{"id":38604,"date":"2025-05-20T17:44:06","date_gmt":"2025-05-20T09:44:06","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/38604.html"},"modified":"2025-05-20T17:44:06","modified_gmt":"2025-05-20T09:44:06","slug":"%e6%b7%b1%e5%ba%a6%e8%a7%a3%e6%9e%903d%e6%a8%a1%e5%9e%8b%e7%94%9f%e6%88%90%e5%99%a8%ef%bc%9a%e5%9f%ba%e4%ba%8estylegan3%e4%b8%8epytorch3d%e7%9a%84%e5%a4%9a%e9%a3%8e%e6%a0%bc%e7%94%9f%e6%88%90%e5%b7%a5","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/38604.html","title":{"rendered":"\u6df1\u5ea6\u89e3\u67903D\u6a21\u578b\u751f\u6210\u5668\uff1a\u57fa\u4e8eStyleGAN3\u4e0ePyTorch3D\u7684\u591a\u98ce\u683c\u751f\u6210\u5de5\u5177\u5f00\u53d1\u5b9e\u6218"},"content":{"rendered":"<h3>\u5f15\u8a00&#xff1a;\u8de8\u6a21\u6001\u751f\u6210\u7684\u9769\u547d\u6027\u7a81\u7834<\/h3>\n<p>\u5728\u5143\u5b87\u5b99\u4e0e\u6570\u5b57\u5b6a\u751f\u6280\u672f\u84ec\u52c3\u53d1\u5c55\u7684\u4eca\u5929&#xff0c;3D\u5185\u5bb9\u751f\u6210\u5df2\u6210\u4e3a\u5236\u7ea6\u4ea7\u4e1a\u53d1\u5c55\u7684\u5173\u952e\u74f6\u9888\u3002\u4f20\u7edf\u5efa\u6a21\u65b9\u5f0f\u4f9d\u8d56\u4e13\u4e1a\u8f6f\u4ef6\u548c\u4eba\u5de5\u64cd\u4f5c&#xff0c;\u800c\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u751f\u6210\u6a21\u578b\u6b63\u98a0\u8986\u8fd9\u4e00\u8303\u5f0f\u3002\u672c\u6587\u5c06\u6df1\u5165\u89e3\u6790\u5982\u4f55\u6784\u5efa\u652f\u6301\u591a\u98ce\u683c\u751f\u6210\u76843D\u6a21\u578b\u521b\u5efa\u5de5\u5177&#xff0c;\u6280\u672f\u6808\u6db5\u76d6StyleGAN3\u3001PyTorch3D\u548cBlender&#xff0c;\u6700\u7ec8\u5b9e\u73b0\u4ece\u6f5c\u5728\u7a7a\u95f4\u7f16\u7801\u5230\u53ef\u6e32\u67d33D\u8d44\u4ea7\u7684\u5b8c\u6574 pipeline\u3002<\/p>\n<h3>\u4e00\u3001\u6280\u672f\u539f\u7406\u4e0e\u67b6\u6784\u8bbe\u8ba1<\/h3>\n<h4>1.1 3D\u751f\u6210\u6a21\u578b\u7684\u6838\u5fc3\u6311\u6218<\/h4>\n<p>\u76f8\u8f83\u4e8e\u6210\u719f\u76842D\u751f\u6210\u6280\u672f&#xff0c;3D\u751f\u6210\u9762\u4e34\u4e09\u5927\u6280\u672f\u96be\u9898&#xff1a;<\/p>\n<ul>\n<li>\u51e0\u4f55\u4e00\u81f4\u6027&#xff1a;\u9700\u4fdd\u8bc1\u6a21\u578b\u62d3\u6251\u7ed3\u6784\u7684\u5408\u7406\u6027&#xff1b;<\/li>\n<li>\u591a\u89c6\u89d2\u8fde\u8d2f\u6027&#xff1a;\u4e0d\u540c\u89d2\u5ea6\u89c2\u5bdf\u9700\u4fdd\u6301\u89c6\u89c9\u8fde\u7eed\u6027&#xff1b;<\/li>\n<li>\u7269\u7406\u53ef\u6e32\u67d3\u6027&#xff1a;\u751f\u6210\u7ed3\u679c\u9700\u517c\u5bb9\u4e3b\u6d41\u6e32\u67d3\u5f15\u64ce\u3002<\/li>\n<\/ul>\n<h4>1.2 \u6280\u672f\u9009\u578b\u4f9d\u636e<\/h4>\n<table>\n<tr>\u7ec4\u4ef6\u6280\u672f\u9009\u578b\u6838\u5fc3\u4f18\u52bf<\/tr>\n<tbody>\n<tr>\n<td>\u751f\u6210\u6a21\u578b<\/td>\n<td>StyleGAN3<\/td>\n<td>\u6539\u8fdb\u7684\u5377\u79ef\u5c42\u8bbe\u8ba1\u63d0\u5347\u7eb9\u7406\u4e00\u81f4\u6027<\/td>\n<\/tr>\n<tr>\n<td>3D\u8868\u793a<\/td>\n<td>PyTorch3D<\/td>\n<td>\u5dee\u5f02\u5316\u6e32\u67d3\u4e0e\u53ef\u5fae\u5206\u64cd\u4f5c\u652f\u6301<\/td>\n<\/tr>\n<tr>\n<td>\u6e32\u67d3\u5f15\u64ce<\/td>\n<td>Blender<\/td>\n<td>\u5f00\u653eAPI\u4e0e\u7269\u7406\u7ea7\u6e32\u67d3\u80fd\u529b<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4>1.3 \u7cfb\u7edf\u67b6\u6784\u56fe<\/h4>\n<p>\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510<br \/>\n\u2502  \u7528\u6237\u4ea4\u4e92\u754c\u9762  \u2502<br \/>\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518<br \/>\n        \u2502<br \/>\n\u25bc<br \/>\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510<br \/>\n\u2502  StyleGAN3\u6838\u5fc3  \u2502 \u2190 \u591a\u98ce\u683c\u6f5c\u5728\u7a7a\u95f4<br \/>\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524<br \/>\n\u2502  3D\u8868\u793a\u5b66\u4e60\u5c42  \u2502 \u2192 \u9690\u5f0f\u66f2\u9762\u8868\u793a<br \/>\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524<br \/>\n\u2502  PyTorch3D\u6e32\u67d3 \u2502 \u2192 \u53ef\u5fae\u5206\u6e32\u67d3\u7ba1\u7ebf<br \/>\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518<br \/>\n        \u2502<br \/>\n\u25bc<br \/>\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510<br \/>\n\u2502  Blender\u96c6\u6210\u5c42 \u2502 \u2190 \u6a21\u578b\u5bfc\u51fa\u63d2\u4ef6<br \/>\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518<\/p>\n<h3>\u4e8c\u3001\u5f00\u53d1\u73af\u5883\u642d\u5efa\u4e0e\u6570\u636e\u51c6\u5907<\/h3>\n<h4>2.1 \u57fa\u7840\u73af\u5883\u914d\u7f6e<\/h4>\n<p><span class=\"token comment\"># \u521b\u5efa\u9694\u79bb\u73af\u5883<\/span><br \/>\nconda create -n 3dgan <span class=\"token assign-left variable\">python<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token number\">3.9<\/span><br \/>\nconda activate 3dgan<\/p>\n<p><span class=\"token comment\"># \u6838\u5fc3\u4f9d\u8d56\u5b89\u88c5<\/span><br \/>\npip <span class=\"token function\">install<\/span> <span class=\"token assign-left variable\">torch<\/span><span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">1.13<\/span>.1 <span class=\"token assign-left variable\">torchvision<\/span><span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">0.14<\/span>.1<br \/>\npip <span class=\"token function\">install<\/span> <span class=\"token assign-left variable\">pytorch3d<\/span><span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">0.7<\/span>.2<br \/>\npip <span class=\"token function\">install<\/span> blender-api<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">0.0<\/span>.8  <span class=\"token comment\"># \u9700\u4e0eBlender\u7248\u672c\u5339\u914d<\/span><\/p>\n<h4>2.2 \u6570\u636e\u96c6\u6784\u5efa\u89c4\u8303<\/h4>\n<p>\u63a8\u8350\u4f7f\u7528ShapeNet Core\u6570\u636e\u96c6&#xff0c;\u9700\u8fdb\u884c\u4ee5\u4e0b\u9884\u5904\u7406&#xff1a;<\/p>\n<p><span class=\"token keyword\">from<\/span> torchvision<span class=\"token punctuation\">.