Please refer to CUDA and cuDNN.

Hint

You can use pip install cmake to install the latest version of CMake.

Caution

cudatoolkit installed by conda install cannot be used to compile k2.

Please follow CUDA and cuDNN to install cudatoolkit and cuDNN.

After setting up the environment, we are ready to build k2:

git clone https://github.com/k2-fsa/k2.git
cd k2
export K2_MAKE_ARGS="-j6"
python3 setup.py install

That is all you need to run.

Hint

We use export K2_MAKE_ARGS="-j6" to pass -j6 to make to reduce compilation time. If you have many GPUs and enough RAM, you can choose a larger value.

Caution

If you plan to run k2 on a different machine than the one you used to build k2 and the two machines have different types of GPUs, please use the following commands to install k2.
git clone https://github.com/k2-fsa/k2.git
cd k2
export K2_CMAKE_ARGS="-DK2_BUILD_FOR_ALL_ARCHS=ON"
python3 setup.py install

Otherwise, you may get some error like below when running k2:

[F] /xxx/k2/k2-latest/k2/csrc/eval.h:147:void k2::EvalDevice(cudaStream_t,
int32_t, LambdaT&) [with LambdaT = __nv_dl_wrapper_t<__nv_dl_tag<k2::Array1<int>
(*)(std::shared_ptr<k2::Context>, int, int, int), k2::Range<int>, 1>, int*,
int, int>; cudaStream_t = CUstream_st*; int32_t = int] Check failed:
e == cudaSuccess (98 vs. 0)  Error: invalid device function.

To test that k2 is installed successfully, you can run:

$ python3
Python 3.8.6 (default, Dec  2 2020, 15:56:31)
[GCC 7.5.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import k2
>>> s = '''
... 0 1 -1 0.1
... 1
... '''
>>> fsa = k2.Fsa.from_str(s)
>>> print(fsa)
k2.Fsa: 0 1 -1 0.1
1
properties_str = "Valid|Nonempty|TopSorted|TopSortedAndAcyclic|ArcSorted|ArcSortedAndDeterministic|EpsilonFree|MaybeAccessible|MaybeCoaccessible".

To uninstall k2, run:

pip uninstall k2