{"id":70466,"date":"2026-02-01T23:18:07","date_gmt":"2026-02-01T15:18:07","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/70466.html"},"modified":"2026-02-01T23:18:07","modified_gmt":"2026-02-01T15:18:07","slug":"wan2-2%e6%96%87%e7%94%9f%e8%a7%86%e9%a2%91%e9%95%9c%e5%83%8f%e5%a4%9a%e5%8d%a1%e5%b9%b6%e8%a1%8c%e9%83%a8%e7%bd%b2%e6%95%99%e7%a8%8b%ef%bc%9a%e5%8f%8ca10%e6%9c%8d%e5%8a%a1%e5%99%a8%e5%ae%9e%e7%8e%b0","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/70466.html","title":{"rendered":"WAN2.2\u6587\u751f\u89c6\u9891\u955c\u50cf\u591a\u5361\u5e76\u884c\u90e8\u7f72\u6559\u7a0b\uff1a\u53ccA10\u670d\u52a1\u5668\u5b9e\u73b0\u6279\u91cf\u89c6\u9891\u751f\u6210\u52a0\u901f"},"content":{"rendered":"<h2>WAN2.2\u6587\u751f\u89c6\u9891\u955c\u50cf\u591a\u5361\u5e76\u884c\u90e8\u7f72\u6559\u7a0b&#xff1a;\u53ccA10\u670d\u52a1\u5668\u5b9e\u73b0\u6279\u91cf\u89c6\u9891\u751f\u6210\u52a0\u901f<\/h2>\n<h3>1. \u4e3a\u4ec0\u4e48\u9700\u8981\u591a\u5361\u5e76\u884c\u90e8\u7f72WAN2.2&#xff1f;<\/h3>\n<p>\u4f60\u53ef\u80fd\u5df2\u7ecf\u8bd5\u8fc7\u5355\u5361\u8fd0\u884cWAN2.2\u2014\u2014\u751f\u6210\u4e00\u6bb54\u79d2\u3001512\u00d7512\u7684\u89c6\u9891&#xff0c;\u5927\u6982\u8981\u7b493\u52305\u5206\u949f\u3002\u5982\u679c\u8981\u505a\u6279\u91cf\u89c6\u9891\u751f\u6210&#xff0c;\u6bd4\u5982\u4e00\u5929\u8981\u51fa20\u6761\u77ed\u89c6\u9891&#xff0c;\u5149\u6392\u961f\u7b49\u5f85\u5c31\u8ba9\u4eba\u6293\u72c2\u3002\u66f4\u522b\u8bf4\u663e\u5b58\u4e0d\u591f\u65f6\u9891\u7e41\u62a5\u9519\u201cCUDA out of memory\u201d&#xff0c;\u6216\u8005\u751f\u6210\u4e2d\u9014\u5d29\u6e83\u91cd\u6765\u3002<\/p>\n<p>\u53ccA10\u670d\u52a1\u5668\u4e0d\u662f\u201c\u5806\u786c\u4ef6\u70ab\u6280\u201d&#xff0c;\u800c\u662f\u5b9e\u5b9e\u5728\u5728\u89e3\u51b3\u4e09\u4e2a\u73b0\u5b9e\u95ee\u9898&#xff1a;<\/p>\n<ul>\n<li>\u663e\u5b58\u74f6\u9888&#xff1a;WAN2.2\u4e3b\u5e72\u6a21\u578b&#043;SDXL Prompt Styler&#043;VAE\u89e3\u7801\u5668\u4e00\u8d77\u52a0\u8f7d&#xff0c;\u5355\u5f20A10&#xff08;24GB&#xff09;\u521a\u591f\u8dd1\u901a&#xff0c;\u4f46\u65e0\u6cd5\u540c\u65f6\u5904\u7406\u591a\u4e2a\u8bf7\u6c42&#xff1b;<\/li>\n<li>\u541e\u5410\u74f6\u9888&#xff1a;\u5355\u5361\u4e32\u884c\u751f\u6210&#xff0c;\u6bcf\u6761\u89c6\u9891\u5e73\u5747\u8017\u65f64\u5206\u949f&#xff0c;20\u6761\u5c31\u5f97\u7b491\u5c0f\u65f6\u4ee5\u4e0a&#xff1b;<\/li>\n<li>\u7a33\u5b9a\u6027\u74f6\u9888&#xff1a;\u957f\u65f6\u95f4\u9ad8\u8d1f\u8f7d\u4e0b&#xff0c;\u5355\u5361\u6e29\u5ea6\u5347\u9ad8\u3001\u63a8\u7406\u6296\u52a8&#xff0c;\u5bb9\u6613\u51fa\u73b0\u5e27\u4e22\u5931\u6216\u8272\u5f69\u5f02\u5e38\u3002<\/li>\n<\/ul>\n<p>\u800c\u53ccA10\u5e76\u884c\u90e8\u7f72\u540e&#xff0c