import{S as zr,i as Fr,s as Yr,e as i,k as a,w as c,t as f,M as qr,c as r,d as t,m as l,a as o,x as m,h as u,b as n,N as Hr,G as s,g as p,y as h,L as Kr,q as g,o as _,B as v,v as Or}from"../../../chunks/vendor-hf-doc-builder.js";import{D as $}from"../../../chunks/Docstring-hf-doc-builder.js";import{C as $t}from"../../../chunks/CodeBlock-hf-doc-builder.js";import{I as E}from"../../../chunks/IconCopyLink-hf-doc-builder.js";function eo(Bi){let D,Js,A,N,ze,ae,Mt,Fe,Et,js,k,S,Ye,le,Dt,qe,At,Is,de,pe,kt,xt,Us,Xe,Tt,Gs,X,Pt,fe,Jt,jt,Ws,x,V,He,ue,It,Ke,Ut,Zs,R,Oe,T,es,Gt,Wt,ss,Zt,Nt,Ve,St,Xt,ts,P,is,ce,Vt,Rt,rs,os,Bt,Lt,Re,me,Be,Li,Ns,J,B,ns,he,Ct,as,Qt,Ss,j,L,ls,ge,zt,ds,Ft,Xs,_e,Vs,I,C,ps,ve,Yt,fs,qt,Rs,be,Bs,U,Q,us,we,Ht,cs,Kt,Ls,ye,Cs,G,z,ms,$e,Ot,hs,ei,Qs,Me,zs,W,F,gs,Ee,si,_s,ti,Fs,w,De,ii,Ae,ri,Le,oi,ni,ai,Y,ke,li,vs,di,pi,q,xe,fi,bs,ui,ci,H,Te,mi,ws,hi,gi,K,Pe,_i,ys,vi,Ys,Z,O,$s,Je,bi,Ms,wi,qs,b,je,yi,ee,Ie,$i,Es,Mi,Ei,se,Ue,Di,Ds,Ai,ki,te,Ge,xi,As,Ti,Pi,ie,We,Ji,ks,ji,Ii,re,Ze,Ui,xs,Gi,Wi,oe,Ne,Zi,Ts,Ni,Si,ne,Se,Xi,Ps,Vi,Hs;return ae=new E({}),le=new E({}),ue=new E({}),he=new E({}),ge=new E({}),_e=new $t({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> IPython.display <span class="hljs-keyword">import</span> Audio
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

device = <span class="hljs-string">&quot;cuda&quot;</span> <span class="hljs-keyword">if</span> torch.cuda.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">&quot;cpu&quot;</span>
pipe = DiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;teticio/audio-diffusion-256&quot;</span>).to(device)

output = pipe()
display(output.images[<span class="hljs-number">0</span>])
display(Audio(output.audios[<span class="hljs-number">0</span>], rate=pipe.mel.get_sample_rate()))`}}),ve=new E({}),be=new $t({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> IPython.display <span class="hljs-keyword">import</span> Audio
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

device = <span class="hljs-string">&quot;cuda&quot;</span> <span class="hljs-keyword">if</span> torch.cuda.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">&quot;cpu&quot;</span>
pipe = DiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;teticio/latent-audio-diffusion-256&quot;</span>).to(device)

output = pipe()
display(output.images[<span class="hljs-number">0</span>])
display(Audio(output.audios[<span class="hljs-number">0</span>], rate=pipe.mel.get_sample_rate()))`}}),we=new E({}),ye=new $t({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> IPython.display <span class="hljs-keyword">import</span> Audio
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

device = <span class="hljs-string">&quot;cuda&quot;</span> <span class="hljs-keyword">if</span> torch.cuda.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">&quot;cpu&quot;</span>
pipe = DiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;teticio/audio-diffusion-ddim-256&quot;</span>).to(device)

output = pipe()
display(output.images[<span class="hljs-number">0</span>])
display(Audio(output.audios[<span class="hljs-number">0</span>], rate=pipe.mel.get_sample_rate()))`}}),$e=new E({}),Me=new $t({props:{code:"b3V0cHV0JTIwJTNEJTIwcGlwZSglMEElMjAlMjAlMjAlMjByYXdfYXVkaW8lM0RvdXRwdXQuYXVkaW9zJTVCMCUyQyUyMDAlNUQlMkMlMEElMjAlMjAlMjAlMjBzdGFydF9zdGVwJTNEaW50KHBpcGUuZ2V0X2RlZmF1bHRfc3RlcHMoKSUyMCUyRiUyMDIpJTJDJTBBJTIwJTIwJTIwJTIwbWFza19zdGFydF9zZWNzJTNEMSUyQyUwQSUyMCUyMCUyMCUyMG1hc2tfZW5kX3NlY3MlM0QxJTJDJTBBKSUwQWRpc3BsYXkob3V0cHV0LmltYWdlcyU1QjAlNUQpJTBBZGlzcGxheShBdWRpbyhvdXRwdXQuYXVkaW9zJTVCMCU1RCUyQyUyMHJhdGUlM0RwaXBlLm1lbC5nZXRfc2FtcGxlX3JhdGUoKSkp",highlighted:`output = pipe(
