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See https://k2.readthedocs.io/en/latest/installation/index.html for more details.

Use conda

conda install -c k2-fsa -c pytorch -c conda-forge k2 python=3.8 cudatoolkit=11.1 pytorch=1.8.1
# You can choose the versions of Python, cudatoolkit, and PyTorch as you like

Read https://k2.readthedocs.io/en/latest/installation/conda.html for more.

Use pip

# Install a CUDA version compiled using CUDA 10.1 and PyTorch 1.7.1
#
pip install k2

# Install a CPU version compiled against PyTorch 1.8.1 on 2021.10.22
#
pip install k2==1.9.dev20211022+cpu.torch1.8.1 -f https://k2-fsa.org/nightly/

# Install a CPU version compiled against PyTorch 1.9.0 on 2021.10.22
#
pip install k2==1.9.dev20211022+cpu.torch1.9.0 -f https://k2-fsa.org/nightly/

# Please visit https://k2-fsa.org/nightly/ for more versions of k2

Read the following two pages to learn more:

From source

git clone https://github.com/k2-fsa/k2.git
cd k2
python3 setup.py install

From source (with CUDA support)

git clone https://github.com/k2-fsa/k2.git
cd k2
export K2_CMAKE_ARGS="-DK2_WITH_CUDA=ON -DCMAKE_BUILD_TYPE=Release"
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda/lib:$LD_LIBRARY_PATH
export PATH=$PATH:/usr/local/cuda/bin
python3 setup.py install

Read https://k2.readthedocs.io/en/latest/installation/from_source.html to learn more

For developers

First, you have to install CMake, CUDA toolkit (with cuDNN), and PyTorch:

  • CMake 3.11.0 and 3.18.0 are known to work. Other CMake versions may work but they are not tested.
  • Install PyTorch. PyTorch 1.5.x and above are known to work. Other PyTorch versions may work, but they are not tested.
  • Install CUDA toolkit and cuDNN. CUDA 10.1 and above are known to work. Other versions are not tested.
  • Your Python version has to be at least 3.6.

Second, let's clone the repository to some path /some/path:

cd /some/path
git clone https://github.com/k2-fsa/k2.git

# Normally, you would first fork the repo and use
# git clone https://github.com/your_github_username/k2.git

To build a release version, use:

cd /some/path/k2
mkdir build_release
cd build_release
cmake -DCMAKE_BUILD_TYPE=Release ..
make -j
export PYTHONPATH=$PWD/../k2/python:$PYTHONPATH # for `import k2`
export PYTHONPATH=$PWD/lib:$PYTHONPATH # for `import _k2`

# To test that your build is successful, run
python3 -c "import k2; print(k2.__file__)"
# It should print /some/path/k2/k2/python/k2/__init.py

python3 -c "import torch; import _k2; print(_k2.__file__)"
# It should print /some/path/k2/build_release/lib/_k2.cpython-38-x86_64-linux-gnu.so
# (I assume that you're using Python 3.8, so there is a string 38 above)

To build a debug version, use:

cd /some/path/k2
mkdir build_debug
cd build_debug
cmake -DCMAKE_BUILD_TYPE=Debug ..
make -j
export PYTHONPATH=$PWD/../k2/python:$PYTHONPATH # for `import k2`
export PYTHONPATH=$PWD/lib:$PYTHONPATH # for `import _k2`

# To test that your build is successful, run
python3 -c "import k2; print(k2.__file__)"
# It should print /some/path/k2/k2/python/k2/__init.py

python3 -c "import torch; import _k2; print(_k2.__file__)"
# It should print /some/path/k2/build_debug/lib/_k2.cpython-38-x86_64-linux-gnu.so
# (I assume that you're using Python 3.8, so there is a string 38 above)

To run tests, use:

cd /some/path/k2/build_release # or switch to build_debug
make -j
make test
# alternatively, you can run
# ctest -j5

To run a specific C++ test, use:

cd /some/path/k2/build_release # or switch to build_debug
make cu_ragged_test
# You will find an executable ./bin/cu_ragged_test
./cu_ragged_test
#
# Use `make help` to find all available C++ tests


# Inside k2/csrc/ragged_test.cu, there is a test case like below:
#
# TEST(RaggedShapeOpsTest, CatMoreAxes) {
#
# To run the above test case only, use
./cu_ragged_test --gtest_filter="RaggedShapeOpsTest.CatMoreAxes"
#
# The option `--gtest_filter` supports regular expressions.
#
# Run `./cu_ragged_test --help` to learn more

To run a specific Python test, use:

cd /some/path/k2/build_release # or switch to build_debug

export PYTHONPATH=$PWD/../k2/python:$PYTHONPATH # for `import k2`
export PYTHONPATH=$PWD/lib:$PYTHONPATH # for `import _k2`

python3 ../k2/python/tests/index_test.py

# Alternatively, you can use
ctest --verbose -R index_test_py

# At the head of each Python test file, you can find an instruction
# describing how to run that test file.

Hint

As a developer, there is no need to run python3 setup.py install!!!

All you need is to create a bash script, say activate_k2_release.sh, containing:

#!/bin/bash
K2_ROOT=/some/path/k2
export PYTHONPATH=$K2_ROOT/k2/python:$PYTHONPATH
export PYTHONPATH=$K2_ROOT/build_release/lib:$PYTHONPATH

To simpily the debug process, we also recommend you to create another bash script, e.g., activate_k2_debug.sh, containing:

#!/bin/bash
K2_ROOT=/some/path/k2
export PYTHONPATH=$K2_ROOT/k2/python:$PYTHONPATH
export PYTHONPATH=$K2_ROOT/build_debug/lib:$PYTHONPATH

To use a release build of k2, run:

source /path/to/activate_k2_release.sh

To use a debug build of k2, run:

source /path/to/activate_k2_debug.sh

To check whether you are using a release version or a debug version, run:

python3 -c "import torch; import _k2; print(_k2.__file__)"

It should print the directory where k2 was built. That is, the above output contains a string build_release or build_debug.

Alternatively, you can run:

python3 -m k2.version

You can find the build type in the above output.