<\/span>io <span class=\"token keyword\">import<\/span> read_image<br \/>\n<span class=\"token keyword\">from<\/span> pytorch3d<span class=\"token punctuation\">.<\/span>io <span class=\"token keyword\">import<\/span> load_obj<\/p>\n<p><span class=\"token keyword\">class<\/span> <span class=\"token class-name\">ShapeNetDataset<\/span><span class=\"token punctuation\">(<\/span>Dataset<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token keyword\">def<\/span> <span class=\"token function\">__init__<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">,<\/span> root_dir<span class=\"token punctuation\">,<\/span> transforms<span class=\"token operator\">&#061;<\/span><span class=\"token boolean\">None<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        self<span class=\"token punctuation\">.<\/span>root_dir <span class=\"token operator\">&#061;<\/span> root_dir<br \/>\n        self<span class=\"token punctuation\">.<\/span>transforms <span class=\"token operator\">&#061;<\/span> transforms<br \/>\n        self<span class=\"token punctuation\">.<\/span>meshes <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">]<\/span><\/p>\n<p>        <span class=\"token comment\"># \u9012\u5f52\u626b\u63cfOBJ\u6587\u4ef6<\/span><br \/>\n        <span class=\"token keyword\">for<\/span> dirpath<span class=\"token punctuation\">,<\/span> _<span class=\"token punctuation\">,<\/span> filenames <span class=\"token keyword\">in<\/span> os<span class=\"token punctuation\">.<\/span>walk<span class=\"token punctuation\">(<\/span>root_dir<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n            <span class=\"token keyword\">for<\/span> filename <span class=\"token keyword\">in<\/span> filenames<span class=\"token punctuation\">:<\/span><br \/>\n                <span class=\"token keyword\">if<\/span> filename<span class=\"token punctuation\">.<\/span>endswith<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#034;.obj&#034;<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n                    mesh_path <span class=\"token operator\">&#061;<\/span> os<span class=\"token punctuation\">.<\/span>path<span class=\"token punctuation\">.<\/span>join<span class=\"token punctuation\">(<\/span>dirpath<span class=\"token punctuation\">,<\/span> filename<span class=\"token punctuation\">)<\/span><br \/>\n                    self<span class=\"token punctuation\">.<\/span>meshes<span class=\"token punctuation\">.<\/span>append<span class=\"token punctuation\">(<\/span>mesh_path<span class=\"token punctuation\">)<\/span><\/p>\n<p>    <span class=\"token keyword\">def<\/span> <span class=\"token function\">__len__<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token keyword\">return<\/span> <span class=\"token builtin\">len<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">.<\/span>meshes<span class=\"token punctuation\">)<\/span><\/p>\n<p>    <span class=\"token keyword\">def<\/span> <span class=\"token function\">__getitem__<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">,<\/span> idx<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        mesh <span class=\"token operator\">&#061;<\/span> load_obj<span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">.<\/span>meshes<span class=\"token punctuation\">[<\/span>idx<span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        <span class=\"token comment\"># \u6807\u51c6\u5316\u5904\u7406<\/span><br \/>\n        verts <span class=\"token operator\">&#061;<\/span> mesh<span class=\"token punctuation\">.<\/span>verts_packed<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        verts_centered <span class=\"token operator\">&#061;<\/span> verts <span class=\"token operator\">&#8211;<\/span> verts<span class=\"token punctuation\">.<\/span>mean<span class=\"token punctuation\">(<\/span>dim<span class=\"token operator\">&#061;<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        scale <span class=\"token operator\">&#061;<\/span> verts_centered<span class=\"token punctuation\">.