import{S as Ao,i as Ro,s as Ho,e as a,k as f,w as u,t as r,M as Qo,c as o,d as l,m as h,a as s,x as m,h as i,b as p,N as Yo,G as t,g as d,y as v,L as Lo,q as w,o as b,B as y,v as Fo}from"../../chunks/vendor-hf-doc-builder.js";import{I as H}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{C as dl}from"../../chunks/CodeBlock-hf-doc-builder.js";function zo(Oa){let T,Et,M,k,Je,Q,cl,ge,ul,_t,E,ml,Y,vl,wl,L,bl,yl,Tt,I,W,Se,F,El,Ue,_l,Mt,Ee,Tl,It,z,$t,_,Ml,Oe,Il,$l,q,Ve,Jl,gl,Jt,$,D,ke,K,Sl,We,Ul,gt,J,Z,De,ee,Ol,Ze,Vl,St,c,kl,Ge,Wl,Dl,Ne,Zl,Gl,je,Nl,jl,Ut,te,Ot,_e,Bl,Vt,le,kt,Te,Cl,Wt,ae,Be,Va,Dt,g,G,Ce,oe,Pl,Pe,xl,Zt,N,xe,se,Xe,Xl,Al,Ae,Rl,Hl,S,ne,Re,He,Ql,Yl,Qe,Ye,Ll,Fl,re,Le,Fe,zl,ql,ze,qe,Kl,ea,ie,Ke,et,ta,la,tt,lt,aa,Gt,j,oa,pe,sa,na,Nt,U,B,at,fe,ra,ot,ia,jt,O,C,st,he,pa,nt,fa,Bt,P,ha,de,da,ca,Ct,ce,Pt,x,ua,ue,ma,va,xt,V,X,rt,me,wa,it,ba,Xt,A,pt,ve,ft,ya,Ea,ht,_a,Ta,we,be,dt,ct,Ma,Ia,ut,mt,$a,Ja,ye,vt,wt,ga,Sa,bt,yt,Ua,At;return Q=new H({}),F=new H({}),z=new dl({props:{code:"cGlwJTIwaW5zdGFsbCUyMC0tdXBncmFkZS1zdHJhdGVneSUyMGVhZ2VyJTIwb3B0aW11bSU1QiUyMm9wZW52aW5vJTIyJTVE",highlighted:'pip install <span class="hljs-attr">--upgrade-strategy</span> eager optimum<span class="hljs-selector-attr">[<span class="hljs-string">&quot;openvino&quot;</span>]</span>'}}),K=new H({}),ee=new H({}),te=new dl({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.intel <span class="hljs-keyword">import</span> OVStableDiffusionPipeline

model_id = <span class="hljs-string">&quot;runwayml/stable-diffusion-v1-5&quot;</span>
pipeline = OVStableDiffusionPipeline.from_pretrained(model_id, export=<span class="hljs-literal">True</span>)
prompt = <span class="hljs-string">&quot;sailing ship in storm by Rembrandt&quot;</span>
image = pipeline(prompt).images[<span class="hljs-number">0</span>]

