import{s as C,o as Y,n as q}from"../chunks/scheduler.5c93273d.js";import{S as z,i as W,g as T,s,r as k,A as D,h as g,f as l,c as o,j as L,u as y,x as E,k as A,y as F,a as n,v as I,d as J,t as v,w as H}from"../chunks/index.e43dd92b.js";import{T as S}from"../chunks/Tip.1cbfe904.js";import{C as X}from"../chunks/CodeBlock.6896320e.js";import{H as V,E as N}from"../chunks/getInferenceSnippets.bd93e167.js";function K(b){let a,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>。';return{c(){a=T("p"),a.innerHTML=p},l(i){a=g(i,"P",{"data-svelte-h":!0}),E(a)!=="svelte-1o0va8c"&&(a.innerHTML=p)},m(i,$){n(i,a,$)},p:q,d(i){i&&l(a)}}}function tt(b){let a,p,i,$,u,G,m,Z='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。',U,f,x='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。',w,c,O="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：",_,h,Q,r,j,d,P,M,R;return u=new V({props:{title:"Intel Gaudi",local:"intel-gaudi",headingTag:"h1"}}),h=new X({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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