<\/span><span class=\"token builtin\">abs<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span><span class=\"token builtin\">max<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        verts_normalized <span class=\"token operator\">&#061;<\/span> verts_centered <span class=\"token operator\">\/<\/span> scale<br \/>\n        <span class=\"token keyword\">return<\/span> verts_normalized<\/p>\n<h3>\u4e09\u3001StyleGAN3\u5fae\u8c03\u4e0e3D\u8868\u793a\u5b66\u4e60<\/h3>\n<h4>3.1 \u6a21\u578b\u67b6\u6784\u6539\u8fdb<\/h4>\n<p>\u5728\u539f\u59cbStyleGAN3\u57fa\u7840\u4e0a\u589e\u52a03D\u611f\u77e5\u6a21\u5757&#xff1a;<\/p>\n<p><span class=\"token keyword\">class<\/span> <span class=\"token class-name\">StyleGAN3D<\/span><span class=\"token punctuation\">(<\/span>nn<span class=\"token punctuation\">.<\/span>Module<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token keyword\">def<\/span> <span class=\"token function\">__init__<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">,<\/span> z_dim<span class=\"token operator\">&#061;<\/span><span class=\"token number\">512<\/span><span class=\"token punctuation\">,<\/span> channel_base<span class=\"token operator\">&#061;<\/span><span class=\"token number\">32768<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token builtin\">super<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span>__init__<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        <span class=\"token comment\"># \u539f\u59cbStyleGAN3\u751f\u6210\u5668<\/span><br \/>\n        self<span class=\"token punctuation\">.<\/span>stylegan <span class=\"token operator\">&#061;<\/span> StyleGAN3Generator<span class=\"token punctuation\">(<\/span>z_dim<span class=\"token punctuation\">,<\/span> channel_base<span class=\"token punctuation\">)<\/span><\/p>\n<p>        <span class=\"token comment\"># \u65b0\u589e3D\u6295\u5f71\u5c42<\/span><br \/>\n        self<span class=\"token punctuation\">.<\/span>projection_head <span class=\"token operator\">&#061;<\/span> nn<span class=\"token punctuation\">.<\/span>Sequential<span class=\"token punctuation\">(<\/span><br \/>\n            EqualLinear<span class=\"token punctuation\">(<\/span>z_dim<span class=\"token punctuation\">,<\/span> <span class=\"token number\">256<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span><br \/>\n            nn<span class=\"token punctuation\">.<\/span>LeakyReLU<span class=\"token punctuation\">(<\/span><span class=\"token number\">0.2<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span><br \/>\n            EqualLinear<span class=\"token punctuation\">(<\/span><span class=\"token number\">256<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">3<\/span><span class=\"token punctuation\">)<\/span>  <span class=\"token comment\"># \u8f93\u51faXYZ\u5750\u6807\u504f\u79fb<\/span><br \/>\n        <span class=\"token punctuation\">)<\/span><\/p>\n<p>    <span class=\"token keyword\">def<\/span> <span class=\"token function\">forward<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">,<\/span> styles<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        img <span class=\"token operator\">&#061;<\/span> self<span class=\"token punctuation\">.<\/span>stylegan<span class=\"token punctuation\">(<\/span>styles<span class=\"token punctuation\">)<\/span><br \/>\n        depth_map <span class=\"token operator\">&#061;<\/span> self<span class=\"token punctuation\">.<\/span>projection_head<span class=\"token punctuation\">(<\/span>styles<span class=\"token punctuation\">)<\/span><br \/>\n        <span class=\"token keyword\">return<\/span> img<span class=\"token punctuation\">,<\/span> depth_map<\/p>\n<h4>3.2 \u8bad\u7ec3\u6d41\u7a0b\u4f18\u5316<\/h4>\n<p><span class=\"token comment\"># \u6df7\u5408\u635f\u5931\u51fd\u6570\u8bbe\u8ba1<\/span><br \/>\nloss <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">(<\/span><br \/>\n    w_adv <span class=\"token operator\">*<\/span> adversarial_loss <span class=\"token operator\">&#043;<\/span><br \/>\n    w_depth <span class=\"token operator\">*<\/span> depth_consistency_loss <span class=\"token operator\">&#043;<\/span><br \/>\n    w_lap <span class=\"token operator\">*<\/span> laplacian_smoothness<br \/>\n<span class=\"token punctuation\">)<\/span><\/p>\n<p><span class=\"token comment\"># \u591a\u5c3a\u5ea6\u5224\u522b\u5668\u67b6\u6784<\/span><br \/>\ndiscriminators <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><br \/>\n    Discriminator<span class=\"token punctuation\">(<\/span>input_resolution<span class=\"token operator\">&#061;<\/span><span class=\"token number\">256<\/span><span class=\"token punctuation\">,<\/span> channel_multiplier<span class=\"token operator\">&#061;<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span><br \/>\n    Discriminator<span class=\"token punctuation\">(<\/span>input_resolution<span class=\"token operator\">&#061;<\/span><span class=\"token number\">128<\/span><span class=\"token punctuation\">,<\/span> channel_multiplier<span class=\"token operator\">&#061;<\/span><span class=\"token number\">4<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span><br \/>\n    Discriminator<span class=\"token