diffusers/pr_12403/zh/_app/immutable/nodes/29.f0987a88.js

import{s as se,h as ie,o as me,n as oe}from"../chunks/scheduler.5c93273d.js";import{S as pe,i as re,g as o,s,r as N,A as ue,h as p,f as t,c as i,j as ae,u as R,x as Q,k as b,y as Me,a as n,v as $,d as J,t as S,w as F}from"../chunks/index.e43dd92b.js";import{T as fe}from"../chunks/Tip.3538f9e3.js";import{C as H}from"../chunks/CodeBlock.6896320e.js";import{H as ce,E as Ue}from"../chunks/getInferenceSnippets.161194d2.js";function Te(A){let a,M='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。';return{c(){a=o("p"),a.innerHTML=M},l(m){a=p(m,"P",{"data-svelte-h":!0}),Q(a)!=="svelte-1iylva9"&&(a.innerHTML=M)},m(m,j){n(m,a,j)},p:oe,d(m){m&&t(a)}}}function ye(A){let a,M,m,j,f,I,c,z='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。',O,U,P='<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,T,k,u,v,y,q="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,g,K="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,W,V,ee="现在使用预编译的 SDXL 模型生成一些图像。",x,w,X,r,le,Y,h,te='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！',L,d,Z,_,D;return f=new ce({props:{title:"AWS Neuron",local:"aws-neuron",headingTag:"h1"}}),T=new H({props:{code:"cHl0aG9uJTIwLW0lMjBwaXAlMjBpbnN0YWxsJTIwLS11cGdyYWRlLXN0cmF0ZWd5JTIwZWFnZXIlMjBvcHRpbXVtJTVCbmV1cm9ueCU1RA==",highlighted:"python -m pip install --upgrade-strategy eager optimum[neuronx]",wrap:!1}}),u=new fe({props:{$$slots:{default:[Te]},$$scope:{ctx:A}}}),C=new H({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}}),w=new H({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}}),d=new Ue({props:{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/zh/optimization/neuron.md"}}),{c(){a=o("meta"),M=s(),m=o("p"),j=s(),N(f.$$.fragment),I=s(),c=o("p"),c.innerHTML=z,O=s(),U=o("p"),U.innerHTML=P,B=s(),N(T.$$.fragment),k=s(),N(u.$$.fragment),v=s(),y=o("p"),y.innerHTML=q,E=s(),g=o("p"),g.innerHTML=K,G=s(),N(C.$$.fragment),W=s(),V=o("p"),V.textContent=ee,x=s(),N(w.$$.fragment),X=s(),r=o("img"),Y=s(),h=o("p"),h.innerHTML=te,L=s(),N(d.$$.fragment),Z=s(),_=o("p"),this.h()},l(e){const l=ue("svelte-u9bgzb",document.head);a=p(l,"META",{name:!0,content:!0}),l.forEach(t),M=i(e),m=p(e,"P",{}),ae(m).forEach(t),j=i(e),R(f.$$.fragment,e),I=i(e),c=p(e,"P",{"data-svelte-h":!0}),Q(c)!=="svelte-10o1brc"&&(c.innerHTML=z),O=i(e),U=p(e,"P",{"data-svelte-h":!0}),Q(U)!=="svelte-udgf4g"&&(U.innerHTML=P),B=i(e),R(T.$$.fragment,e),k=i(e),R(u.$$.fragment,e),v=i(e),y=p(e,"P",{"data-svelte-h":!0}),Q(y)!=="svelte-trr0gu"&&(y.innerHTML=q),E=i(e),g=p(e,"P",{"data-svelte-h":!0}),Q(g)!=="svelte-1ody1vo"&&(g.innerHTML=K),G=i(e),R(C.$$.fragment,e),W=i(e),V=p(e,"P",{"data-svelte-h":!0}),Q(V)!=="svelte-1nzkau6"&&(V.textContent=ee),x=i(e),R(w.$$.fragment,e),X=i(e),r=p(e,"IMG",{src:!0,width:!0,height:!0,alt:!0}),Y=i(e),h=p(e,"P",{"data-svelte-h":!0}),Q(h)!=="svelte-1bu1s2g"&&(h.innerHTML=te),L=i(e),R(d.$$.fragment,e),Z=i(e),_=p(e,"P",{}),ae(_).forEach(t),this.h()},h(){b(a,"name","hf:doc:metadata"),b(a,"content",ge),ie(r.src,le="https://huggingface.co/datasets/Jingya/document_images/resolve/main/optimum/neuron/sdxl_pig.png")||b(r,"src",le),b(r,"width","256"),b(r,"height","256"),b(r,"alt","peggy generated by sdxl on inf2")},m(e,l){Me(document.head,a),n(e,M,l),n(e,m,l),n(e,j,l),$(f,e,l),n(e,I,l),n(e,c,l),n(e,O,l),n(e,U,l),n(e,B,l),$(T,e,l),n(e,k,l),$(u,e,l),n(e,v,l),n(e,y,l),n(e,E,l),n(e,g,l),n(e,G,l),$(C,e,l),n(e,W,l),n(e,V,l),n(e,x,l),$(w,e,l),n(e,X,l),n(e,r,l),n(e,Y,l),n(e,h,l),n(e,L,l),$(d,e,l),n(e,Z,l),n(e,_,l),D=!0},p(e,[l]){const ne={};l&2&&(ne.$$scope={dirty:l,ctx:e}),u.$set(ne)},i(e){D||(J(f.$$.fragment,e),J(T.$$.fragment,e),J(u.$$.fragment,e),J(C.$$.fragment,e),J(w.$$.fragment,e),J(d.$$.fragment,e),D=!0)},o(e){S(f.$$.fragment,e),S(T.$$.fragment,e),S(u.$$.fragment,e),S(C.$$.fragment,e),S(w.$$.fragment,e),S(d.$$.fragment,e),D=!1},d(e){e&&(t(M),t(m),t(j),t(I),t(c),t(O),t(U),t(B),t(k),t(v),t(y),t(E),t(g),t(G),t(W),t(V),t(x),t(X),t(r),t(Y),t(h),t(L),t(Z),t(_)),t(a),F(f,e),F(T,e),F(u,e),F(C,e),F(w,e),F(d,e)}}}const ge='{"title":"AWS Neuron","local":"aws-neuron","sections":[],"depth":1}';function Ce(A){return me(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class je extends pe{constructor(a){super(),re(this,a,Ce,ye,se,{})}}export{je as component};