import{S as zt,i as Jt,s as Rt,e as i,k as l,w as B,t as p,M as Ft,c as a,d as t,m as d,a as n,x as V,h as f,b as o,G as r,g as h,y as Y,L as Wt,q as K,o as Q,B as X,v as jt}from"../../../chunks/vendor-hf-doc-builder.js";import{D as Ut}from"../../../chunks/Docstring-hf-doc-builder.js";import{I as ke}from"../../../chunks/IconCopyLink-hf-doc-builder.js";function Bt(ft){let u,ue,m,P,Z,A,Ne,ee,Oe,me,v,y,te,T,Le,re,qe,ve,x,I,Ce,He,ge,H,Ge,_e,G,Ue,be,w,ze,S,Je,Re,De,g,$,ie,k,Fe,ae,We,Pe,E,ne,_,oe,je,Be,se,Ve,Ye,U,Ke,Qe,le,b,de,N,Xe,Ze,pe,fe,et,tt,z,rt,ye,D,M,he,O,it,ce,at,we,c,L,nt,q,ot,J,st,lt,dt,R,C,$e;return A=new ke({}),T=new ke({}),k=new ke({}),O=new ke({}),L=new Ut({props:{name:"class diffusers.DDPMPipeline",anchor:"diffusers.DDPMPipeline",parameters:[{name:"unet",val:""},{name:"scheduler",val:""}],parametersDescription:[{anchor:"diffusers.DDPMPipeline.unet",description:'<strong>unet</strong> (<a href="/docs/diffusers/v0.17.0/en/api/models#diffusers.UNet2DModel">UNet2DModel</a>) &#x2014; U-Net architecture to denoise the encoded image.',name:"unet"},{anchor:"diffusers.DDPMPipeline.scheduler",description:`<strong>scheduler</strong> (<a href="/docs/diffusers/v0.17.0/en/api/schedulers/overview#diffusers.SchedulerMixin">SchedulerMixin</a>) &#x2014;
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<a href="/docs/diffusers/v0.17.0/en/api/schedulers/ddpm#diffusers.DDPMScheduler">DDPMScheduler</a>, or <a href="/docs/diffusers/v0.17.0/en/api/schedulers/ddim#diffusers.DDIMScheduler">DDIMScheduler</a>.`,name:"scheduler"}],source:"https://github.com/huggingface/diffusers/blob/v0.17.0/src/diffusers/pipelines/ddpm/pipeline_ddpm.py#L24"}}),C=new Ut({props:{name:"__call__",anchor:"diffusers.DDPMPipeline.__call__",parameters:[{name:"batch_size",val:": int = 1"},{name:"generator",val:": typing.Union[torch._C.Generator, typing.List[torch._C.Generator], NoneType] = None"},{name:"num_inference_steps",val:": int = 1000"},{name:"output_type",val:": typing.Optional[str] = 'pil'"},{name:"return_dict",val:": bool = True"}],parametersDescription:[{anchor:"diffusers.DDPMPipeline.__call__.batch_size",description:`<strong>batch_size</strong> (<code>int</code>, <em>optional</em>, defaults to 1) &#x2014;
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<p><code>~pipelines.utils.ImagePipelineOutput</code> if <code>return_dict</code> is
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