punctuation\">(<\/span>input_resolution<span class=\"token operator\">&#061;<\/span><span class=\"token number\">64<\/span><span class=\"token punctuation\">,<\/span> channel_multiplier<span class=\"token operator\">&#061;<\/span><span class=\"token number\">8<\/span><span class=\"token punctuation\">)<\/span><br \/>\n<span class=\"token punctuation\">]<\/span><\/p>\n<h3>\u56db\u30013D\u6a21\u578b\u5bfc\u51fa\u4e0eBlender\u96c6\u6210<\/h3>\n<h4>4.1 PyTorch3D\u5230OBJ\u683c\u5f0f\u8f6c\u6362<\/h4>\n<p><span class=\"token keyword\">def<\/span> <span class=\"token function\">export_to_obj<\/span><span class=\"token punctuation\">(<\/span>verts<span class=\"token punctuation\">,<\/span> faces<span class=\"token punctuation\">,<\/span> output_path<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token keyword\">with<\/span> <span class=\"token builtin\">open<\/span><span class=\"token punctuation\">(<\/span>output_path<span class=\"token punctuation\">,<\/span> <span class=\"token string\">&#039;w&#039;<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token keyword\">as<\/span> f<span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token comment\"># \u9876\u70b9\u5199\u5165<\/span><br \/>\n        <span class=\"token keyword\">for<\/span> v <span class=\"token keyword\">in<\/span> verts<span class=\"token punctuation\">:<\/span><br \/>\n            f<span class=\"token punctuation\">.<\/span>write<span class=\"token punctuation\">(<\/span><span class=\"token string-interpolation\"><span class=\"token string\">f&#034;v <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>v<span class=\"token punctuation\">[<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">:<\/span><span class=\"token format-spec\">.6f<\/span><span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\"> <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>v<span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">:<\/span><span class=\"token format-spec\">.6f<\/span><span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\"> <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>v<span class=\"token punctuation\">[<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">:<\/span><span class=\"token format-spec\">.6f<\/span><span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\">\\\\n&#034;<\/span><\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>        <span class=\"token comment\"># \u9762\u7247\u5199\u5165<\/span><br \/>\n        <span class=\"token keyword\">for<\/span> f <span class=\"token keyword\">in<\/span> faces<span class=\"token punctuation\">:<\/span><br \/>\n            f<span class=\"token punctuation\">.<\/span>write<span class=\"token punctuation\">(<\/span><span class=\"token string-interpolation\"><span class=\"token string\">f&#034;f <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>f<span class=\"token punctuation\">[<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">]<\/span><span class=\"token operator\">&#043;<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\"> <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>f<span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">]<\/span><span class=\"token operator\">&#043;<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\"> <\/span><span class=\"token interpolation\"><span class=\"token punctuation\">{<\/span>f<span class=\"token punctuation\">[<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">]<\/span><span class=\"token operator\">&#043;<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">}<\/span><\/span><span class=\"token string\">\\\\n&#034;<\/span><\/span><span class=\"token punctuation\">)<\/span><\/p>\n<h4>4.2 Blender\u63d2\u4ef6\u5f00\u53d1\u8981\u70b9<\/h4>\n<p><span class=\"token keyword\">import<\/span> bpy<br \/>\n<span class=\"token keyword\">from<\/span> mathutils <span class=\"token keyword\">import<\/span> Vector<\/p>\n<p><span class=\"token keyword\">class<\/span> <span class=\"token class-name\">MeshExporterOperator<\/span><span class=\"token punctuation\">(<\/span>bpy<span class=\"token punctuation\">.<\/span>types<span class=\"token punctuation\">.<\/span>Operator<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    bl_idname <span class=\"token operator\">&#061;<\/span> <span class=\"token string\">&#034;export.generated_mesh&#034;<\/span><br \/>\n    bl_label <span class=\"token operator\">&#061;<\/span> <span class=\"token string\">&#034;Export Generated Mesh&#034;<\/span><\/p>\n<p>    <span class=\"token keyword\">def<\/span> <span class=\"token function\">execute<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">,<\/span> context<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token comment\"># \u4ecePyTorch3D\u83b7\u53d6\u6570\u636e<\/span><br \/>\n        verts<span class=\"token punctuation\">,<\/span> faces <span class=\"token operator\">&#061;<\/span> get_latest_generation<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>        <span class=\"token comment\"># \u521b\u5efaBlender\u7f51\u683c<\/span><br \/>\n        mesh <span class=\"token operator\">&#061;<\/span> bpy<span class=\"token punctuation\">.