    raw_audio=output.audios[<span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
    start_step=<span class="hljs-built_in">int</span>(pipe.get_default_steps() / <span class="hljs-number">2</span>),
    mask_start_secs=<span class="hljs-number">1</span>,
    mask_end_secs=<span class="hljs-number">1</span>,
)
display(output.images[<span class="hljs-number">0</span>])
display(Audio(output.audios[<span class="hljs-number">0</span>], rate=pipe.mel.get_sample_rate()))`}}),Ee=new E({}),De=new $({props:{name:"class diffusers.AudioDiffusionPipeline",anchor:"diffusers.AudioDiffusionPipeline",parameters:[{name:"vqvae",val:": AutoencoderKL"},{name:"unet",val:": UNet2DConditionModel"},{name:"mel",val:": Mel"},{name:"scheduler",val:": typing.Union[diffusers.schedulers.scheduling_ddim.DDIMScheduler, diffusers.schedulers.scheduling_ddpm.DDPMScheduler]"}],parametersDescription:[{anchor:"diffusers.AudioDiffusionPipeline.vqae",description:'<strong>vqae</strong> (<a href="/docs/diffusers/v0.18.2/en/api/models/autoencoderkl#diffusers.AutoencoderKL">AutoencoderKL</a>) &#x2014; Variational AutoEncoder for Latent Audio Diffusion or None',name:"vqae"},{anchor:"diffusers.AudioDiffusionPipeline.unet",description:'<strong>unet</strong> (<a href="/docs/diffusers/v0.18.2/en/api/models/unet2d-cond#diffusers.UNet2DConditionModel">UNet2DConditionModel</a>) &#x2014; UNET model',name:"unet"},{anchor:"diffusers.AudioDiffusionPipeline.mel",description:'<strong>mel</strong> (<a href="/docs/diffusers/v0.18.2/en/api/pipelines/audio_diffusion#diffusers.Mel">Mel</a>) &#x2014; transform audio &lt;-&gt; spectrogram',name:"mel"},{anchor:"diffusers.AudioDiffusionPipeline.scheduler",description:"<strong>scheduler</strong> ([<code>DDIMScheduler</code> or <code>DDPMScheduler</code>]) &#x2014; de-noising scheduler",name:"scheduler"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/pipeline_audio_diffusion.py#L30"}}),ke=new $({props:{name:"__call__",anchor:"diffusers.AudioDiffusionPipeline.__call__",parameters:[{name:"batch_size",val:": int = 1"},{name:"audio_file",val:": str = None"},{name:"raw_audio",val:": ndarray = None"},{name:"slice",val:": int = 0"},{name:"start_step",val:": int = 0"},{name:"steps",val:": int = None"},{name:"generator",val:": Generator = None"},{name:"mask_start_secs",val:": float = 0"},{name:"mask_end_secs",val:": float = 0"},{name:"step_generator",val:": Generator = None"},{name:"eta",val:": float = 0"},{name:"noise",val:": Tensor = None"},{name:"encoding",val:": Tensor = None"},{name:"return_dict",val:" = True"}],parametersDescription:[{anchor:"diffusers.AudioDiffusionPipeline.__call__.batch_size",description:"<strong>batch_size</strong> (<code>int</code>) &#x2014; number of samples to generate",name:"batch_size"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.audio_file",description:"<strong>audio_file</strong> (<code>str</code>) &#x2014; must be a file on disk due to Librosa limitation or",name:"audio_file"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.raw_audio",description:"<strong>raw_audio</strong> (<code>np.ndarray</code>) &#x2014; audio as numpy