How to install python and deep learning libraries ================================================= 1. Check if your computer has an NVIDIA graphics card ----------------------------------------------------- +----------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | **Platform** | **Steps** | +================+===================================================================================================================================================================+ | **Windows** | 1. Open *Device Manager* (**Right-click** the *Start* button; click *Device Manager*). | | | 2. Find and expand the *Display adapters* category. | | | 3. If the list contains any device starting with *NVIDIA*, your computer is equipped with an NVIDIA GPU. | | | 4. Visit `Download The Official Nvidia Drivers `_ to download and install (or update to) the latest driver for your NVIDIA GPU. | +----------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | **Linux** | 1. Open *Terminal*. | | | 2. Type ``lspci | grep -i nvidia`` and press **Enter**. | | | 3. If the command produces any text output, your computer is equipped with an NVIDIA GPU. | | | 4. Visit `Download The Official Nvidia Drivers `_ to download and install (or update to) the latest driver for your NVIDIA GPU.| +----------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | **macOS** | The required NVIDIA GPU is not supported on macOS. | +----------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+ 2. Check the maximum supported CUDA version of your NVIDIA GPU -------------------------------------------------------------- If your computer is running macOS or is not equipped with an NVIDIA graphics card, please skip this step. +----------------+---------------------------------------------------------------------------------------+ | **Platform** | **Steps** | +================+=======================================================================================+ | **Windows** | 1. Open *Command Prompt* (Press **Win** + **R**; type ``cmd``; press **Enter**). | | | 2. Type ``nvidia-smi`` and press **Enter**. | | | 3. Look for *CUDA Version* in the output. | | | 4. Note this version number for later. | +----------------+---------------------------------------------------------------------------------------+ | **Linux** | 1. Open *Terminal*. | | | 2. Type ``nvidia-smi`` and press **Enter**. | | | 3. Look for *CUDA Version* in the output. | | | 4. Note this version number for later. | +----------------+---------------------------------------------------------------------------------------+ .. note:: Older NVIDIA GPUs may not support the ``nvidia-smi`` command or may not display *CUDA version*. If this happens, try updating your graphics card drivers first and check again. Otherwise, your graphics card does not support CUDA. Now, please check if your computer meets the basic requirements for running. If it does, you can continue with the next steps. Otherwise, your computer cannot run the project participating in LiGHTLIN through the following configuration methods. +-----------------------------+----------------------------------+-------------------------------------+ | **Platform** | CPU only | NVIDIA GPU with CUDA >= 11.8 | | | | | | | or nonuse GPU | | | | | | | | or non-CUDA GPU | | | | | | | | or NVIDIA GPU with CUDA < 11.8 | | +=============================+==================================+=====================================+ | Windows 10/11 64-bit | |:x:| | |:white_check_mark:| | +-----------------------------+----------------------------------+-------------------------------------+ | Linux x86-64 | |:white_check_mark:| | |:white_check_mark:| | +-----------------------------+----------------------------------+-------------------------------------+ | Otherwise (including macOS) | |:x:| | |:x:| | +-----------------------------+----------------------------------+-------------------------------------+ 3. Download and install Miniconda --------------------------------- If your computer has already installed Anaconda or Miniconda, please skip this step. +----------------+---------------------------------------------------------------------------------------------------------------------------------------+ | **Platform** | **Installation Steps** | +================+=======================================================================================================================================+ | **Windows** | 1. Go to `Miniconda Archive `_. | | | 2. Download `Miniconda3-latest-Windows-x86_64.exe`. | | | 3. Run the installer. | | | 4. (Recommended) Change the default installation driver (C:). | | | 5. Complete the installation. | +----------------+---------------------------------------------------------------------------------------------------------------------------------------+ | **Linux** | 1. Go to `Miniconda Archive `_. | | | 2. Download `Miniconda3-latest-Linux-x86_64.sh`. | | | 3. Open *Terminal* in the download folder. | | | 4. Type ``./Miniconda3-latest-Linux-x86_64.sh``. | | | 5. Type ``yes`` and press **Enter** for any prompt that requires the user to type ``yes`` or ``no``. | | | 6. Close and reopen the terminal for changes to take effect. | +----------------+---------------------------------------------------------------------------------------------------------------------------------------+ .. the Miniconda3 latest Linux installer ending with **x86_64.sh** for *Intel/AMD CPUs* or **aarch64.sh** for *ARM CPUs* (Replace **Miniconda3-latest-Linux-x86_64.sh** with