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docs/notes/installation.rst
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docs/notes/installation.rst
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.. _installation:
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Installation
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============
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Most functions in Kaolin use PyTorch with custom high-performance code in C++ and CUDA. For this reason,
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full Kaolin functionality is only available for systems with an NVIDIA GPU, supporting CUDA. While it is possible to install
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Kaolin on other systems, only a fraction of operations will be available for a CPU-only install.
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Requirements
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------------
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* Linux, Windows, or macOS (CPU-only)
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* Python >= 3.8, <= 3.10
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* `CUDA <https://developer.nvidia.com/cuda-toolkit>`_ >= 10.0 (with 'nvcc' installed) See `CUDA Toolkit Archive <https://developer.nvidia.com/cuda-toolkit-archive>`_ to install older version.
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* torch >= 1.8, <= 2.1.1
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Quick Start (Linux, Windows)
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----------------------------
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| Make sure any of the supported CUDA and torch versions below are pre-installed.
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| The latest version of Kaolin can be installed with pip:
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.. code-block:: bash
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$ pip install kaolin==0.15.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-{TORCH_VER}_cu{CUDA_VER}.html
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.. Note::
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Replace *TORCH_VER* and *CUDA_VER* with any of the compatible options below.
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.. rst-class:: center-align-center-col
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch / CUDA** | **cu113** | **cu116** | **cu117** | **cu118** | **cu121** |
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+==================+===========+===========+===========+===========+===========+
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| **torch-2.1.1** | | | | ✓ | ✓ |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-2.1.0** | | | | ✓ | ✓ |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-2.0.1** | | | ✓ | ✓ | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-2.0.0** | | | ✓ | ✓ | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.13.1** | | ✓ | ✓ | | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.13.0** | | ✓ | ✓ | | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.12.1** | ✓ | ✓ | | | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.12.0** | ✓ | ✓ | | | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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For example, to install kaolin for torch 1.12.1 and CUDA 11.3:
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.. code-block:: bash
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$ pip install kaolin==0.15.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-1.12.1_cu113.html
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You can check https://nvidia-kaolin.s3.us-east-2.amazonaws.com/index.html to see all the wheels available.
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Installation from source
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------------------------
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.. Note::
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We recommend installing Kaolin into a virtual environment. For instance to create a new environment with `Anaconda <https://www.anaconda.com/>`_:
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.. code-block:: bash
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$ conda create --name kaolin python=3.8
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$ conda activate kaolin
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1. Clone Repository
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^^^^^^^^^^^^^^^^^^^
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Clone and optionally check out an `official release <https://github.com/NVIDIAGameWorks/kaolin/tags>`_:
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.. code-block:: bash
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$ git clone --recursive https://github.com/NVIDIAGameWorks/kaolin
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$ cd kaolin
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$ git checkout v0.15.0 # optional
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2. Install dependencies
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^^^^^^^^^^^^^^^^^^^^^^^
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You can install the dependencies running:
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.. code-block:: bash
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$ pip install -r tools/build_requirements.txt -r tools/viz_requirements.txt -r tools/requirements.txt
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2. Test CUDA
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^^^^^^^^^^^^
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You can verify that CUDA is properly installed at the desired version with nvcc by running the following:
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.. code-block:: bash
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$ nvidia-smi
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$ nvcc --version
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3. Install Pytorch
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^^^^^^^^^^^^^^^^^^
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Follow `official instructions <https://pytorch.org>`_ to install PyTorch of a supported version.
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Kaolin may be able to work with other PyTorch versions, but we only explicitly test within the version range 1.10.0 to 2.1.1.
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See below for overriding PyTorch version check during install.
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Here is how to install the latest Pytorch version supported by Kaolin for cuda 11.8:
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.. code-block:: bash
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$ pip install torch==2.1.1 --extra-index-url https://download.pytorch.org/whl/cu118
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4. Optional Environment Variables
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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* If trying Kaolin with an unsupported PyTorch version, set: ``export IGNORE_TORCH_VER=1``
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* If using heterogeneous GPU setup, set the architectures for which to compile the CUDA code, e.g.: ``export TORCH_CUDA_ARCH_LIST="7.0 7.5"``
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* In some setups, there may be a conflict between cub available with cuda install > 11 and ``third_party/cub`` that kaolin includes as a submodule. If conflict occurs or cub is not found, set ``CUB_HOME`` to the cuda one, e.g. typically on Linux: ``export CUB_HOME=/usr/local/cuda-*/include/``
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5. Install Kaolin
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^^^^^^^^^^^^^^^^^
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.. code-block:: bash
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$ python setup.py develop
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.. Note::
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Kaolin can be installed without GPU, however, CPU support is limited and many CUDA-only functions will be missing.
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Testing your installation
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-------------------------
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Run a quick test of your installation and version:
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.. code-block:: bash
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$ python -c "import kaolin; print(kaolin.__version__)"
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Running tests
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^^^^^^^^^^^^^
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For an exhaustive check, install testing dependencies and run tests as follows:
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.. code-block:: bash
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$ pip install -r tools/ci_requirements.txt
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$ export CI='true' # on Linux
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$ set CI='true' # on Windows
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$ pytest --import-mode=importlib -s tests/python/
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.. Note::
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These tests rely on CUDA operations and will fail if you installed on CPU only, where not all functionality is available.
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