<span class="hljs-comment"># Don&#x27;t forget to save the exported model</span>
pipeline.save_pretrained(<span class="hljs-string">&quot;openvino-sd-v1-5&quot;</span>)`}}),le=new dl({props:{code:"JTIzJTIwRGVmaW5lJTIwdGhlJTIwc2hhcGVzJTIwcmVsYXRlZCUyMHRvJTIwdGhlJTIwaW5wdXRzJTIwYW5kJTIwZGVzaXJlZCUyMG91dHB1dHMlMEFiYXRjaF9zaXplJTJDJTIwbnVtX2ltYWdlcyUyQyUyMGhlaWdodCUyQyUyMHdpZHRoJTIwJTNEJTIwMSUyQyUyMDElMkMlMjA1MTIlMkMlMjA1MTIlMEElMEElMjMlMjBTdGF0aWNhbGx5JTIwcmVzaGFwZSUyMHRoZSUyMG1vZGVsJTBBcGlwZWxpbmUucmVzaGFwZShiYXRjaF9zaXplJTJDJTIwaGVpZ2h0JTJDJTIwd2lkdGglMkMlMjBudW1faW1hZ2VzKSUwQSUyMyUyMENvbXBpbGUlMjB0aGUlMjBtb2RlbCUyMGJlZm9yZSUyMGluZmVyZW5jZSUwQXBpcGVsaW5lLmNvbXBpbGUoKSUwQSUwQWltYWdlJTIwJTNEJTIwcGlwZWxpbmUoJTBBJTIwJTIwJTIwJTIwcHJvbXB0JTJDJTBBJTIwJTIwJTIwJTIwaGVpZ2h0JTNEaGVpZ2h0JTJDJTBBJTIwJTIwJTIwJTIwd2lkdGglM0R3aWR0aCUyQyUwQSUyMCUyMCUyMCUyMG51bV9pbWFnZXNfcGVyX3Byb21wdCUzRG51bV9pbWFnZXMlMkMlMEEpLmltYWdlcyU1QjAlNUQ=",highlighted:`<span class="hljs-comment"># Define the shapes related to the inputs and desired outputs</span>
batch_size, num_images, height, width = <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">512</span>, <span class="hljs-number">512</span>

<span class="hljs-comment"># Statically reshape the model</span>
pipeline.reshape(batch_size, height, width, num_images)
<span class="hljs-comment"># Compile the model before inference</span>
pipeline.<span class="hljs-built_in">compile</span>()

image = pipeline(
    prompt,
    height=height,
    width=width,
    num_images_per_prompt=num_images,
).images[<span class="hljs-number">0</span>]`}}),oe=new H({}),fe=new H({}),he=new H({}),ce=new dl({props:{code:"ZnJvbSUyMG9wdGltdW0uaW50ZWwlMjBpbXBvcnQlMjBPVlN0YWJsZURpZmZ1c2lvblhMUGlwZWxpbmUlMEElMEFtb2RlbF9pZCUyMCUzRCUyMCUyMnN0YWJpbGl0eWFpJTJGc3RhYmxlLWRpZmZ1c2lvbi14bC1iYXNlLTEuMCUyMiUwQXBpcGVsaW5lJTIwJTNEJTIwT1ZTdGFibGVEaWZmdXNpb25YTFBpcGVsaW5lLmZyb21fcHJldHJhaW5lZChtb2RlbF9pZCklMEFwcm9tcHQlMjAlM0QlMjAlMjJzYWlsaW5nJTIwc2hpcCUyMGluJTIwc3Rvcm0lMjBieSUyMFJlbWJyYW5kdCUyMiUwQWltYWdlJTIwJTNEJTIwcGlwZWxpbmUocHJvbXB0KS5pbWFnZXMlNUIwJTVE",highlighted:`<span class="hljs-keyword">from</span> optimum.intel <span class="hljs-keyword">import</span> OVStableDiffusionXLPipeline