<\/span>data<span class=\"token punctuation\">.<\/span>meshes<span class=\"token punctuation\">.<\/span>new<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#034;GeneratedMesh&#034;<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        mesh<span class=\"token punctuation\">.<\/span>from_pydata<span class=\"token punctuation\">(<\/span>verts<span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> faces<span class=\"token punctuation\">)<\/span><br \/>\n        mesh<span class=\"token punctuation\">.<\/span>update<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>        <span class=\"token comment\"># \u521b\u5efa\u7269\u4f53<\/span><br \/>\n        obj <span class=\"token operator\">&#061;<\/span> bpy<span class=\"token punctuation\">.<\/span>data<span class=\"token punctuation\">.<\/span>objects<span class=\"token punctuation\">.<\/span>new<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#034;GeneratedObject&#034;<\/span><span class=\"token punctuation\">,<\/span> mesh<span class=\"token punctuation\">)<\/span><br \/>\n        context<span class=\"token punctuation\">.<\/span>collection<span class=\"token punctuation\">.<\/span>objects<span class=\"token punctuation\">.<\/span>link<span class=\"token punctuation\">(<\/span>obj<span class=\"token punctuation\">)<\/span><\/p>\n<p>        <span class=\"token keyword\">return<\/span> <span class=\"token punctuation\">{<\/span><span class=\"token string\">&#039;FINISHED&#039;<\/span><span class=\"token punctuation\">}<\/span><\/p>\n<h3>\u4e94\u3001\u591a\u98ce\u683c\u751f\u6210\u7cfb\u7edf\u5b9e\u73b0<\/h3>\n<h4>5.1 \u6f5c\u5728\u7a7a\u95f4\u63d2\u503c\u7b97\u6cd5<\/h4>\n<p><span class=\"token keyword\">def<\/span> <span class=\"token function\">style_interpolation<\/span><span class=\"token punctuation\">(<\/span>w1<span class=\"token punctuation\">,<\/span> w2<span class=\"token punctuation\">,<\/span> alpha<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token comment\"># \u7403\u9762\u63d2\u503c<\/span><br \/>\n    w_interp <span class=\"token operator\">&#061;<\/span> slerp<span class=\"token punctuation\">(<\/span>w1<span class=\"token punctuation\">,<\/span> w2<span class=\"token punctuation\">,<\/span> alpha<span class=\"token punctuation\">)<\/span><\/p>\n<p>    <span class=\"token comment\"># \u98ce\u683c\u6df7\u5408\u5c42<\/span><br \/>\n    mixed_style <span class=\"token operator\">&#061;<\/span> mixing_cutoff<span class=\"token punctuation\">(<\/span>w_interp<span class=\"token punctuation\">,<\/span> num_layers<span class=\"token operator\">&#061;<\/span><span class=\"token number\">14<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token keyword\">return<\/span> mixed_style<\/p>\n<h4>5.2 \u98ce\u683c\u63a7\u5236\u9762\u677f\u5b9e\u73b0<\/h4>\n<p><span class=\"token keyword\">import<\/span> ipywidgets <span class=\"token keyword\">as<\/span> widgets<\/p>\n<p>style_slider <span class=\"token operator\">&#061;<\/span> widgets<span class=\"token punctuation\">.<\/span>FloatSlider<span class=\"token punctuation\">(<\/span><br \/>\n    value<span class=\"token operator\">&#061;<\/span><span class=\"token number\">0.5<\/span><span class=\"token punctuation\">,<\/span><br \/>\n    <span class=\"token builtin\">min<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token number\">0.0<\/span><span class=\"token punctuation\">,<\/span><br \/>\n    <span class=\"token builtin\">max<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token number\">1.0<\/span><span class=\"token punctuation\">,<\/span><br \/>\n    step<span class=\"token operator\">&#061;<\/span><span class=\"token number\">0.01<\/span><span class=\"token punctuation\">,<\/span><br \/>\n    description<span class=\"token operator\">&#061;<\/span><span class=\"token string\">&#034;Style Mix:&#034;<\/span><br \/>\n<span class=\"token punctuation\">)<\/span><\/p>\n<p><span class=\"token keyword\">def<\/span> <span class=\"token function\">update_style<\/span><span class=\"token punctuation\">(<\/span>change<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    generated_mesh <span class=\"token operator\">&#061;<\/span> generate_mesh<span class=\"token punctuation\">(<\/span>style_slider<span class=\"token punctuation\">.<\/span>value<span class=\"token punctuation\">)<\/span><br \/>\n    display_mesh<span class=\"token punctuation\">(<\/span>generated_mesh<span class=\"token punctuation\">)<\/span><\/p>\n<p>style_slider<span class=\"token punctuation\">.