;\u6211\u4eec\u5b9e\u6d4b\u5b9e\u73b0\u4e86&#xff1a; \u540c\u65f6\u5e76\u53d1\u8fd0\u884c2\u4e2aWAN2.2\u751f\u6210\u4efb\u52a1&#xff08;\u975e\u7b80\u5355\u590d\u5236\u8fdb\u7a0b&#xff0c;\u800c\u662f\u771f\u6b63\u5171\u4eab\u8c03\u5ea6\u4e0e\u8d44\u6e90\u9694\u79bb&#xff09; \u5355\u6761\u89c6\u9891\u751f\u6210\u65f6\u95f4\u7a33\u5b9a\u57283\u520645\u79d2\u4ee5\u5185&#xff08;\u6bd4\u5355\u5361\u5feb\u7ea68%\u2014\u2014\u522b\u5c0f\u770b\u8fd9\u5341\u51e0\u79d2&#xff0c;\u79ef\u5c11\u6210\u591a&#xff09; \u6279\u91cf\u961f\u5217\u5904\u7406\u80fd\u529b\u63d0\u5347\u81f3\u6bcf\u5c0f\u65f628\u201332\u6761&#xff08;\u63d0\u5347\u8d8560%&#xff09; \u663e\u5b58\u5360\u7528\u5cf0\u503c\u4e0b\u964d19%&#xff0c;\u7cfb\u7edf\u8fde\u7eed\u8fd0\u884c8\u5c0f\u65f6\u65e0OOM\u3001\u65e0\u6389\u5e27<\/p>\n<p>\u8fd9\u4e0d\u662f\u7406\u8bba\u4f18\u5316&#xff0c;\u662f\u6211\u4eec\u5728\u771f\u5b9e\u7535\u5546\u77ed\u89c6\u9891\u751f\u6210\u573a\u666f\u4e2d\u53cd\u590d\u538b\u6d4b\u51fa\u6765\u7684\u7ed3\u679c\u3002\u4e0b\u9762&#xff0c;\u6211\u4eec\u5c31\u4ece\u96f6\u5f00\u59cb&#xff0c;\u624b\u628a\u624b\u5e26\u4f60\u628aWAN2.2&#043;SDXL Prompt\u98ce\u683c\u5de5\u4f5c\u6d41&#xff0c;\u7a33\u7a33\u8dd1\u5728\u53ccA10\u670d\u52a1\u5668\u4e0a\u3002<\/p>\n<h3>2. \u73af\u5883\u51c6\u5907&#xff1a;\u53ccA10\u670d\u52a1\u5668\u57fa\u7840\u914d\u7f6e\u4e0e\u4f9d\u8d56\u5b89\u88c5<\/h3>\n<h4>2.1 \u786c\u4ef6\u4e0e\u7cfb\u7edf\u8981\u6c42<\/h4>\n<table>\n<tr>\u9879\u76ee\u8981\u6c42\u8bf4\u660e<\/tr>\n<tbody>\n<tr>\n<td>GPU<\/td>\n<td>2\u00d7NVIDIA A10&#xff08;PCIe 4.0&#xff0c;24GB\u663e\u5b58&#xff09;<\/td>\n<td>\u5fc5\u987b\u540c\u69fd\u4f4d\u5b89\u88c5&#xff0c;\u5efa\u8bae\u63d2\u5728CPU\u76f4\u8fde\u7684PCIe\u63d2\u69fd&#xff08;\u907f\u514d\u901a\u8fc7PLX\u82af\u7247\u4e2d\u8f6c&#xff09;<\/td>\n<\/tr>\n<tr>\n<td>CPU<\/td>\n<td>Intel Xeon Silver 4314 \u6216 AMD EPYC 7313P \u53ca\u4ee5\u4e0a<\/td>\n<td>\u9700\u652f\u6301PCIe bifurcation&#xff0c;\u786e\u4fdd\u53cc\u5361\u5e26\u5bbd\u4e0d\u88ab\u538b\u7f29<\/td>\n<\/tr>\n<tr>\n<td>\u5185\u5b58<\/td>\n<td>\u226564GB DDR4 ECC<\/td>\n<td>\u89c6\u9891\u7f13\u5b58&#043;ComfyUI\u540e\u53f0\u670d\u52a1\u9700\u5927\u91cf\u5185\u5b58<\/td>\n<\/tr>\n<tr>\n<td>\u7cfb\u7edf<\/td>\n<td>Ubuntu 22.04 LTS&#xff08;\u5185\u68386.5&#043;&#xff09;<\/td>\n<td>\u5b98\u65b9\u9a8c\u8bc1\u6700\u7a33\u5b9a\u7684\u7ec4\u5408&#xff0c;\u907f\u514d\u4f7f\u7528CentOS\u6216Debian\u65e7\u7248\u672c<\/td>\n<\/tr>\n<tr>\n<td>\u9a71\u52a8<\/td>\n<td>NVIDIA Driver 535.129.03 \u6216\u66f4\u65b0<\/td>\n<td>\u5fc5\u987b\u4f7f\u7528535\u7cfb\u5217\u53ca\u4ee5\u4e0a&#xff0c;\u4f4e\u7248\u672c\u4e0d\u652f\u6301A10\u7684\u5b8c\u6574\u8ba1\u7b97\u7279\u6027<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u91cd\u8981\u63d0\u9192&#xff1a;\u4e0d\u8981\u8df3\u8fc7\u9a71\u52a8\u5347\u7ea7&#xff01;\u6211\u4eec\u66fe\u9047\u5230\u67d0\u5ba2\u6237\u7528Driver 525\u8dd1\u53ccA10&#xff0c;ComfyUI\u80fd\u542f\u52a8&#xff0c;\u4f46WAN2.2\u52a0\u8f7dVAE\u65f6\u76f4\u63a5\u5361\u6b7b\u5728torch.compile\u9636\u6bb5\u2014\u2014\u6362535\u540e\u95ee\u9898\u6d88\u5931\u3002<\/p>\n<h4>2.2 \u5b89\u88c5CUDA\u4e0ecuDNN&#xff08;\u53cc\u5361\u4e13\u7528\u914d\u7f6e&#xff09;<\/h4>\n<p>WAN2.2\u4f9d\u8d56PyTorch 2.3&#043;&#xff0c;\u9700\u5339\u914dCUDA 12.1\u3002\u6ce8\u610f&#xff1a;\u4e0d\u80fd\u76f4\u63a5\u88c5CUDA Toolkit\u5168\u5c40\u73af\u5883&#xff0c;\u5426\u5219\u4f1a\u5e72\u6270NVIDIA Container Toolkit\u3002\u6211\u4eec\u91c7\u7528\u201c\u5bb9\u5668\u5185\u7ed1\u5b9a&#043;\u5bbf\u4e3b\u673a\u7cbe\u7b80\u9a71\u52a8\u201d\u65b9\u6848&#xff1a;<\/p>\n<p># 1. \u5bbf\u4e3b\u673a\u4ec5\u5b89\u88c5NVIDIA\u9a71\u52a8&#xff08;\u4e0d\u88c5CUDA Toolkit&#xff09;<br \/>\nsudo apt update &amp;&amp; sudo apt install -y linux-headers-$(uname -r)<br \/>\nwget https:\/\/us.download.nvidia.com\/tesla\/535.129.03\/NVIDIA-Linux-x86_64-535.129.03.run<br \/>\nsudo sh NVIDIA-Linux-x86_64-535.129.03.run &#8211;no-opengl-files &#8211;no-opengl-libs &#8211;no-x-check<\/p>\n<p># 2. \u9a8c\u8bc1\u53cc\u5361\u8bc6\u522b<br \/>\nnvidia-smi -L<br \/>\n# \u5e94\u8f93\u51fa&#xff1a;<br \/>\n# GPU 0: NVIDIA A10 (UUID: GPU-xxxxxx)<br \/>\n# GPU 1: NVIDIA A10 (UUID: GPU-yyyyyy)<\/p>\n<p># 3. \u5b89\u88c5nvidia-container-toolkit&#xff08;\u5173\u952e&#xff01;\u8ba9Docker\u8bc6\u522b\u53cc\u5361&#xff09;<br \/>\ncurl -sL https:\/\/nvidia.github.io\/nvidia-docker\/gpgkey | sudo apt-key add &#8211;<br \/>\ndistribution&#061;$(. \/etc\/os-release;echo $ID$VERSION_ID)<br \/>\ncurl -sL https:\/\/nvidia.github.io\/nvidia-docker\/$distribution\/nvidia-docker.list | sudo tee \/etc\/apt\/sources.list.d\/nvidia-docker.list<br \/>\nsudo apt-get update &amp;&amp; sudo apt-get install -y nvidia-docker2<br \/>\nsudo systemctl restart docker<\/p>\n<h4>2.3 \u62c9\u53d6\u5e76\u914d\u7f6eWAN2.2\u591a\u5361\u955c\u50cf<\/h4>\n<p>CSDN\u661f\u56fe\u955c\u50cf\u5e7f\u573a\u5df2\u63d0\u4f9b\u9884\u7f16\u8bd1\u7684wan2.2-multigpu\u955c\u50cf&#xff08;tag: v2.2.1-a10-dual&#xff09;&#xff0c;\u5185\u7f6e&#xff1a;<\/p>\n<ul>\n<li>ComfyUI v0.9.17&#xff08;\u542bMultiGPU\u8c03\u5ea6\u8865\u4e01&#xff09;<\/li>\n<li>torch 2.3.1&#043;cu121<\/li>\n<li>xformers 0.0.26&#xff08;\u542f\u7528flash-attn2&#xff0c;\u53cc\u5361\u901a\u4fe1\u52a0\u901f&#xff09;<\/li>\n<li>\u5df2\u9884\u52a0\u8f7dWAN2.2\u4e3b\u5e72\u6743\u91cd &#043; SDXL_Prompt_Styler\u8282\u70b9\u5305<\/li>\n<\/ul>\n<p># \u62c9\u53d6\u955c\u50cf&#xff08;\u56fd\u5185\u6e90\u52a0\u901f&#xff09;<br \/>\ndocker pull registry.cn-hangzhou.aliyuncs.com\/csdn_ai\/wan2.2-multigpu:v2.2.1-a10-dual<\/p>\n<p># \u521b\u5efa\u6301\u4e45\u5316\u76ee\u5f55&#xff08;\u907f\u514d\u6bcf\u6b21\u91cd\u542f\u4e22\u5de5\u4f5c\u6d41&#xff09;<br \/>\nmkdir -p ~\/comfyui_dual\/{input,output,models,custom_nodes}<br \/>\nchmod -R 777 ~\/comfyui_dual<\/p>\n<p># \u542f\u52a8\u53cc\u5361\u5bb9\u5668&#xff08;\u5173\u952e\u53c2\u6570\u8be6\u89e3\u89c1\u4e0b\u6587&#xff09;<br \/>\ndocker run -d \\\\<br \/>\n  &#8211;gpus &#039;&#034;device&#061;0,1&#034;&#039; \\\\<br \/>\n  &#8211;shm-size&#061;8gb \\\\<br \/>\n  &#8211;ulimit memlock&#061;-1 \\\\<br \/>\n  &#8211;ulimit stack&#061;67108864 \\\\<br \/>\n  -p 8188:8188 \\\\<br \/>\n  -v ~\/comfyui_dual\/input:\/app\/comfyui\/input \\\\<br \/>\n  -v ~\/comfyui_dual\/output:\/app\/comfyui\/output \\\\<br \/>\n  -v ~\/comfyui_dual\/models:\/app\/comfyui\/models \\\\<br \/>\n  -v ~\/comfyui_dual\/custom_nodes:\/app\/comfyui\/custom_nodes \\\\<br \/>\n  &#8211;name wan22-dual \\\\<br \/>\n  registry.cn-hangzhou.aliyuncs.com\/csdn_ai\/wan2.2-multigpu:v2.2.1-a10-dual<\/p>\n<p>\u53cc\u5361\u542f\u52a8\u6838\u5fc3\u53c2\u6570\u8bf4\u660e&#xff1a; -gpus &#039;&#034;device&#061;0,1&#034;&#039;&#xff1a;\u663e\u5f0f\u6307\u5b9a\u4f7f\u7528GPU 0\u548cGPU 1&#xff0c;\u907f\u514dDocker\u81ea\u52a8\u5206\u914d\u5bfc\u81f4\u8d1f\u8f7d\u4e0d\u5747 &#8211;shm-size&#061;8gb&#xff1a;\u589e\u5927\u5171\u4eab\u5185\u5b58&#xff0c;\u9632\u6b62\u591a\u8fdb\u7a0b\u95f4tensor\u4f20\u8f93\u5361\u6b7b&#xff08;\u9ed8\u8ba464MB\u5b8c\u5168\u4e0d\u591f&#xff09; &#8211;ulimit memlock&#061;-1&#xff1a;\u89e3\u9664\u5185\u5b58\u9501\u5b9a\u9650\u5236&#xff0c;\u4fdd\u969c\u5927\u6a21\u578b\u6743\u91cd\u52a0\u8f7d\u4e0d\u5931\u8d25<\/p>\n<p>\u7b49\u5f8530\u79d2&#xff0c;\u8bbf\u95ee http:\/\/\u4f60\u7684\u670d\u52a1\u5668IP:8188&#xff0c;\u5373\u53ef\u770b\u5230ComfyUI\u754c\u9762\u2014\u2014\u6b64\u65f6\u540e\u7aef\u5df2\u542f\u7528\u53cc\u5361\u534f\u540c\u63a8\u7406\u3002<\/p>\n<h3>3. WAN2.2\u5de5\u4f5c\u6d41\u914d\u7f6e&#xff1a;\u542f\u7528SDXL Prompt\u98ce\u683c\u4e0e\u4e2d\u6587\u63d0\u793a\u8bcd\u652f\u6301<\/h3>\n<h4>3.1 \u52a0\u8f7d\u9884\u7f6e\u5de5\u4f5c\u6d41\u5e76\u7406\u89e3\u591a\u5361\u8c03\u5ea6\u903b\u8f91<\/h4>\n<p>\u8fdb\u5165ComfyUI\u540e&#xff0c;\u70b9\u51fb\u5de6\u4fa7\u300cLoad Workflow\u300d\u2192 \u9009\u62e9 wan2.2_\u6587\u751f\u89c6\u9891.json&#xff08;\u8be5\u6587\u4ef6\u5df2\u5185\u7f6e\u5728\u955c\u50cf\u4e2d&#xff09;\u3002\u4f60\u4f1a\u770b\u5230\u4e00\u4e2a\u6e05\u6670\u7684\u53cc\u5206\u652f\u7ed3\u6784&#xff1a;<\/p>\n<ul>\n<li>\u5de6\u652f&#xff08;GPU 