array",name:"raw_audio"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.slice",description:"<strong>slice</strong> (<code>int</code>) &#x2014; slice number of audio to convert",name:"slice"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.start_step",description:"<strong>start_step</strong> (int) &#x2014; step to start from",name:"start_step"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.steps",description:"<strong>steps</strong> (<code>int</code>) &#x2014; number of de-noising steps (defaults to 50 for DDIM, 1000 for DDPM)",name:"steps"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.generator",description:"<strong>generator</strong> (<code>torch.Generator</code>) &#x2014; random number generator or None",name:"generator"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.mask_start_secs",description:"<strong>mask_start_secs</strong> (<code>float</code>) &#x2014; number of seconds of audio to mask (not generate) at start",name:"mask_start_secs"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.mask_end_secs",description:"<strong>mask_end_secs</strong> (<code>float</code>) &#x2014; number of seconds of audio to mask (not generate) at end",name:"mask_end_secs"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.step_generator",description:"<strong>step_generator</strong> (<code>torch.Generator</code>) &#x2014; random number generator used to de-noise or None",name:"step_generator"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.eta",description:"<strong>eta</strong> (<code>float</code>) &#x2014; parameter between 0 and 1 used with DDIM scheduler",name:"eta"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.noise",description:"<strong>noise</strong> (<code>torch.Tensor</code>) &#x2014; noise tensor of shape (batch_size, 1, height, width) or None",name:"noise"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.encoding",description:"<strong>encoding</strong> (<code>torch.Tensor</code>) &#x2014; for UNet2DConditionModel shape (batch_size, seq_length, cross_attention_dim)",name:"encoding"},{anchor:"diffusers.AudioDiffusionPipeline.__call__.return_dict",description:"<strong>return_dict</strong> (<code>bool</code>) &#x2014; if True return AudioPipelineOutput, ImagePipelineOutput else Tuple",name:"return_dict"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/pipeline_audio_diffusion.py#L62",returnDescription:`
<p>mel spectrograms (<code>float</code>, <code>List[np.ndarray]</code>): sample rate and raw audios</p>
`,returnType:`
<p><code>List[PIL Image]</code></p>
`}}),xe=new $({props:{name:"encode",anchor:"diffusers.AudioDiffusionPipeline.encode",parameters:[{name:"images",val:": typing.List[PIL.Image.Image]"},{name:"steps",val:": int = 50"}],parametersDescription:[{anchor:"diffusers.AudioDiffusionPipeline.encode.images",description:"<strong>images</strong> (<code>List[PIL Image]</code>) &#x2014; list of images to encode",name:"images"},{anchor:"diffusers.AudioDiffusionPipeline.encode.steps",description:"<strong>steps</strong> (<code>int</code>) &#x2014; number of encoding steps to perform (defaults to 50)",name:"steps"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/pipeline_audio_diffusion.py#L198",returnDescription:`
<p>noise tensor of shape (batch_size, 1, height, width)</p>
`,returnType:`
<p><code>np.ndarray</code></p>
`}}),Te=new $({props:{name:"get_default_steps",anchor:"diffusers.AudioDiffusionPipeline.get_default_steps",parameters:[],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/pipeline_audio_diffusion.py#L54",returnDescription:`