your downloaded file name). | **macOS** | 1. Go to `Miniconda Archive `_. | | | 2. Download the Miniconda3 latest macOS installer (ending with **arm64.pkg**). | | | 3. Run the installer and follow the prompts. | | | 4. Close and reopen the terminal for changes to take effect. | +----------------+---------------------------------------------------------------------------------------------------------------------------------------+ 4. Launch CONDA environment (for daily use) ------------------------------------------- +--------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ | **Platform** | **Steps to Launch** | +==============+========================================================================================================================================================+ | **Windows** | 1. Open *Start menu*. | | | 2. Find and run *Anaconda Prompt* as **Administrator**! | +--------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ | **Linux** | 1. Open *Terminal*. | | | 2. If you follow Step 3, there will be ``(base)`` at the beginning of the line, indicating that the conda environment has been automatically activated.| +--------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ .. | **macOS** | 1. Open *Terminal*. | | | 2. If you follow Step 3, there will be ``(base)`` at the beginning of the line, indicating that the conda environment has been automatically activated.| +--------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ 5. Create a Python 3.12 virtual environment ------------------------------------------- Type ``conda create --name lightlin python=3.12`` in the CONDA environment and press **Enter**. Here, ``lightlin`` is the name of the virtual environment, and you can also change it to another name. Please wait for the execution to complete before proceeding to the next step. 6. Activate the virtual environment (for daily use) --------------------------------------------------- Type ``conda activate lightlin`` in the CONDA environment and press **Enter**. When the beginning of a new line changes to ``(lightlin)``, it indicates a successful virtual environment switch. Here, ``lightlin`` needs to be replaced with the virtual environment name you taken. 7. Install PyTorch and popular point-cloud-based deep learning libraries ------------------------------------------------------------------------ If you encounter any errors while performing the steps correctly, it means that your system environment is not compatible and you should replace your computer for use. Please select the corresponding command based on the result from Step 2 and run it in the activated virtual environment (such as ``lightlin``). 1. Install `PyTorch `_ .. warning:: **This step is very easy to choose incorrectly, please read it carefully!** For NVIDIA Blackwell-architecture GPUs (such as Geforce RTX 50 series), **YOU MUST INSTALL cu128**! Please refer to `here `_ for the specific products included. Otherwise, PyTorch will cause an error like .. code-block:: bash NVIDIA GeForce RTX 5070 Ti with CUDA capability sm_120 is not compatible with the current PyTorch installation. The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90 compute_37. If you want to use the NVIDIA GeForce RTX 5070 Ti GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/ For NVIDIA GPUs prior to the Blackwell architecture (such as Geforce RTX 40 series and earlier), you can choose to install *cu126* or *cu118*, but **DO NOT INSTALL cu128**, otherwise spconv will cause an error like .. code-block:: bash N > 0 assert faild. CUDA kernel launch blocks must be positive, but got N= 0 +-------------------------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ | **CUDA Version** | **PyTorch** | **Command** | +=========================+=====================+========================================================================================================================================================+ | **>= 12.8** | **cu128** | ``pip install torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 --index-url https://download.pytorch.org/whl/cu128`` | +-------------------------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ | **>= 12.6** | **cu126** | ``pip install torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 --index-url https://download.pytorch.org/whl/cu126`` | +-------------------------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ | **>= 11.8** | **cu118** | ``pip install torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 --index-url https://download.pytorch.org/whl/cu118`` | +-------------------------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ | **Not using CUDA** | **cpu** | ``pip install torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 --index-url https://download.pytorch.org/whl/cpu`` | +-------------------------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ .. .. note:: The macOS, non-NVIDIA GPUs, and older NVIDIA GPUs are all considered **unsupported** CUDA platforms. 