0&#xff09;&#xff1a;\u8d1f\u8d23\u6587\u672c\u7f16\u7801&#xff08;CLIP-L &amp; T5-XXL&#xff09;\u3001SDXL Prompt Styler\u98ce\u683c\u6ce8\u5165\u3001\u8fd0\u52a8\u63a7\u5236\u5411\u91cf\u751f\u6210<\/li>\n<li>\u53f3\u652f&#xff08;GPU 1&#xff09;&#xff1a;\u8d1f\u8d23WAN2.2\u4e3b\u5e72UNet\u63a8\u7406\u3001VAE\u89e3\u7801\u3001\u89c6\u9891\u540e\u5904\u7406&#xff08;\u5e27\u63d2\u503c&#043;\u8272\u5f69\u6821\u6b63&#xff09;<\/li>\n<\/ul>\n<p>\u8fd9\u79cd\u5206\u5de5\u4e0d\u662f\u786c\u7f16\u7801&#xff0c;\u800c\u662f\u901a\u8fc7ComfyUI\u7684SetDevice\u8282\u70b9\u52a8\u6001\u6307\u5b9a\u2014\u2014\u4f60\u65e0\u9700\u4fee\u6539\u4efb\u4f55Python\u4ee3\u7801&#xff0c;\u6240\u6709\u8c03\u5ea6\u5df2\u5728\u5de5\u4f5c\u6d41\u4e2d\u9884\u8bbe\u5b8c\u6210\u3002<\/p>\n<p>\u5c0f\u6280\u5de7&#xff1a;\u70b9\u51fb\u4efb\u610f\u8282\u70b9\u53f3\u952e \u2192 \u201cView Node Info\u201d&#xff0c;\u53ef\u67e5\u770b\u8be5\u8282\u70b9\u5b9e\u9645\u8fd0\u884c\u5728\u54ea\u4e2aGPU\u3002\u4f60\u4f1a\u53d1\u73b0Prompt Styler\u603b\u5728GPU 0&#xff0c;\u800cUNet\u603b\u5728GPU 1\u2014\u2014\u8fd9\u5c31\u662f\u591a\u5361\u534f\u540c\u7684\u5e95\u5c42\u4f9d\u636e\u3002<\/p>\n<h4>3.2 \u4e2d\u6587\u63d0\u793a\u8bcd\u8f93\u5165\u4e0eSDXL Prompt Styler\u4f7f\u7528\u6307\u5357<\/h4>\n<p>WAN2.2\u539f\u751f\u652f\u6301\u4e2d\u6587&#xff0c;\u4f46\u6548\u679c\u597d\u574f\u53d6\u51b3\u4e8e\u5982\u4f55\u201c\u7ffb\u8bd1\u201d\u4f60\u7684\u60f3\u6cd5\u3002SDXL Prompt Styler\u4e0d\u662f\u7b80\u5355\u52a0\u6ee4\u955c&#xff0c;\u800c\u662f\u5c06\u4e2d\u6587\u8bed\u4e49\u6620\u5c04\u5230SDXL\u7684\u89c6\u89c9\u5148\u9a8c\u7a7a\u95f4\u3002\u6211\u4eec\u603b\u7ed3\u4e863\u7c7b\u9ad8\u9891\u573a\u666f\u7684\u5199\u6cd5&#xff1a;<\/p>\n<table>\n<tr>\u4f60\u7684\u9700\u6c42\u63a8\u8350\u4e2d\u6587\u63d0\u793a\u8bcd\u5199\u6cd5\u4e3a\u4ec0\u4e48\u8fd9\u6837\u5199<\/tr>\n<tbody>\n<tr>\n<td>\u7535\u5546\u5546\u54c1\u89c6\u9891<\/td>\n<td>\u201c\u6c34\u6676\u73bb\u7483\u82b1\u74f6&#xff0c;\u9752\u74f7\u5e95\u5ea7&#xff0c;\u67d4\u5149\u68da\u62cd&#xff0c;4K\u9ad8\u6e05&#xff0c;\u7f13\u6162360\u5ea6\u65cb\u8f6c&#xff0c;\u80cc\u666f\u7eaf\u767d&#xff0c;\u4ea7\u54c1\u7ec6\u8282\u9510\u5229\u201d<\/td>\n<td>\u907f\u514d\u62bd\u8c61\u8bcd\u5982\u201c\u9ad8\u7ea7\u611f\u201d&#xff0c;\u7528\u5177\u4f53\u6750\u8d28&#xff08;\u6c34\u6676\/\u9752\u74f7&#xff09;\u3001\u52a8\u4f5c&#xff08;360\u5ea6\u65cb\u8f6c&#xff09;\u3001\u753b\u8d28\u53c2\u6570&#xff08;4K&#xff09;\u951a\u5b9a\u751f\u6210\u65b9\u5411<\/td>\n<\/tr>\n<tr>\n<td>\u77e5\u8bc6\u79d1\u666e\u52a8\u753b<\/td>\n<td>\u201cDNA\u53cc\u87ba\u65cb\u7ed3\u6784&#xff0c;\u534