diffusers/pr_12747/zh/_app/immutable/nodes/29.4e175abb.js

import{s as me,a as oe,n as pe,o as re}from"../chunks/scheduler.e4ff9b64.js";import{S as Me,i as ue,e as i,s as a,c as b,h as fe,a as m,d as t,b as s,f as ie,g as j,j as Q,k as d,l as Ue,m as n,n as N,t as R,o as J,p as S}from"../chunks/index.09f1bca0.js";import{C as ce,H as Te,E as ye}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.fa41648d.js";import{C as z}from"../chunks/CodeBlock.24c75275.js";function Ce(P){let o,_,F,O,M,I,u,A,f,q='Diffusers 功能可在 <a href="https://aws.amazon.com/ec2/instance-types/inf2/" rel="nofollow">AWS Inf2 实例</a>上使用，这些是由 <a href="https://aws.amazon.com/machine-learning/inferentia/" rel="nofollow">Neuron 机器学习加速器</a>驱动的 EC2 实例。这些实例旨在提供更好的计算性能（更高的吞吐量、更低的延迟）和良好的成本效益，使其成为 AWS 用户将扩散模型部署到生产环境的良好选择。',k,U,K='<a href="https://huggingface.co/docs/optimum-neuron/en/index" rel="nofollow">Optimum Neuron</a> 是 Hugging Face 库与 AWS 加速器之间的接口，包括 AWS <a href="https://aws.amazon.com/machine-learning/trainium/" rel="nofollow">Trainium</a> 和 AWS <a href="https://aws.amazon.com/machine-learning/inferentia/" rel="nofollow">Inferentia</a>。它支持 Diffusers 中的许多功能，并具有类似的 API，因此如果您已经熟悉 Diffusers，学习起来更容易。一旦您创建了 AWS Inf2 实例，请安装 Optimum Neuron。',B,c,v,r,ee='<p>我们提供预构建的 <a href="https://aws.amazon.com/marketplace/pp/prodview-gr3e6yiscria2" rel="nofollow">Hugging Face Neuron 深度学习 AMI</a>（DLAMI）和用于 Amazon SageMaker 的 Optimum Neuron 容器。建议正确设置您的环境。</p>',x,T,le="下面的示例演示了如何在 inf2.8xlarge 实例上使用 Stable Diffusion XL 模型生成图像（一旦模型编译完成，您可以切换到更便宜的 inf2.xlarge 实例）。要生成一些图像，请使用 <code>NeuronStableDiffusionXLPipeline</code> 类，该类类似于 Diffusers 中的 <code>StableDiffusionXLPipeline</code> 类。",E,y,te="与 Diffusers 不同，您需要将管道中的模型编译为 Neuron 格式，即 <code>.neuron</code>。运行以下命令将模型导出为 <code>.neuron</code> 格式。",G,C,L,g,ne="现在使用预编译的 SDXL 模型生成一些图像。",W,V,X,p,ae,Y,w,se='欢迎查看Optimum Neuron <a href="https://huggingface.co/docs/optimum-neuron/en/inference_tutorials/stable_diffusion#generate-images-with-stable-diffusion-models-on-aws-inferentia" rel="nofollow">文档</a>中更多不同用例的指南和示例！',Z,h,D,$,H;return M=new ce({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),u=new Te({props:{title:"AWS Neuron",local:"aws-neuron",headingTag:"h1"}}),c=new z({props:{code:"cHl0aG9uJTIwLW0lMjBwaXAlMjBpbnN0YWxsJTIwLS11cGdyYWRlLXN0cmF0ZWd5JTIwZWFnZXIlMjBvcHRpbXVtJTVCbmV1cm9ueCU1RA==",highlighted:"python -m pip install --upgrade-strategy eager optimum[neuronx]",wrap:!1}}),C=new z({props:{code:"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",highlighted:'optimum-cli <span class="hljs-built_in">export</span> neuron --model stabilityai/stable-diffusion-xl-base-1.0 \\\n  --batch_size 1 \\\n  --height 1024 `<span class="hljs-comment"># 生成图像的高度（像素），例如 768, 1024` \\</span>\n  --width 1024 `<span class="hljs-comment"># 生成图像的宽度（像素），例如 768, 1024` \\</span>\n  --num_images_per_prompt 1 `<span class="hljs-comment"># 每个提示生成的图像数量，默认为 1` \\</span>\n  --auto_cast matmul `<span class="hljs-comment"># 仅转换矩阵乘法操作` \\</span>\n  --auto_cast_type bf16 `<span class="hljs-comment"># 将操作从 FP32 转换为 BF16` \\</span>\n  sd_neuron_xl/',wrap:!1}}),V=new z({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> Neu
ronStableDiffusionXLPipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>stable_diffusion_xl = NeuronStableDiffusionXLPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl/&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>prompt = <span class="hljs-string">&quot;a pig with wings flying in floating US dollar banknotes in the air, skyscrapers behind, warm color palette, muted colors, detailed, 8k&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>image = stable_diffusion_xl(prompt).images[<span class="hljs-number">0</span>]`,wrap:!1}}),h=new ye({props:{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/zh/optimization/neuron.md"}}),{c(){o=i("meta"),_=a(),F=i("p"),O=a(),b(M.$$.fragment),I=a(),b(u.$$.fragment),A=a(),f=i("p"),f.innerHTML=q,k=a(),U=i("p"),U.innerHTML=K,B=a(),b(c.$$.fragment),v=a(),r=i("blockquote"),r.innerHTML=ee,x=a(),T=i("p"),T.innerHTML=le,E=a(),y=i("p"),y.innerHTML=te,G=a(),b(C.$$.fragment),L=a(),g=i("p"),g.textContent=ne,W=a(),b(V.$$.fragment),X=a(),p=i("img"),Y=a(),w=i("p"),w.innerHTML=se,Z=a(),b(h.$$.fragment),D=a(),$=i("p"),this.h()},l(e){const l=fe("svelte-u9bgzb",document.head);o=m(l,"META",{name:!0,content:!0}),l.forEach(t),_=s(e),F=m(e,"P",{}),ie(F).forEach(t),O=s(e),j(M.$$.fragment,e),I=s(e),j(u.$$.fragment,e),A=s(e),f=m(e,"P",{"data-svelte-h":!0}),Q(f)!=="svelte-10o1brc"&&(f.innerHTML=q),k=s(e),U=m(e,"P",{"data-svelte-h":!0}),Q(U)!=="svelte-udgf4g"&&(U.innerHTML=K),B=s(e),j(c.$$.fragment,e),v=s(e),r=m(e,"BLOCKQUOTE",{class:!0,"data-svelte-h":!0}),Q(r)!=="svelte-1pfprny"&&(r.innerHTML=ee),x=s(e),T=m(e,"P",{"data-svelte-h":!0}),Q(T)!=="svelte-trr0gu"&&(T.innerHTML=le),E=s(e),y=m(e,"P",{"data-svelte-h":!0}),Q(y)!=="svelte-1ody1vo"&&(y.innerHTML=te),G=s(e),j(C.$$.fragment,e),L=s(e),g=m(e,"P",{"data-svelte-h":!0}),Q(g)!=="svelte-1nzkau6"&&(g.textContent=ne),W=s(e),j(V.$$.fragment,e),X=s(e),p=m(e,"IMG",{src:!0,width:!0,height:!0,alt:!0}),Y=s(e),w=m(e,"P",{"data-svelte-h":!0}),Q(w)!=="svelte-1bu1s2g"&&(w.innerHTML=se),Z=s(e),j(h.$$.fragment,e),D=s(e),$=m(e,"P",{}),ie($).forEach(t),this.h()},h(){d(o,"name","hf:doc:metadata"),d(o,"content",ge),d(r,"class","tip"),oe(p.src,ae="https://huggingface.co/datasets/Jingya/document_images/resolve/main/optimum/neuron/sdxl_pig.png")||d(p,"src",ae),d(p,"width","256"),d(p,"height","256"),d(p,"alt","peggy generated by sdxl on inf2")},m(e,l){Ue(document.head,o),n(e,_,l),n(e,F,l),n(e,O,l),N(M,e,l),n(e,I,l),N(u,e,l),n(e,A,l),n(e,f,l),n(e,k,l),n(e,U,l),n(e,B,l),N(c,e,l),n(e,v,l),n(e,r,l),n(e,x,l),n(e,T,l),n(e,E,l),n(e,y,l),n(e,G,l),N(C,e,l),n(e,L,l),n(e,g,l),n(e,W,l),N(V,e,l),n(e,X,l),n(e,p,l),n(e,Y,l),n(e,w,l),n(e,Z,l),N(h,e,l),n(e,D,l),n(e,$,l),H=!0},p:pe,i(e){H||(R(M.$$.fragment,e),R(u.$$.fragment,e),R(c.$$.fragment,e),R(C.$$.fragment,e),R(V.$$.fragment,e),R(h.$$.fragment,e),H=!0)},o(e){J(M.$$.fragment,e),J(u.$$.fragment,e),J(c.$$.fragment,e),J(C.$$.fragment,e),J(V.$$.fragment,e),J(h.$$.fragment,e),H=!1},d(e){e&&(t(_),t(F),t(O),t(I),t(A),t(f),t(k),t(U),t(B),t(v),t(r),t(x),t(T),t(E),t(y),t(G),t(L),t(g),t(W),t(X),t(p),t(Y),t(w),t(Z),t(D),t($)),t(o),S(M,e),S(u,e),S(c,e),S(C,e),S(V,e),S(h,e)}}}const ge='{"title":"AWS Neuron","local":"aws-neuron","sections":[],"depth":1}';function Ve(P){return re(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class be extends Me{constructor(o){super(),ue(this,o,Ve,Ce,me,{})}}export{be as component};