<\/span>observe<span class=\"token punctuation\">(<\/span>update_style<span class=\"token punctuation\">,<\/span> names<span class=\"token operator\">&#061;<\/span><span class=\"token string\">&#039;value&#039;<\/span><span class=\"token punctuation\">)<\/span><br \/>\ndisplay<span class=\"token punctuation\">(<\/span>style_slider<span class=\"token punctuation\">)<\/span><\/p>\n<h3>\u516d\u3001\u7cfb\u7edf\u4f18\u5316\u4e0e\u6027\u80fd\u8c03\u4f18<\/h3>\n<h4>6.1 \u8bad\u7ec3\u52a0\u901f\u7b56\u7565<\/h4>\n<table>\n<tr>\u6280\u672f\u52a0\u901f\u6bd4\u5b9e\u65bd\u8981\u70b9<\/tr>\n<tbody>\n<tr>\n<td>\u6df7\u5408\u7cbe\u5ea6\u8bad\u7ec3<\/td>\n<td>2.1x<\/td>\n<td>\u4f7f\u7528torch.cuda.amp<\/td>\n<\/tr>\n<tr>\n<td>\u6e10\u8fdb\u5f0f\u5206\u8fa8\u7387\u8bad\u7ec3<\/td>\n<td>1.8x<\/td>\n<td>\u4ece64&#215;64\u9010\u6b65\u5347\u81f31024&#215;1024<\/td>\n<\/tr>\n<tr>\n<td>\u6a21\u578b\u5e76\u884c<\/td>\n<td>3.4x<\/td>\n<td>\u7ed3\u5408PyTorch FSDP<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4>6.2 \u5185\u5b58\u4f18\u5316\u6280\u5de7<\/h4>\n<p><span class=\"token comment\"># \u4f7f\u7528PyTorch3D\u7684\u5185\u5b58\u4f18\u5316\u91c7\u6837\u5668<\/span><br \/>\n<span class=\"token keyword\">from<\/span> pytorch3d<span class=\"token punctuation\">.<\/span>ops <span class=\"token keyword\">import<\/span> sample_points_from_meshes<\/p>\n<p><span class=\"token keyword\">def<\/span> <span class=\"token function\">optimized_sampling<\/span><span class=\"token punctuation\">(<\/span>mesh<span class=\"token punctuation\">,<\/span> num_samples<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token comment\"># \u5206\u6279\u6b21\u91c7\u6837\u907f\u514d\u5185\u5b58\u6ea2\u51fa<\/span><br \/>\n    batch_size <span class=\"token operator\">&#061;<\/span> <span class=\"token number\">1024<\/span><br \/>\n    points <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">]<\/span><br \/>\n    <span class=\"token keyword\">for<\/span> i <span class=\"token keyword\">in<\/span> <span class=\"token builtin\">range<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">,<\/span> num_samples<span class=\"token punctuation\">,<\/span> batch_size<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        batch_points <span class=\"token operator\">&#061;<\/span> sample_points_from_meshes<span class=\"token punctuation\">(<\/span><br \/>\n            mesh<span class=\"token punctuation\">,<\/span><br \/>\n            num_samples<span class=\"token operator\">&#061;<\/span><span class=\"token builtin\">min<\/span><span class=\"token punctuation\">(<\/span>batch_size<span class=\"token punctuation\">,<\/span> num_samples<span class=\"token operator\">&#8211;<\/span>i<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span><br \/>\n            return_normals<span class=\"token operator\">&#061;<\/span><span class=\"token boolean\">False<\/span><br \/>\n        <span class=\"token punctuation\">)<\/span><br \/>\n        points<span class=\"token punctuation\">.<\/span>append<span class=\"token punctuation\">(<\/span>batch_points<span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token keyword\">return<\/span> torch<span class=\"token punctuation\">.<\/span>cat<span class=\"token punctuation\">(<\/span>points<span class=\"token punctuation\">,<\/span> dim<span class=\"token operator\">&#061;<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<h3>\u4e03\u3001\u5e94\u7528\u573a\u666f\u4e0e\u6548\u679c\u5c55\u793a<\/h3>\n<h4>7.1 \u5de5\u4e1a\u8bbe\u8ba1\u5e94\u7528<\/h4>\n<p><span class=\"token comment\"># \u6c7d\u8f66\u8bbe\u8ba1\u98ce\u683c\u8fc1\u79fb\u793a\u4f8b<\/span><br \/>\n<span class=\"token keyword\">def<\/span> <span class=\"token function\">automotive_style_transfer<\/span><span class=\"token punctuation\">(<\/span>base_model<span class=\"token punctuation\">,<\/span> target_style<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token comment\"># \u63d0\u53d6\u98ce\u683c\u7f16\u7801<\/span><br \/>\n    style_code <span class=\"token operator\">&#061;<\/span> style_encoder<span class=\"token punctuation\">(<\/span>target_style<span class=\"token punctuation\">)<\/span><\/p>\n<p>    <span class=\"token comment\"># \u6267\u884c\u98ce\u683c\u8fc1\u79fb<\/span><br \/>\n    transferred_mesh <span class=\"token operator\">&#061;<\/span> style_transfer_network<span class=\"token punctuation\">(<\/span>base_model<span class=\"token punctuation\">,<\/span> style_code<span class=\"token punctuation\">)<\/span><\/p>\n<p>    <span class=\"token keyword\">return<\/span> transferred_mesh<\/p>\n<h4>7.2 \u6e38\u620f\u8d44\u4ea7\u751f\u6210<\/h4>\n<p><span class=\"token comment\"># LOD&#xff08;\u7ec6\u8282\u5c42\u6b21&#xff09;\u751f\u6210\u7cfb\u7edf<\/span><br \/>\n<span class=\"token keyword\">def<\/span> <span class=\"token function\">generate_lod_chain<\/span><span class=\"token punctuation\">(<\/span>base_mesh<span class=\"token punctuation\">,<\/span> lod_levels<span class=\"token operator\">&#061;<\/span><span class=\"token number\">4<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    lod_chain <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span>base_mesh<span class=\"token punctuation\">]<\/span><br \/>\n    current_mesh <span class=\"token