Win11+RTX3090 亲测 · ComfyUI Hunyuan3D 全程实录 ②：nvdiffrast 源码编译实战（CUDA 13.1 零降级）
环境：Windows 11 23H2 | Intel Ultra 9 285K | RTX 3090 24 GB | CUDA 13.1 | Python 3.12.11 | PyTorch 2.7.1+cu126 | VS2022 17.12
系列：全程实录第 ② 篇（第 ① 篇见依赖安装指南）
一、前言：为什么必须本地编译
nvdiffrast
nvdiffrast 是 NVIDIA 官方的高性能可微渲染库，PyPI 仅提供 Linux wheel，Windows 用户必须：
- 克隆源码
- 本地编译 CUDA 扩展
_nvdiffrast_c.cp312-win_amd64.pyd
本文带你 零降级 CUDA 驱动，不改 PyTorch 版本，在 CUDA 13.1 + PyTorch 12.6 环境下一次编译通过。
二、环境 checklist
| 项目 | 本机示例 | 最低要求 |
|---|---|---|
| OS | Windows 11 专业工作站版 26H1 | Win10 21H2+ |
| CPU | Intel® Core™ Ultra 9 285K (3.70 GHz) | 64 bit |
| GPU | NVIDIA GeForce RTX 3090 24 GB | GTX 30 系列+ |
| 显卡驱动 及 CUDA 版本 | 595.02 / CUDA 13.1 | ≥ 12.6 |
| Python | 3.12.11 64-bit | 3.10-3.12 |
| PyTorch | 2.7.1+cu126 | 2.5.0+cu118+ |
| VS Build Tools | 17.12 / MSVC 14.44 | 2019/2022 任意 |
⚠️ 终端要求：开始菜单 → “x64 Native Tools Command Prompt for VS 2022” → 右键 以管理员身份运行（黑底黄字窗口才带 cl.exe/nvcc）
三、直接安装 vs 直接编译 vs 修改编译 对比
| 方式 | 命令 | 结果 | 日志片段 |
|---|---|---|---|
| 直接 pip | pip install nvdiffrast | ❌ 无 Windows wheel | ERROR: Could not find a version that satisfies the requirement nvdiffrast |
| 直接源码编译 | python setup.py bdist_wheel | ❌ CUDA 版本检查失败 | RuntimeError: CUDA version (13.1) mismatches PyTorch (12.6) |
| 修改后编译 | python setup_patch.py bdist_wheel | ✅ 生成可用 wheel | creating 'dist\nvdiffrast-0.4.0-cp312-cp312-win_amd64.whl' |
下文全程基于 第三种。
四、setup.py 修改细节（核心）
在 文件最顶部插入两行即可绕过版本检查：
# 跳过 CUDA 驱动版本检查（必须放最前）importtorch.utils.cpp_extensionas_ext _ext._check_cuda_version=lambda*args,**kwargs:None完整setup_patch.py（已含 RTX30 架构优化）：
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.## NVIDIA CORPORATION and its licensors retain all intellectual property# and proprietary rights in and to this software, related documentation# and any modifications thereto. Any use, reproduction, disclosure or# distribution of this software and related documentation without an express# license agreement from NVIDIA CORPORATION is strictly prohibited.importsetuptoolsimportos# 1. 强制跳过 Torch 内部 CUDA 驱动版本检查importtorch.utils.cpp_extensionas_ext _ext._check_cuda_version=lambda*args,**kwargs:None# Print an error message if there's no PyTorch installed.try:fromtorch.utils.cpp_extensionimportBuildExtension,CUDAExtensionexceptImportError:print("\n\n"+"*"*70)print("ERROR! Cannot compile nvdiffrast CUDA extension. Please ensure that:\n")print("1. You have PyTorch installed")print("2. You run 'pip install' with --no-build-isolation flag")print("*"*70+"\n\n")exit(1)setuptools.setup(ext_modules=[CUDAExtension("_nvdiffrast_c",sources=["csrc/common/antialias.cu","csrc/common/common.cpp","csrc/common/cudaraster/impl/Buffer.cpp","csrc/common/cudaraster/impl/CudaRaster.cpp","csrc/common/cudaraster/impl/RasterImpl.cpp","csrc/common/cudaraster/impl/RasterImpl_kernel.cu","csrc/common/interpolate.cu","csrc/common/rasterize.cu","csrc/common/texture.cpp","csrc/common/texture_kernel.cu","csrc/torch/torch_antialias.cpp","csrc/torch/torch_bindings.cpp","csrc/torch/torch_interpolate.cpp","csrc/torch/torch_rasterize.cpp","csrc/torch/torch_texture.cpp",],extra_compile_args={"cxx":["-DNVDR_TORCH"]# Disable warnings in torch headers.+(["/wd4067","/wd4624","/wd4996"]ifos.name=="nt"else[]),"nvcc":["-DNVDR_TORCH","-lineinfo"],},)],cmdclass={"build_ext":BuildExtension},)五、编译成功现场（日志截图）
# 运行编译命令 python setup.py bdist_wheel[91/91] Linking build\lib.win-amd64-cpython-312\_nvdiffrast_c.cp312-win_amd64.pyd creating 'dist\nvdiffrast-0.4.0-cp312-cp312-win_amd64.whl' Successfully installed nvdiffrast-0.4.0六、安装与验证
pipinstalldist\nvdiffrast-0.4.0-cp312-cp312-win_amd64.whl python -c"import nvdiffrast.torch as nvr; print('✅', nvr.__file__)"输出示例：
✅ H:\YourComfyUI\.venv\Lib\site-packages\nvdiffrast\torch\__init__.py七、常见报错对照表（收藏级）
| 报错关键词 | 原因 | 一键修复 |
|---|---|---|
-CUDA version (13.1) mismatches PyTorch (12.6)- | -驱动 vs 编译版本检查- | -本文 MonkeyPatch - |
-cl.exe not found- | -未用 VS2022 x64 终端- | -开始菜单 → x64 Native Tools- |
-nvcc fatal : Unsupported gpu architecture 'compute_90'- | -CUDA 13 默认架构过高- | -已在setup_patch.py指定compute_86- |
-MSVC/cl.exe with traditional preprocessor is used- | -仅警告，可忽略- | -加/WX-不视为错误- |
八、一键脚本（失败→成功全流程）
保存为build_nvdiffrast.bat，右键管理员运行“x64 Native Tools Command Prompt for VS 2022”然后运行此脚本即可复现全文所有步骤：
@echo off title nvdiffrast-Windows-Build cd /d "%~dp0" call .venv\Scripts\activate echo [1/4] 克隆源码... git clone https://github.com/NVlabs/nvdiffrast.git cd nvdiffrast echo [2/4] 应用 MonkeyPatch... copy setup.py setup.py.bak python -c "import torch.utils.cpp_extension as _ext;_ext._check_cuda_version=lambda *a,**k:None" setup.py bdist_wheel echo [3/4] 安装 wheel... pip install dist\nvdiffrast-0.4.0-cp312-cp312-win_amd64.whl echo [4/4] 验证... python -c "import nvdiffrast.torch as nvr;print('✅',nvr.__file__)" pause九、系列交叉引用
- 第 0 篇（已发）：自定义光栅化器编译全记录
- 第 ① 篇（已发）：依赖安装完全指南
- 第 ③ 篇（明天发）：diso 编译实战 + 节点验证 + WF 演示
转载注明出处 → 博客标题 + 链接即可。
ComfyUI, Hunyuan3D, nvdiffrast, CUDA13.1, PyTorch12.6, 源码编译, setup.py, MonkeyPatch, RTX3090, Windows11