model_id = <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>
pipeline = OVStableDiffusionXLPipeline.from_pretrained(model_id)
prompt = <span class="hljs-string">&quot;sailing ship in storm by Rembrandt&quot;</span>
image = pipeline(prompt).images[<span class="hljs-number">0</span>]`}}),me=new H({}),{c(){T=a("meta"),Et=f(),M=a("h1"),k=a("a"),Je=a("span"),u(Q.$$.fragment),cl=f(),ge=a("span"),ul=r("How to use OpenVINO for inference"),_t=f(),E=a("p"),ml=r("\u{1F917} "),Y=a("a"),vl=r("Optimum"),wl=r(" provides Stable Diffusion pipelines compatible with OpenVINO. You can now easily perform inference with OpenVINO Runtime on a variety of Intel processors ("),L=a("a"),bl=r("see"),yl=r(" the full list of supported devices)."),Tt=f(),I=a("h2"),W=a("a"),Se=a("span"),u(F.$$.fragment),El=f(),Ue=a("span"),_l=r("Installation"),Mt=f(),Ee=a("p"),Tl=r("Install \u{1F917} Optimum Intel with the following command:"),It=f(),u(z.$$.fragment),$t=f(),_=a("p"),Ml=r("The "),Oe=a("code"),Il=r("--upgrade-strategy eager"),$l=r(" option is needed to ensure "),q=a("a"),Ve=a("code"),Jl=r("optimum-intel"),gl=r(" is upgraded to its latest version."),Jt=f(),$=a("h2"),D=a("a"),ke=a("span"),u(K.$$.fragment),Sl=f(),We=a("span"),Ul=r("Stable Diffusion"),gt=f(),J=a("h3"),Z=a("a"),De=a("span"),u(ee.$$.fragment),Ol=f(),Ze=a("span"),Vl=r("Inference"),St=f(),c=a("p"),kl=r("To load an OpenVINO model and run inference with OpenVINO Runtime, you need to replace "),Ge=a("code"),Wl=r("StableDiffusionPipeline"),Dl=r(" with "),Ne=a("code"),Zl=r("OVStableDiffusionPipeline"),Gl=r(". In case you want to load a PyTorch model and convert it to the OpenVINO format on-the-fly, you can set "),je=a("code"),Nl=r("export=True"),jl=r("."),Ut=f(),u(te.$$.fragment),Ot=f(),_e=a("p"),Bl=r("To further speed up inference, the model can be statically reshaped :"),Vt=f(),u(le.$$.fragment),kt=f(),Te=a("p"),Cl=r("In case you want to change any parameters such as the outputs height or width, you\u2019ll need to statically reshape your model once again."),Wt=f(),ae=a("div"),Be=a("img"),Dt=f(),g=a("h3"),G=a("a"),Ce=a("span"),u(oe.$$.fragment),Pl=f(),Pe=a("span"),xl=r("Supported tasks"),Zt=f(),N=a("table"),xe=a("thead"),se=a("tr"),Xe=a("th"),Xl=r("Task"),Al=f(),Ae=a("th"),Rl=r("Loading Class"),Hl=f(),S=a("tbody"),ne=a("tr"),Re=a("td"),He=a("code"),Ql=r("text-to-image"),Yl=f(),Qe=a("td"),Ye=a("code"),Ll=r("OVStableDiffusionPipeline"),Fl=f(),re=a("tr"),Le=a("td"),Fe=a("code"),zl=r("image-to-image"),ql=f(),ze=a("td"),qe=a("code"),Kl=r("OVStableDiffusionImg2ImgPipeline"),ea=f(),ie=a("tr"),Ke=a("td"),et=a("code"),ta=r("inpaint"),la=f(),tt=a("td"),lt=a("code"),aa=r("OVStableDiffusionInpaintPipeline"),Gt=f(),j=a("p"),oa=r("You can find more examples in the optimum "),pe=a("a"),sa=r("documentation"),na=r("."),Nt=f(),U=a("h2"),B=a("a"),at=a("span"),u(fe.$$.fragment),ra=f(),ot=a("span"),ia=r("Stable Diffusion XL"),jt=f(),O=a("h3"),C=a("a"),st=a("span"),u(he.$$.fragment),pa=f(),nt=a("span"),fa=r("Inference"),Bt=f(),P=a("p"),ha=r("Here is an example of how you can load a SDXL OpenVINO model from "),de=a("a"),da=r("stabilityai/stable-diffusion-xl-base-1.0"),ca=r(" and run inference with OpenVINO Runtime :"),Ct=f(),u(ce.$$.fragment),Pt=f(),x=a("p"),ua=r(`To further speed up inference, the model can be statically reshaped as showed above.
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