import{s as pt,o as ut,n as lt}from"../chunks/scheduler.182ea377.js";import{S as ot,i as ft,g as l,s as n,r as o,A as dt,h as p,f as s,c as a,j as I,u as f,x as h,k as O,y as u,a as i,v as d,d as m,t as c,w as g}from"../chunks/index.abf12888.js";import{T as rt}from"../chunks/Tip.230e2334.js";import{D as ee}from"../chunks/Docstring.93f6f462.js";import{C as Ge}from"../chunks/CodeBlock.57fe6e13.js";import{H as oe}from"../chunks/Heading.16916d63.js";function mt(te){let r,x="To check a specific pipeline or model output, refer to its corresponding API documentation.";return{c(){r=l("p"),r.textContent=x},l($){r=p($,"P",{"data-svelte-h":!0}),h(r)!=="svelte-60gd7d"&&(r.textContent=x)},m($,T){i($,r,T)},p:lt,d($){$&&s(r)}}}function ct(te){let r,x=`You can’t unpack a <code>BaseOutput</code> directly. Use the <a href="/docs/diffusers/v0.26.0/en/api/outputs#diffusers.utils.BaseOutput.to_tuple">to_tuple()</a> method to convert it to a tuple
first.`;return{c(){r=l("p"),r.innerHTML=x},l($){r=p($,"P",{"data-svelte-h":!0}),h(r)!=="svelte-mot26u"&&(r.innerHTML=x)},m($,T){i($,r,T)},p:lt,d($){$&&s(r)}}}function gt(te){let r,x,$,T,V,de,B,We='All model outputs are subclasses of <a href="/docs/diffusers/v0.26.0/en/api/outputs#diffusers.utils.BaseOutput">BaseOutput</a>, data structures containing all the information returned by the model. The outputs can also be used as tuples or dictionaries.',me,k,Se="For example:",ce,U,ge,E,Qe='The <code>outputs</code> object is a <a href="/docs/diffusers/v0.26.0/en/api/pipelines/ddim#diffusers.ImagePipelineOutput">ImagePipelineOutput</a> which means it has an image attribute.',$e,z,Xe="You can access each attribute as you normally would or with a keyword lookup, and if that attribute is not returned by the model, you will get <code>None</code>:",he,D,be,F,Ye=`When considering the <code>outputs</code> object as a tuple, it only considers the attributes that don’t have <code>None</code> values.
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tuple) or strings (like a dictionary) that will ignore the <code>None</code> attributes. Otherwise behaves like a regular
Python dictionary.`,De,C,Fe,M,N,Je,ie,et="Convert self to a tuple containing all the attributes/keys that are not <code>None</code>.",ye,Z,we,P,q,je,ne,tt="Output class for image pipelines.",Ie,R,Oe,v,G,Ae,ae,st="Output class for image pipelines.",Ne,H,W,Ze,re,it="“Returns a new object replacing the specified fields with new values.",Te,S,Le,y,Q,qe,le,nt="Output class for audio pipelines.",Ce,X,Me,w,Y,Re,pe,at="Output class for joint image-text pipelines.",He,fe,Ve;return V=new oe({props:{title:"Outputs",local:"outputs",headingTag:"h1"}}),U=new Ge({props:{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMERESU1QaXBlbGluZSUwQSUwQXBpcGVsaW5lJTIwJTNEJTIwRERJTVBpcGVsaW5lLmZyb21fcHJldHJhaW5lZCglMjJnb29nbGUlMkZkZHBtLWNpZmFyMTAtMzIlMjIpJTBBb3V0cHV0cyUyMCUzRCUyMHBpcGVsaW5lKCk=",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DDIMPipeline

pipeline = DDIMPipeline.from_pretrained(<span class="hljs-string">&quot;google/ddpm-cifar10-32&quot;</span>)
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List of denoised PIL images of length <code>batch_size</code> or NumPy array of shape <code>(batch_size, height, width, num_channels)</code>.`,name:"images"}],source:"https://github.com/huggingface/diffusers/blob/v0.26.0/src/diffusers/pipelines/pipeline_flax_utils.py#L87"}}),W=new ee({props:{name:"replace",anchor:"diffusers.pipelines.pipeline_flax_utils.FlaxImagePipelineOutput.replace",parameters:[{name:"**updates",val:""}],source:"https://github.com/huggingface/diffusers/blob/v0.26.0/src/flax/struct.py#L111"}}),S=new oe({props:{title:"AudioPipelineOutput",local:"diffusers.AudioPipelineOutput",headingTag:"h2"}}),Q=new ee({props:{name:"class diffusers.AudioPipelineOutput",anchor:"diffusers.AudioPipelineOutput",parameters:[{name:"audios",val:": ndarray"}],parametersDescription:[{anchor:"diffusers.AudioPipelineOutput.audios",description:`<strong>audios</strong> (<code>np.ndarray</code>) &#x2014;
List of denoised audio samples of a NumPy array of shape <code>(batch_size, num_channels, sample_rate)</code>.`,name:"audios"}],source:"https://github.com/huggingface/diffusers/blob/v0.26.0/src/diffusers/pipelines/pipeline_utils.py#L130"}}),X=new oe({props:{title:"ImageTextPipelineOutput",local:"diffusers.ImageTextPipelineOutput",headingTag:"h2"}}),Y=new ee({props:{name:"class diffusers.ImageTextPipelineOutput",anchor:"diffusers.ImageTextPipelineOutput",parameters:[{name:"images",val:": Union"},{name:"text",val:": Union"}],parametersDescription:[{anchor:"diffusers.ImageTextPipelineOutput.images",description:`<strong>images</strong> (<code>List[PIL.Image.Image]</code> or <code>np.ndarray</code>) &#x2014;
List of denoised PIL images of length <code>batch_size</code> or NumPy array of shape <code>(batch_size, height, width, num_channels)</code>.`,name:"images"},{anchor:"diffusers.ImageTextPipelineOutput.text",description:`<strong>text</strong> (<code>List[str]</code> or <code>List[List[str]]</code>) &#x2014;
List of generated text strings of length <code>batch_size</code> or a list of list of strings whose outer list has
length 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