import{s as A,n as Y,o as W}from"../chunks/scheduler.e4ff9b64.js";import{S,i as D,e as d,s as n,c as x,h as F,a as T,d as l,b as i,f as z,g as I,j as P,k as O,l as X,m as a,n as J,t as v,o as E,p as H}from"../chunks/index.09f1bca0.js";import{C as V,H as N,E as K}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.dde31fc2.js";import{C as tt}from"../chunks/CodeBlock.54e44b16.js";function et(Z){let s,b,g,U,p,G,r,$,u,L='Intel Gaudi AI 加速器系列包括 <a href="https://habana.ai/products/gaudi/" rel="nofollow">Intel Gaudi 1</a>、<a href="https://habana.ai/products/gaudi2/" rel="nofollow">Intel Gaudi 2</a> 和 <a href="https://habana.ai/products/gaudi3/" rel="nofollow">Intel Gaudi 3</a>。每台服务器配备 8 个设备，称为 Habana 处理单元 (HPU)，在 Gaudi 3 上提供 128GB 内存，在 Gaudi 2 上提供 96GB 内存，在第一代 Gaudi 上提供 32GB 内存。有关底层硬件架构的更多详细信息，请查看 <a href="https://docs.habana.ai/en/latest/Gaudi_Overview/Gaudi_Architecture.html" rel="nofollow">Gaudi 架构</a> 概述。',w,m,B='Diffusers 管道可以利用 HPU 加速，即使管道尚未添加到 <a href="https://huggingface.co/docs/optimum/main/en/habana/index" rel="nofollow">Optimum for Intel Gaudi</a>，也可以通过 <a href="https://docs.habana.ai/en/latest/PyTorch/PyTorch_Model_Porting/GPU_Migration_Toolkit/GPU_Migration_Toolkit.html" rel="nofollow">GPU 迁移工具包</a> 实现。',_,f,C="在您的管道上调用 <code>.to(&quot;hpu&quot;)</code> 以将其移动到 HPU 设备，如下所示为 Flux 示例：",Q,c,y,o,q='<p>对于 Gaudi 优化的扩散管道实现，我们推荐使用 <a href="https://huggingface.co/docs/optimum/main/en/habana/index" rel="nofollow">Optimum for Intel Gaudi</a>。</p>',j,h,k,M,R;return p=new V({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),r=new N({props:{title:"Intel Gaudi",local:"intel-gaudi",headingTag:"h1"}}),c=new tt({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;black-forest-labs/FLUX.1-schnell&quot;</span>, torch_dtype=torch.bfloat16)
pipeline.to(<span class="hljs-string">&quot;hpu&quot;</span>)

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