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INSTALL.md

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Installation

  • We'll use conda to install dependencies and set up the environment. We recommend using the Python 3.9 Miniconda installer.
  • After installing conda, install mamba to the base environment. mamba is a faster, drop-in replacement for conda: 
    conda install mamba -n base -c conda-forge
  • Also install conda-merge to the base environment: 
    conda install conda-merge -n base -c conda-forge

Next, follow the instructions for GPU or CPU machines depending on your hardware to create a new environment named ocp-models and install dependencies.

GPU machines

Instructions are for PyTorch 1.13.1, CUDA 11.6 specifically.

  • First, check that CUDA is in your PATH and LD_LIBRARY_PATH, e.g. 
    $ echo $PATH | tr ':' '\n' | grep cuda
/public/apps/cuda/11.6/bin

$ echo $LD_LIBRARY_PATH | tr ':' '\n' | grep cuda
/public/apps/cuda/11.6/lib64
    The exact paths may differ on your system.
  • Then install the dependencies: 
    conda-merge env.common.yml env.gpu.yml > env.yml
mamba env create -f env.yml
    Activate the conda environment with conda activate ocp-models.
  • Install the ocp package with pip install -e ..
  • Finally, install the pre-commit hooks: 
    pre-commit install

CPU-only machines

Please skip the following if you completed the with-GPU installation from above.

conda-merge env.common.yml env.cpu.yml > env.yml
mamba env create -f env.yml
conda activate ocp-models
pip install -e .
pre-commit install