<p>number of steps</p>
`,returnType:`
<p><code>int</code></p>
`}}),Pe=new $({props:{name:"slerp",anchor:"diffusers.AudioDiffusionPipeline.slerp",parameters:[{name:"x0",val:": Tensor"},{name:"x1",val:": Tensor"},{name:"alpha",val:": float"}],parametersDescription:[{anchor:"diffusers.AudioDiffusionPipeline.slerp.x0",description:"<strong>x0</strong> (<code>torch.Tensor</code>) &#x2014; first tensor to interpolate between",name:"x0"},{anchor:"diffusers.AudioDiffusionPipeline.slerp.x1",description:"<strong>x1</strong> (<code>torch.Tensor</code>) &#x2014; seconds tensor to interpolate between",name:"x1"},{anchor:"diffusers.AudioDiffusionPipeline.slerp.alpha",description:"<strong>alpha</strong> (<code>float</code>) &#x2014; interpolation between 0 and 1",name:"alpha"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/pipeline_audio_diffusion.py#L235",returnDescription:`
<p>interpolated tensor</p>
`,returnType:`
<p><code>torch.Tensor</code></p>
`}}),Je=new E({}),je=new $({props:{name:"class diffusers.Mel",anchor:"diffusers.Mel",parameters:[{name:"x_res",val:": int = 256"},{name:"y_res",val:": int = 256"},{name:"sample_rate",val:": int = 22050"},{name:"n_fft",val:": int = 2048"},{name:"hop_length",val:": int = 512"},{name:"top_db",val:": int = 80"},{name:"n_iter",val:": int = 32"}],parametersDescription:[{anchor:"diffusers.Mel.x_res",description:"<strong>x_res</strong> (<code>int</code>) &#x2014; x resolution of spectrogram (time)",name:"x_res"},{anchor:"diffusers.Mel.y_res",description:"<strong>y_res</strong> (<code>int</code>) &#x2014; y resolution of spectrogram (frequency bins)",name:"y_res"},{anchor:"diffusers.Mel.sample_rate",description:"<strong>sample_rate</strong> (<code>int</code>) &#x2014; sample rate of audio",name:"sample_rate"},{anchor:"diffusers.Mel.n_fft",description:"<strong>n_fft</strong> (<code>int</code>) &#x2014; number of Fast Fourier Transforms",name:"n_fft"},{anchor:"diffusers.Mel.hop_length",description:"<strong>hop_length</strong> (<code>int</code>) &#x2014; hop length (a higher number is recommended for lower than 256 y_res)",name:"hop_length"},{anchor:"diffusers.Mel.top_db",description:"<strong>top_db</strong> (<code>int</code>) &#x2014; loudest in decibels",name:"top_db"},{anchor:"diffusers.Mel.n_iter",description:"<strong>n_iter</strong> (<code>int</code>) &#x2014; number of iterations for Griffin Linn mel inversion",name:"n_iter"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L37"}}),Ie=new $({props:{name:"audio_slice_to_image",anchor:"diffusers.Mel.audio_slice_to_image",parameters:[{name:"slice",val:": int"}],parametersDescription:[{anchor:"diffusers.Mel.audio_slice_to_image.slice",description:"<strong>slice</strong> (<code>int</code>) &#x2014; slice number of audio to convert (out of get_number_of_slices())",name:"slice"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L128",returnDescription:`
<p>grayscale image of x_res x y_res</p>
`,returnType:`
<p><code>PIL Image</code></p>
`}}),Ue=new $({props:{name:"get_audio_slice",anchor:"diffusers.Mel.get_audio_slice",parameters:[{name:"slice",val:": int = 0"}],parametersDescription:[{anchor:"diffusers.Mel.get_audio_slice.slice",description:"<strong>slice</strong> (<code>int</code>) &#x2014; slice number of audio (out of get_number_of_slices())",name:"slice"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L109",returnDescription:`