2. Install `SpConv: Spatially Sparse Convolution Library `_ +---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | **PyTorch Version** | **Command** | +=====================+===============================================================================================================================================================================================================+ | **cu128** | For Windows: | | | | | | ``pip install "https://raw.githubusercontent.com/MrForExample/Comfy3D_Pre_Builds/refs/heads/main/_Build_Wheels/_Wheels_win_py312_torch2.7.0_cu128/spconv-2.3.8-cp312-cp312-win_amd64.whl"`` | | | | | | For Linux x86-64: | | | | | | ``pip install https://raw.githubusercontent.com/MrForExample/Comfy3D_Pre_Builds/refs/heads/main/_Build_Wheels/_Wheels_linux_py312_torch2.7.0_cu128/spconv_cu126-2.3.8-cp312-cp312-manylinux_2_28_x86_64.whl`` | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | **cu126** | ``pip install spconv-cu126`` | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | **cu118** | ``pip install spconv-cu118`` | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | **cpu** | ``pip install spconv`` | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ 3. Install `PyG (Pytorch Geometric) `_ +---------------------+---------------------------------------------------------------------------------------------------------------------------------------+ | **PyTorch Version** | **Command** | +=====================+=======================================================================================================================================+ | **cu128** | .. code-block:: bash | | | | | | pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.7.0+cu128.html | | | pip install torch_geometric | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------+ | **cu126** | .. code-block:: bash | | | | | | pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.7.0+cu126.html | | | pip install torch_geometric | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------+ | **cu118** | .. code-block:: bash | | | | | | pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.7.0+cu118.html | | | pip install torch_geometric | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------+ | **cpu** | .. code-block:: bash | | | | | | pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.7.0+cpu.html | | | pip install torch_geometric | +---------------------+---------------------------------------------------------------------------------------------------------------------------------------+ 4. Install `NVIDIA Kaolin Library `_ +---------------------+-----------------------------------------------------------------------------------------------------------+ | **PyTorch Version** | **Command** | +=====================+===========================================================================================================+ | **cu128** | ``pip install kaolin==0.18.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.7.0_cu128.html`` | +---------------------+-----------------------------------------------------------------------------------------------------------+ | **cu126** | ``pip install kaolin==0.18.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.7.0_cu126.html`` | +---------------------+-----------------------------------------------------------------------------------------------------------+ | **cu118** | ``pip install kaolin==0.18.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.7.0_cu118.html`` | +---------------------+-----------------------------------------------------------------------------------------------------------+ | **cpu** | ``pip install kaolin==0.18.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.7.0_cpu.html`` | +---------------------+-----------------------------------------------------------------------------------------------------------+ 8. Verify Installation ---------------------- To ensure everything works properly later, please check your installation with the following steps: 1. Run Steps 4 and 6 to activate the target virtual environment. 2. Type ``pip list`` and carefully check that the suffixes of pytorch, spconv, and kaolin are consistent with each other and compatible with your *CUDA Version*. 3. Type ``python``. 4. In the output, verify that the Python version is ``3.12.X`` (you can ignore the X). 5. Type the following commands one by one and press **Enter** after each: .. code-block:: python3 import torch import spconv import torch_scatter import kaolin import torch_geometric torch.cuda.is_available() If no errors are reported, everything has been installed successfully! Finally, you can type ``exit()`` and press **Enter** to exit Python. 9. Postscript (for daily use) ----------------------------- In the virtual environment, you need to master how to change the **working directory** .. _working_directory: .. code-block:: bash cd "/path/of/your/project" # For Linux REM For Windows cd /d "D:\path\of\your\project" .. note:: The **working directory** is the folder where your commands are executed. You can see it in the prompt before you type a command, e.g.: - On Linux: the path shown before the ``$``, ``#`` etc, e.g. ``ubuntu@linuxopsys:~/path/of/your/project$`` ``(lightlin) [root@pc project]#`` (in the latter case, run ``pwd`` to show the full path ``/path/of/your/project``). - On Windows: the path shown before the ``>``, e.g. ``D:\path\of\your\project>`` ``(base) D:\path\of\your\project>`` and execute Python files by .. code-block:: bash python your_script.py or using command-line arguments like .. code-block:: bash python your_script.py -h We also recommend that you master the basic usage methods of `conda `_ and `pip `_. For example: - Clean after installing the library to save disk space: .. code-block:: bash conda clean -a pip cache purge - Exit the current virtual environment to activate the default (base) environment: .. code-block:: bash conda deactivate - Remove a virtual environment: .. code-block:: bash conda env remove -n your_env_name