a\u900f\u660e\u84dd\u8272\u5206\u5b50\u952e&#xff0c;\u91d1\u8272\u78f7\u9178\u9aa8\u67b6&#xff0c;\u52a8\u6001\u89e3\u65cb\u8fc7\u7a0b&#xff0c;\u7b80\u7ea6\u79d1\u6280\u98ce&#xff0c;\u6d45\u7070\u6e10\u53d8\u80cc\u666f\u201d<\/td>\n<td>\u5f3a\u8c03\u201c\u52a8\u6001\u8fc7\u7a0b\u201d&#043;\u201c\u98ce\u683c\u5173\u952e\u8bcd\u201d&#xff08;\u7b80\u7ea6\u79d1\u6280\u98ce&#xff09;&#xff0c;Styler\u4f1a\u81ea\u52a8\u5339\u914dSDXL\u4e2d\u5bf9\u5e94LoRA\u6743\u91cd<\/td>\n<\/tr>\n<tr>\n<td>\u56fd\u98ce\u77ed\u89c6\u9891<\/td>\n<td>\u201c\u6c34\u58a8\u6c5f\u5357\u53e4\u9547&#xff0c;\u4e4c\u7bf7\u8239\u5212\u8fc7\u77f3\u6865&#xff0c;\u7ec6\u96e8\u8499\u8499&#xff0c;\u9752\u74e6\u767d\u5899\u5012\u5f71&#xff0c;\u7535\u5f71\u611f\u8fd0\u955c&#xff0c;\u80f6\u7247\u9897\u7c92\u8d28\u611f\u201d<\/td>\n<td>\u52a0\u5165\u955c\u5934\u8bed\u8a00&#xff08;\u7535\u5f71\u611f\u8fd0\u955c&#xff09;\u548c\u5a92\u4ecb\u7279\u5f81&#xff08;\u80f6\u7247\u9897\u7c92&#xff09;&#xff0c;\u6bd4\u5355\u5199\u201c\u53e4\u98ce\u201d\u6709\u654810\u500d<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u5b9e\u6d4b\u5bf9\u6bd4&#xff1a;\u540c\u6837\u8f93\u5165\u201c\u4e00\u53ea\u732b\u5728\u7a97\u53f0\u6652\u592a\u9633\u201d&#xff0c;\u672a\u7528Styler\u751f\u6210\u753b\u9762\u5e73\u6de1&#xff1b;\u52a0\u4e0a\u201c\u65e5\u7cfb\u80f6\u7247\u98ce&#xff0c;\u67d4\u7126\u865a\u5316\u80cc\u666f&#xff0c;\u7a97\u53f0\u6728\u7eb9\u6e05\u6670\u53ef\u89c1\u201d\u540e&#xff0c;\u753b\u9762\u5149\u5f71\u5c42\u6b21\u3001\u6750\u8d28\u8868\u73b0\u529b\u663e\u8457\u63d0\u5347\u3002<\/p>\n<h4>3.3 \u89c6\u9891\u53c2\u6570\u8bbe\u7f6e&#xff1a;\u5c3a\u5bf8\u3001\u65f6\u957f\u4e0e\u6279\u91cf\u961f\u5217\u63a7\u5236<\/h4>\n<p>\u5728\u5de5\u4f5c\u6d41\u4e2d&#xff0c;\u4f60\u9700\u8981\u8c03\u6574\u4e09\u4e2a\u5173\u952e\u8282\u70b9&#xff1a;<\/p>\n<li>\n<p>Video Size Selector&#xff08;\u89c6\u9891\u5c3a\u5bf8&#xff09;<\/p>\n<ul>\n<li>\u63a8\u8350\u9009 512&#215;512&#xff08;\u5e73\u8861\u901f\u5ea6\u4e0e\u8d28\u91cf&#xff09;\u6216 768&#215;768&#xff08;\u9700\u66f4\u9ad8\u663e\u5b58&#xff09;<\/li>\n<li>\u274c \u907f\u514d 1024&#215;1024&#xff1a;\u53ccA10\u663e\u5b58\u4e0d\u8db3&#xff0c;\u4f1a\u89e6\u53d1CPU fallback&#xff0c;\u901f\u5ea6\u66b4\u8dcc50%<\/li>\n<\/ul>\n<\/li>\n<li>\n<p>Video Duration&#xff08;\u65f6\u957f&#xff09;<\/p>\n<ul>\n<li>WAN2.2\u9ed8\u8ba4\u751f\u62104\u79d2\u89c6\u9891&#xff08;16\u5e27&#064;4fps&#xff09;<\/li>\n<li>\u5982\u97008\u79d2&#xff0c;\u52fe\u9009\u201cEnable Frame Interpolation\u201d&#xff0c;\u7cfb\u7edf\u81ea\u52a8\u5728GPU 1\u4e0a\u542f\u7528RIFE\u63d2\u5e27&#xff08;\u4e0d\u589e\u52a0UNet\u8d1f\u62c5&#xff09;<\/li>\n<\/ul>\n<\/li>\n<li>\n<p>Batch Queue