<p>audio as numpy array</p>
`,returnType:`
<p><code>np.ndarray</code></p>
`}}),Ge=new $({props:{name:"get_number_of_slices",anchor:"diffusers.Mel.get_number_of_slices",parameters:[],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L101",returnDescription:`
<p>number of spectograms audio can be sliced into</p>
`,returnType:`
<p><code>int</code></p>
`}}),We=new $({props:{name:"get_sample_rate",anchor:"diffusers.Mel.get_sample_rate",parameters:[],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L120",returnDescription:`
<p>sample rate of audio</p>
`,returnType:`
<p><code>int</code></p>
`}}),Ze=new $({props:{name:"image_to_audio",anchor:"diffusers.Mel.image_to_audio",parameters:[{name:"image",val:": Image"}],parametersDescription:[{anchor:"diffusers.Mel.image_to_audio.image",description:"<strong>image</strong> (<code>PIL Image</code>) &#x2014; x_res x y_res grayscale image",name:"image"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L145",returnDescription:`
<p>raw audio</p>
`,returnType:`
<p>audio (<code>np.ndarray</code>)</p>
`}}),Ne=new $({props:{name:"load_audio",anchor:"diffusers.Mel.load_audio",parameters:[{name:"audio_file",val:": str = None"},{name:"raw_audio",val:": ndarray = None"}],parametersDescription:[{anchor:"diffusers.Mel.load_audio.audio_file",description:"<strong>audio_file</strong> (<code>str</code>) &#x2014; must be a file on disk due to Librosa limitation or",name:"audio_file"},{anchor:"diffusers.Mel.load_audio.raw_audio",description:"<strong>raw_audio</strong> (<code>np.ndarray</code>) &#x2014; audio as numpy array",name:"raw_audio"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L85"}}),Se=new $({props:{name:"set_resolution",anchor:"diffusers.Mel.set_resolution",parameters:[{name:"x_res",val:": int"},{name:"y_res",val:": int"}],parametersDescription:[{anchor:"diffusers.Mel.set_resolution.x_res",description:"<strong>x_res</strong> (<code>int</code>) &#x2014; x resolution of spectrogram (time)",name:"x_res"},{anchor:"diffusers.Mel.set_resolution.y_res",description:"<strong>y_res</strong> (<code>int</code>) &#x2014; y resolution of spectrogram (frequency bins)",name:"y_res"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/pipelines/audio_diffusion/mel.py#L73"}}),{c(){D=i("meta"),Js=a(),A=i("h1"),N=i("a"),ze=i("span"),c(ae.$$.fragment),Mt=a(),Fe=i("span"),Et=f("Audio Diffusion"),js=a(),k=i("h2"),S=i("a"),Ye=i("span"),c(le.$$.fragment),Dt=a(),qe=i("span"),At=f("Overview"),Is=a(),de=i("p"),pe=i("a"),kt=f("Audio Diffusion"),xt=f(" by Robert Dargavel Smith."),Us=a(),Xe=i("p"),Tt=f(`Audio Diffusion leverages the recent advances in image generation using diffusion models by converting audio samples to
and from mel spectrogram images.`),Gs=a(),X=i("p"),Pt=f("The original codebase of this implementation can be found "),fe=i("a"),Jt=f("here"),jt=f(`, including
