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update wheels installation instructions for 0.14.0 (#748)
sync doc welcome page with readme Signed-off-by: Clement Fuji Tsang <[email protected]>
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docs/index.rst

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@@ -3,10 +3,10 @@ Welcome to Kaolin Library Documentation
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.. image:: ../assets/kaolin.png
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NVIDIA Kaolin library provides a PyTorch API for working with a variety of 3D representations and includes a growing collection of GPU-optimized operations such as modular differentiable rendering, fast conversions between representations, data loading, 3D checkpoints and more.
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`NVIDIA Kaolin library <https://github.com/NVIDIAGameWorks/kaolin>`_ provides a PyTorch API for working with a variety of 3D representations and includes a growing collection of GPU-optimized operations such as modular differentiable rendering, fast conversions between representations, data loading, 3D checkpoints, differentiable camera API, differentiable lighting with spherical harmonics and spherical gaussians, powerful quadtree acceleration structure called Structured Point Clouds, interactive 3D visualizer for jupyter notebooks, convenient batched mesh container and more.
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See :ref:`Installation <installation>`, :ref:`API Overview <overview>` and :ref:`Tutorials <tutorial_index>` to get started!
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Kaolin library is part of a larger suite of tools for 3D deep learning research. For example, `Omniverse Kaolin app <https://docs.omniverse.nvidia.com/app_kaolin/app_kaolin/overview.html>`_ allows interactive visualization of 3D checkpoints. To find out more about the Kaolin ecosystem, visit the `NVIDIA Kaolin Dev Zone page <https://developer.nvidia.com/kaolin>`_.
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Note that Kaolin library is part of the larger `NVIDIA Kaolin effort <https://developer.nvidia.com/kaolin>`_ for 3D deep learning.
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.. toctree::

docs/notes/installation.rst

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------------
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* Linux, Windows, or macOS (CPU-only)
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* Python >= 3.7, <= 3.9
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* Python >= 3.7, <= 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, <= 2.0.0
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* torch >= 1.8, <= 2.0.1
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Quick Start (Linux, Windows)
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----------------------------
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.. code-block:: bash
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$ pip install kaolin==0.13.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-{TORCH_VER}_cu{CUDA_VER}.html
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$ pip install kaolin==0.14.0 -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** | **cu102** | **cu111** | **cu113** | **cu116** | **cu117** |
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| **torch / CUDA** | **cu113** | **cu115** | **cu116** | **cu117** | **cu118** |
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+==================+===========+===========+===========+===========+===========+
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| **torch-1.13.1** | | | |||
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| **torch-2.0.0** | | | |||
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.13.0** | | | |||
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| **torch-2.0.1** | | | |||
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.12.1** | | ||| |
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| **torch-1.13.1** | | ||| |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.12.0** | | ||| |
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| **torch-1.13.0** | | ||| |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.11.0** || || | |
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| **torch-1.12.1** || || | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.10.2** || || | |
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| **torch-1.12.0** || || | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.10.1** |||| | |
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+------------------+-----------+-----------+-----------+-----------+-----------+
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| **torch-1.10.0** |||| | |
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| **torch-1.11.0** ||| | | |
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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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Kaolin may be able to work with other PyTorch versions, but we only explicitly test within the version range 1.10.0 to 2.0.0.
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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 11.3:
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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==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
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$ pip install torch==2.0.1 --extra-index-url https://download.pytorch.org/whl/cu118
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4. Optional Environment Variables

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