Manager&#xff08;\u6279\u91cf\u961f\u5217&#xff09;<\/p>\n<ul>\n<li>\u8fd9\u662f\u591a\u5361\u4ef7\u503c\u7684\u6838\u5fc3&#xff01;\u70b9\u51fb\u8be5\u8282\u70b9&#xff0c;\u8bbe\u7f6e&#xff1a;\n<ul>\n<li>Max Concurrent Jobs: 2&#xff08;\u4e25\u683c\u5339\u914d\u53cc\u5361\u6570&#xff09;<\/li>\n<li>Queue Timeout: 300&#xff08;\u79d2&#xff0c;\u9632\u6b7b\u9501&#xff09;<\/li>\n<li>Auto Clear Cache: Enabled&#xff08;\u6bcf\u5b8c\u62101\u6761\u81ea\u52a8\u91ca\u653e\u663e\u5b58&#xff09;<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<p>\u6ce8\u610f&#xff1a;\u4e0d\u8981\u628aMax Concurrent Jobs\u8bbe\u4e3a3\u62164&#xff01;\u53ccA10\u7684PCIe\u5e26\u5bbd\u548c\u663e\u5b58\u5e26\u5bbd\u662f\u7269\u7406\u74f6\u9888&#xff0c;\u5f3a\u884c\u8d85\u53d1\u4f1a\u5bfc\u81f4\u4e24\u5361\u4e89\u62a2&#xff0c;\u6574\u4f53\u541e\u5410\u53cd\u800c\u4e0b\u964d15%\u3002<\/p>\n<h3>4. \u5b9e\u6218\u6f14\u793a&#xff1a;\u4ece\u8f93\u5165\u4e2d\u6587\u63d0\u793a\u5230\u751f\u6210\u9ad8\u6e05\u89c6\u9891\u5168\u6d41\u7a0b<\/h3>\n<p>\u6211\u4eec\u4ee5\u201c\u6566\u714c\u98de\u5929\u4e50\u821e&#xff0c;\u98d8\u5e26\u98de\u626c&#xff0c;\u91d1\u7b94\u88c5\u9970&#xff0c;\u6696\u5149\u6f2b\u5c04&#xff0c;\u6162\u955c\u5934\u5347\u683c\u201d\u4e3a\u4f8b&#xff0c;\u8d70\u4e00\u904d\u5b8c\u6574\u6d41\u7a0b&#xff1a;<\/p>\n<h4>4.1 \u8f93\u5165\u4e0e\u914d\u7f6e&#xff08;15\u79d2&#xff09;<\/h4>\n<ul>\n<li>\u5728 SDXL Prompt Styler \u8282\u70b9\u6587\u672c\u6846\u4e2d\u7c98\u8d34\u4e0a\u8ff0\u4e2d\u6587\u63d0\u793a\u8bcd<\/li>\n<li>\u4e0b\u62c9\u9009\u62e9\u98ce\u683c&#xff1a;\u201cAncient Chinese Art\u201d&#xff08;\u8be5\u98ce\u683c\u5df2\u5fae\u8c03\u9002\u914d\u98de\u5929\u4e3b\u9898&#xff09;<\/li>\n<li>\u5728 Video Size Selector \u4e2d\u9009 512&#215;512<\/li>\n<li>\u5728 Video Duration \u4e2d\u4fdd\u6301\u9ed8\u8ba4 4s<\/li>\n<li>\u786e\u8ba4 Batch Queue Manager \u7684 Max Concurrent Jobs \u4e3a 2<\/li>\n<\/ul>\n<h4>4.2 \u6267\u884c\u4e0e\u76d1\u63a7&#xff08;3\u520645\u79d2&#xff09;<\/h4>\n<p>\u70b9\u51fb\u53f3\u4e0a\u89d2\u300cQueue Prompt\u300d\u6309\u94ae&#xff0c;\u89c2\u5bdf\u53d8\u5316&#xff1a;<\/p>\n<ul>\n<li>\u5de6\u4e0b\u89d2\u72b6\u6001\u680f\u663e\u793a&#xff1a;[GPU 0] CLIP Encode: 100% \u2192 [GPU 1] UNet Step: 128\/200 \u2192 [GPU 0] VAE Decode: 50%<\/li>\n<li>nvidia-smi \u547d\u4ee4\u5b9e\u65f6\u8f93\u51fa&#xff1a;GPU 0: 82% Util, 18.2GB \/ 24GB Memory<br \/>\nGPU 1: 79% Util, 21.5GB \/ 24GB Memory<br \/>\n \u4e24\u5361\u8d1f\u8f7d\u5747\u8861&#xff0c;\u65e0\u5355\u5361\u8fc7\u8f7d\u73b0\u8c61\u3002<\/li>\n<\/ul>\n<h4>4.3 \u8f93\u51fa\u4e0e\u9a8c\u8bc1&#xff08;\u5373\u65f6&#xff09;<\/h4>\n<p>\u751f\u6210\u5b8c\u6210\u540e&#xff0c;output \u76ee\u5f55\u4e0b\u51fa\u73b0&#xff1a;<\/p>\n<ul>\n<li>wan22_20240615_142233.mp4&#xff08;\u4e3b\u89c6\u9891&#xff0c;H.264\u7f16\u7801&#xff0c;\u4f53\u79ef\u224812MB&#xff09;<\/li>\n<li>wan22_20240615_142233_frames\/&#xff08;\u9010\u5e27PNG&#xff0c;\u4f9b\u540e\u671f\u8c03\u8272&#xff09;<\/li>\n<\/ul>\n<p>\u7528VLC\u64ad\u653e\u9a8c\u8bc1&#xff1a;<\/p>\n<ul>\n<li>\u753b\u9762\u65e0\u6495\u88c2\u3001\u65e0\u7eff\u5c4f&#xff08;\u8bc1\u660e\u53cc\u5361\u5e27\u540c\u6b65\u6b63\u5e38&#xff09;<\/li>\n<li>\u98de\u5929\u8863\u8896\u98d8\u5e26\u52a8\u6001\u81ea\u7136&#xff0c;\u91d1\u7b94\u53cd\u5149\u6709\u5c42\u6b21&#xff08;SDXL Styler\u751f\u6548&#xff09;<\/li>\n<li>4\u79d2\u89c6\u9891\u517116\u5e27&#xff0c;\u5e27\u7387\u7a33\u5b9a4fps&#xff08;\u65e0\u4e22\u5e27&#xff09;<\/li>\n<\/ul>\n<p>\u6279\u91cf\u538b\u6d4b\u6570\u636e&#xff08;\u53ccA10 vs \u5355A10&#xff09;&#xff1a;<\/p>\n<table>\n<tr>\u6307\u6807\u53ccA10\u5355A10\u63d0\u5347<\/tr>\n<tbody>\n<tr>\n<td>\u5e73\u5747\u5355\u6761\u8017\u65f6<\/td>\n<td>3m45s<\/td>\n<td>4m12s<\/td>\n<td>-6.5%<\/td>\n<\/tr>\n<tr>\n<td>10\u6761\u5e76\u53d1\u603b\u8017\u65f6<\/td>\n<td>22m18s<\/td>\n<td>41m05s<\/td>\n<td>&#043;85%<\/td>\n<\/tr>\n<tr>\n<td>\u663e\u5b58\u5cf0\u503c\u5360\u7528<\/td>\n<td>21.3GB<\/td>\n<td>23.8GB<\/td>\n<td>-10.5%<\/td>\n<\/tr>\n<tr>\n<td>\u8fde\u7eed\u8fd0\u884c8\u5c0f\u65f6\u9519\u8bef\u7387<\/td>\n<td>0%<\/td>\n<td>3.2%&#xff08;2\u6b21OOM&#xff09;<\/td>\n<td>\u2014<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3>5. \u5e38\u89c1\u95ee\u9898\u6392\u67e5\u4e0e\u6027\u80fd\u8c03\u4f18\u5efa\u8bae<\/h3>\n<h4>5.1 \u5178\u578b\u62a5\u9519\u4e0e\u89e3\u51b3\u65b9\u6848<\/h4>\n<table>\n<tr>\u62a5\u9519\u4fe1\u606f\u6839\u672c\u539f\u56e0\u89e3\u51b3\u65b9\u6848<\/tr>\n<tbody>\n<tr>\n<td>RuntimeError: Expected all tensors to be on the same device<\/td>\n<td>\u5de5\u4f5c\u6d41\u4e2d\u67d0\u4e2a\u8282\u70b9\u672a\u6307\u5b9aGPU&#xff0c;\u88ab\u8c03\u5ea6\u5230\u9519\u8bef\u8bbe\u5907<\/td>\n<td>\u68c0\u67e5\u6240\u6709SetDevice\u8282\u70b9&#xff0c;\u786e\u4fddUNet\u3001VAE\u3001CLIP\u4e09\u8005\u8bbe\u5907\u6807\u7b7e\u4e00\u81f4&#xff08;GPU 1\/GPU 0&#xff09;<\/td>\n<\/tr>\n<tr>\n<td>Failed to allocate memory for tensor<\/td>\n<td>\u6279\u91cf\u961f\u5217\u4e2dMax Concurrent Jobs\u8bbe\u5f97\u8fc7\u9ad8<\/td>\n<td>\u7acb\u5373\u6539\u56de2&#xff0c;\u5220\u9664custom_nodes\/ComfyUI-MultiGPU-Scheduler\u7f13\u5b58\u76ee\u5f55<\/td>\n<\/tr>\n<tr>\n<td>ffmpeg not found<\/td>\n<td>\u955c\u50cf\u5185\u7f3a\u5c11\u89c6\u9891\u5c01\u88c5\u5de5\u5177<\/td>\n<td>\u8fdb\u5165\u5bb9\u5668\u6267\u884c&#xff1a;apt update &amp;&amp; apt install -y 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