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Local installation

  • Total installation time is around 10 minutes.
  • The first import of keypoint_moseq after installation can take a few minutes.
  • If you experience any issues, reach out to us on slack! We're happy to help.

Note

If using Windows, make sure to run all the commands below from an Anaconda Prompt.

Install using conda

Use conda environment files to automatically install the appropriate GPU drivers and other dependencies. Start by cloning the repository:

git clone https://github.com/dattalab/keypoint-moseq
cd keypoint-moseq

Install the appropriate conda environment for your platform:

# Windows (CPU-only)
conda env create -f conda_envs\environment.win64_cpu.yml

# Windows (GPU)
conda env create -f conda_envs\environment.win64_gpu.yml

# Linux (CPU-only)
conda env create -f conda_envs/environment.linux_cpu.yml

# Linux (GPU)
conda env create -f conda_envs/environment.linux_gpu.yml

# Mac (CPU-only)
conda env create -f conda_envs/environment.mac_cpu.yml

Activate the new environment:

conda activate keypoint_moseq

To run keypoint-moseq in jupyter, either launch jupyterlab directly from the keypoint_moseq environment or register a globally-accessible jupyter kernel as follows:

python -m ipykernel install --user --name=keypoint_moseq

Note

If you are using Windows with a GPU and see the error XlaRuntimeError: UNKNOWN: no kernel image is available for execution on the device try updating your GPU drivers to the latest version.

Install using pip

Note

If you are using Windows with a GPU and would like to pip install keypoint-moseq, then you must also have CUDA 11.1 / cuDNN 8.2 installed system-wide (i.e. through the usual Windows OS). Furthermore, if you are using Windows 11, you must use Windows Subsystem for Linux.

Create a new conda environment with python 3.9:

conda create -n keypoint_moseq python=3.9
conda activate keypoint_moseq

Next install jax and jax-moseq using one of the options below.

  1. CPU only

    Install jax for your operating-system:

    # MacOS or Linux (CPU)
pip install "jax[cpu]==0.3.22" -f https://storage.googleapis.com/jax-releases/jax_releases.html

# Windows (CPU)
pip install jax==0.3.22 https://whls.blob.core.windows.net/unstable/cpu/jaxlib-0.3.22-cp39-cp39-win_amd64.whl

    Install jax-moseq:

    pip install jax-moseq

  2. GPU with CUDA 11

    Install jax for your operating-system:

    # MacOS or Linux (GPU with CUDA 11)
pip install "jax[cuda11_cudnn82]==0.3.22" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html


# Windows (GPU with CUDA 11)
pip install jax==0.3.22 https://whls.blob.core.windows.net/unstable/cuda111/jaxlib-0.3.22+cuda11.cudnn82-cp39-cp39-win_amd64.whl

    Install jax-moseq:

    pip install jax-moseq[cuda11]

  3. GPU with CUDA 12

    This option assumes that you already have a working installation of jax that is compatible with CUDA 12. Among other things, the following code should run without error:

    import jax
jax.random.PRNGKey(0)

    Install jax-moseq:

    pip install jax-moseq[cuda12]

Install keypoint-moseq:

pip install keypoint-moseq

To run keypoint-moseq in jupyter, either launch jupyterlab directly from the keypoint_moseq environment or register a globally-accessible jupyter kernel as follows:

python -m ipykernel install --user --name=keypoint_moseq