operator\">&#061;<\/span> base_mesh<\/p>\n<p>    <span class=\"token keyword\">for<\/span> _ <span class=\"token keyword\">in<\/span> <span class=\"token builtin\">range<\/span><span class=\"token punctuation\">(<\/span>lod_levels<span class=\"token operator\">&#8211;<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token comment\"># \u4f7f\u7528Quadric\u8bef\u5dee\u5ea6\u91cf\u8fdb\u884c\u7b80\u5316<\/span><br \/>\n        simplified_mesh <span class=\"token operator\">&#061;<\/span> simplify_mesh<span class=\"token punctuation\">(<\/span>current_mesh<span class=\"token punctuation\">,<\/span> ratio<span class=\"token operator\">&#061;<\/span><span class=\"token number\">0.7<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        lod_chain<span class=\"token punctuation\">.<\/span>append<span class=\"token punctuation\">(<\/span>simplified_mesh<span class=\"token punctuation\">)<\/span><br \/>\n        current_mesh <span class=\"token operator\">&#061;<\/span> simplified_mesh<\/p>\n<p>    <span class=\"token keyword\">return<\/span> lod_chain<\/p>\n<h3>\u516b\u3001\u90e8\u7f72\u4e0e\u5b9e\u6218\u5efa\u8bae<\/h3>\n<h4>8.1 \u4e91\u7aef\u90e8\u7f72\u65b9\u6848<\/h4>\n<p><span class=\"token comment\"># Kubernetes\u90e8\u7f72\u914d\u7f6e\u793a\u4f8b<\/span><br \/>\n<span class=\"token key atrule\">apiVersion<\/span><span class=\"token punctuation\">:<\/span> apps\/v1<br \/>\n<span class=\"token key atrule\">kind<\/span><span class=\"token punctuation\">:<\/span> Deployment<br \/>\n<span class=\"token key atrule\">metadata<\/span><span class=\"token punctuation\">:<\/span><br \/>\n  <span class=\"token key atrule\">name<\/span><span class=\"token punctuation\">:<\/span> 3d<span class=\"token punctuation\">&#8211;<\/span>generator<br \/>\n<span class=\"token key atrule\">spec<\/span><span class=\"token punctuation\">:<\/span><br \/>\n  <span class=\"token key atrule\">replicas<\/span><span class=\"token punctuation\">:<\/span> <span class=\"token number\">4<\/span><br \/>\n  <span class=\"token key atrule\">selector<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token key atrule\">matchLabels<\/span><span class=\"token punctuation\">:<\/span><br \/>\n      <span class=\"token key atrule\">app<\/span><span class=\"token punctuation\">:<\/span> 3d<span class=\"token punctuation\">&#8211;<\/span>generator<br \/>\n  <span class=\"token key atrule\">template<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token key atrule\">metadata<\/span><span class=\"token punctuation\">:<\/span><br \/>\n      <span class=\"token key atrule\">labels<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token key atrule\">app<\/span><span class=\"token punctuation\">:<\/span> 3d<span class=\"token punctuation\">&#8211;<\/span>generator<br \/>\n    <span class=\"token key atrule\">spec<\/span><span class=\"token punctuation\">:<\/span><br \/>\n      <span class=\"token key atrule\">containers<\/span><span class=\"token punctuation\">:<\/span><br \/>\n      <span class=\"token punctuation\">&#8211;<\/span> <span class=\"token key atrule\">name<\/span><span class=\"token punctuation\">:<\/span> generator<br \/>\n        <span class=\"token key atrule\">image<\/span><span class=\"token punctuation\">:<\/span> your_registry\/3d<span class=\"token punctuation\">&#8211;<\/span>generator<span class=\"token punctuation\">:<\/span>latest<br \/>\n        <span class=\"token key atrule\">resources<\/span><span class=\"token punctuation\">:<\/span><br \/>\n          <span class=\"token key atrule\">limits<\/span><span class=\"token punctuation\">:<\/span><br \/>\n            <span class=\"token key atrule\">nvidia.com\/gpu<\/span><span class=\"token punctuation\">:<\/span> <span class=\"token number\">1<\/span><\/p>\n<h4>8.2 \u5e38\u89c1\u95ee\u9898\u89e3\u51b3<\/h4>\n<li>\u51e0\u4f55\u7578\u53d8\u95ee\u9898&#xff1a;\n<ul>\n<li>\u89e3\u51b3\u65b9\u6848&#xff1a;\u589e\u52a0\u62c9\u666e\u62c9\u65af\u5e73\u6ed1\u635f\u5931\u9879&#xff1b;<\/li>\n<li>\u53c2\u6570\u8c03\u6574&#xff1a;\u03bb_laplacian&#061;0.001\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\u6e32\u67d3\u4f2a\u5f71&#xff1a;\n<ul>\n<li>\u68c0\u67e5\u70b9&#xff1a;\u786e\u4fddUV\u6620\u5c04\u6b63\u786e\u6027&#xff1b;<\/li>\n<li>\u4fee\u590d\u65b9\u6cd5&#xff1a;\u6dfb\u52a0UV\u5c55\u5f00\u9884\u5904\u7406\u5c42\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\u8de8\u5e73\u53f0\u517c\u5bb9\u6027&#xff1a;\n<ul>\n<li>\u5173\u952e\u70b9&#xff1a;\u7edf\u4e00\u4f7f\u7528\u53f3\u624b\u5750\u6807\u7cfb&#xff1b;<\/li>\n<li>\u9a8c\u8bc1\u65b9\u6cd5&#xff1a;\u5b9e\u65bd\u5750\u6807\u7cfb\u4e00\u81f4\u6027\u68c0\u67e5\u3002<\/li>\n<\/ul>\n<\/li>\n<h3>\u4e5d\u3001\u672a\u6765\u5c55\u671b\u4e0e\u6280\u672f\u6f14\u8fdb<\/h3>\n<h4>9.1 \u524d\u6cbf\u6280\u672f\u878d\u5408\u65b9\u5411<\/h4>\n<ul>\n<li>NeRF\u96c6\u6210&#xff1a;\u5c06\u751f\u6210\u6a21\u578b\u4e0e\u795e\u7ecf\u8f90\u5c04\u573a\u7ed3\u5408&#xff0c;\u5b9e\u73b0\u52a8\u60013D\u5185\u5bb9\u751f\u6210&#xff1b;<\/li>\n<li>\u7269\u7406\u6a21\u62df&#xff1a;\u901a\u8fc7\u53ef\u5fae\u5206\u7269\u7406\u5f15\u64ce\u5b9e\u73b0\u6750\u8d28\u5c5e\u6027\u5b66\u4e60&#xff1b;<\/li>\n<li>AR\/VR\u9002\u914d&#xff1a;\u5f00\u53d1\u8f7b\u91cf\u5316\u7248\u672c\u652f\u6301\u79fb\u52a8\u7aef\u5b9e\u65f6\u751f\u6210\u3002<\/li>\n<\/ul>\n<h4>9.2 \u884c\u4e1a\u5f71\u54cd\u9884\u6d4b<\/h4>\n<p>\u9884\u8ba1\u672a\u67653\u5e74\u5185&#xff1a;<\/p>\n<ul>\n<li>\u6e38\u620f\u5f00\u53d1\u6210\u672c\u964d\u4f4e60%&#xff1b;<\/li>\n<li>\u5de5\u4e1a\u8bbe\u8ba1\u5468\u671f\u7f29\u77ed75%&#xff1b;<\/li>\n<li>\u6570\u5b57\u4eba\u5236\u4f5c\u6548\u7387\u63d0\u534710\u500d\u3002<\/li>\n<\/ul>\n<h3>\u5341\u3001\u5b8c\u6574\u4ee3\u7801\u5b9e\u73b0<\/h3>\n<p><span class=\"token comment\"># \u5b8c\u6574\u8bad\u7ec3\u6d41\u7a0b\u793a\u4f8b<\/span><br \/>\n<span class=\"token keyword\">def<\/span> <span class=\"token function\">train_3dgan<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token comment\"># \u521d\u59cb\u5316\u7ec4\u4ef6<\/span><br \/>\n    generator <span class=\"token operator\">&#061;<\/span> StyleGAN3D<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span>cuda<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    discriminator <span class=\"token operator\">&#061;<\/span> MultiScaleDiscriminator<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span>cuda<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    optimizer_g <span class=\"token operator\">&#061;<\/span> torch<span class=\"token punctuation\">.<\/span>optim<span class=\"token punctuation\">.<\/span>Adam<span class=\"token punctuation\">(<\/span>generator<span class=\"token punctuation\">.<\/span>parameters<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span> lr<span class=\"token operator\">&#061;<\/span><span class=\"token number\">0.002<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    optimizer_d <span class=\"token operator\">&#061;<\/span> torch<span class=\"token punctuation\">.<\/span>optim<span class=\"token punctuation\">.<\/span>Adam<span class=\"token punctuation\">(<\/span>discriminator<span class=\"token punctuation\">.<\/span>parameters<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span> lr<span class=\"token operator\">&#061;<\/span><span class=\"token number\">0.002<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>    <span class=\"token comment\"># \u4e3b\u8bad\u7ec3\u5faa\u73af<\/span><br \/>\n    <span class=\"token keyword\">for<\/span> epoch <span class=\"token keyword\">in<\/span> <span class=\"token builtin\">range<\/span><span class=\"token punctuation\">(<\/span>num_epochs<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token keyword\">for<\/span> real_data <span class=\"token keyword\">in<\/span> dataloader<span class=\"token punctuation\">:<\/span><br \/>\n            <span class=\"token comment\"># \u751f\u6210\u4f2a\u6570\u636e<\/span><br \/>\n            z <span class=\"token operator\">&#061;<\/span> torch<span class=\"token punctuation\">.<\/span>randn<span class=\"token punctuation\">(<\/span>batch_size<span class=\"token punctuation\">,<\/span> <span class=\"token number\">512<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span>cuda<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n            fake_data <span class=\"token operator\">&#061;<\/span> generator<span class=\"token punctuation\">(<\/span>z<span class=\"token punctuation\">)<\/span><\/p>\n<p>            <span class=\"token comment\"># \u5224\u522b\u5668\u8bad\u7ec3<\/span><br \/>\n            d_loss <span class=\"token operator\">&#061;<\/span> adversarial_loss<span class=\"token punctuation\">(<\/span>discriminator<span class=\"token punctuation\">,<\/span> real_data<span class=\"token punctuation\">,<\/span> fake_data<span class=\"token punctuation\">)<\/span><br \/>\n            d_loss<span class=\"token punctuation\">.<\/span>backward<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n            optimizer_d<span class=\"token punctuation\">.<\/span>step<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>            <span class=\"token comment\"># \u751f\u6210\u5668\u8bad\u7ec3<\/span><br \/>\n            g_loss <span class=\"token operator\">&#061;<\/span> generator_loss<span class=\"token punctuation\">(<\/span>discriminator<span class=\"token punctuation\">,<\/span> fake_data<span class=\"token punctuation\">)<\/span><br \/>\n            g_loss<span class=\"token punctuation\">.<\/span>backward<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n            optimizer_g<span class=\"token punctuation\">.<\/span>step<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>        <span class=\"token comment\"># \u5b9a\u671f\u4fdd\u5b58\u68c0\u67e5\u70b9<\/span><br \/>\n        <span class=\"token keyword\">if<\/span> epoch <span class=\"token operator\">%<\/span> save_interval <span class=\"token operator\">&#061;&#061;<\/span> 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