training scripts and example notebooks.`),Ws=a(),x=i("h2"),V=i("a"),He=i("span"),c(ue.$$.fragment),It=a(),Ke=i("span"),Ut=f("Available Pipelines:"),Zs=a(),R=i("table"),Oe=i("thead"),T=i("tr"),es=i("th"),Gt=f("Pipeline"),Wt=a(),ss=i("th"),Zt=f("Tasks"),Nt=a(),Ve=i("th"),St=f("Colab"),Xt=a(),ts=i("tbody"),P=i("tr"),is=i("td"),ce=i("a"),Vt=f("pipeline_audio_diffusion.py"),Rt=a(),rs=i("td"),os=i("em"),Bt=f("Unconditional Audio Generation"),Lt=a(),Re=i("td"),me=i("a"),Be=i("img"),Ns=a(),J=i("h2"),B=i("a"),ns=i("span"),c(he.$$.fragment),Ct=a(),as=i("span"),Qt=f("Examples:"),Ss=a(),j=i("h3"),L=i("a"),ls=i("span"),c(ge.$$.fragment),zt=a(),ds=i("span"),Ft=f("Audio Diffusion"),Xs=a(),c(_e.$$.fragment),Vs=a(),I=i("h3"),C=i("a"),ps=i("span"),c(ve.$$.fragment),Yt=a(),fs=i("span"),qt=f("Latent Audio Diffusion"),Rs=a(),c(be.$$.fragment),Bs=a(),U=i("h3"),Q=i("a"),us=i("span"),c(we.$$.fragment),Ht=a(),cs=i("span"),Kt=f("Audio Diffusion with DDIM (faster)"),Ls=a(),c(ye.$$.fragment),Cs=a(),G=i("h3"),z=i("a"),ms=i("span"),c($e.$$.fragment),Ot=a(),hs=i("span"),ei=f("Variations, in-painting, out-painting etc."),Qs=a(),c(Me.$$.fragment),zs=a(),W=i("h2"),F=i("a"),gs=i("span"),c(Ee.$$.fragment),si=a(),_s=i("span"),ti=f("AudioDiffusionPipeline"),Fs=a(),w=i("div"),c(De.$$.fragment),ii=a(),Ae=i("p"),ri=f("This model inherits from "),Le=i("a"),oi=f("DiffusionPipeline"),ni=f(`. Check the superclass documentation for the generic methods the
library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)`),ai=a(),Y=i("div"),c(ke.$$.fragment),li=a(),vs=i("p"),di=f("Generate random mel spectrogram from audio input and convert to audio."),pi=a(),q=i("div"),c(xe.$$.fragment),fi=a(),bs=i("p"),ui=f("Reverse step process: recover noisy image from generated image."),ci=a(),H=i("div"),c(Te.$$.fragment),mi=a(),ws=i("p"),hi=f("Returns default number of steps recommended for inference"),gi=a(),K=i("div"),c(Pe.$$.fragment),_i=a(),ys=i("p"),vi=f("Spherical Linear intERPolation"),Ys=a(),Z=i("h2"),O=i("a"),$s=i("span"),c(Je.$$.fragment),bi=a(),Ms=i("span"),wi=f("Mel"),qs=a(),b=i("div"),c(je.$$.fragment),yi=a(),ee=i("div"),c(Ie.$$.fragment),$i=a(),Es=i("p"),Mi=f("Convert slice of audio to spectrogram."),Ei=a(),se=i("div"),c(Ue.$$.fragment),Di=a(),Ds=i("p"),Ai=f("Get slice of audio."),ki=a(),te=i("div"),c(Ge.$$.fragment),xi=a(),As=i("p"),Ti=f("Get number of slices in audio."),Pi=a(),ie=i("div"),c(We.$$.fragment),Ji=a(),ks=i("p"),ji=f("Get sample rate:"),Ii=a(),re=i("div"),c(Ze.$$.fragment),Ui=a(),xs=i("p"),Gi=f("Converts spectrogram to audio."),Wi=a(),oe=i("div"),c(Ne.$$.fragment),Zi=a(),Ts=i("p"),Ni=f("Load audio."),Si=a(),ne=i("div"),c(Se.$$.fragment),Xi=a(),Ps=i("p"),Vi=f("Set resolution."),this.h()},l(e){const d=qr('[data-svelte="svelte-1phssyn"]',document.head);D=r(d,"META",{name:!0,content:!0}),d.forEach(t),Js=l(e),A=r(e,"H1",{class:!0});var Ks=o(A);N=r(Ks,"A",{id:!0,class:!0,href:!0});var Ci=o(N);ze=r(Ci,"SPAN",{});var Qi=o(ze);m(ae.$$.fragment,Qi),Qi.forEach(t),Ci.forEach(t),Mt=l(Ks),Fe=r(Ks,"SPAN",{});var zi=o(Fe);Et=u(zi,"Audio Diffusion"),zi.forEach(t),Ks.forEach(t),js=l(e),k=r(e,"H2",{class:!0});var Os=o(k);S=r(Os,"A",{id:!0,class:!0,href:!0});var Fi=o(S);Ye=r(Fi,"SPAN",{});var Yi=o(Ye);m(le.$$.fragment,Yi),Yi.forEach(t),Fi.forEach(t),Dt=l(Os),qe=r(Os,"SPAN",{});var qi=o(qe);At=u(qi,"Overview"),qi.forEach(t),Os.forEach(t),Is=l(e),de=r(e,"P",{});var Ri=o(de);pe=r(Ri,"A",{href:!0,rel:!0});var Hi=o(pe);kt=u(Hi,"Audio Diffusion"),Hi.forEach(t),xt=u(Ri," by Robert Dargavel Smith."),Ri.forEach(t),Us=l(e),Xe=r(e,"P",{});var Ki=o(Xe);Tt=u(Ki,`Audio Diffusion leverages the recent advances in image generation using diffusion models by converting audio samples to
and from mel spectrogram images.`),Ki.forEach(t),Gs=l(e),X=r(e,"P",{});var et=o(X);Pt=u(et,"The original codebase of this implementation can be found "),fe=r(et,"A",{href:!0,rel:!0});var Oi=o(fe);Jt=u(Oi,"here"),Oi.forEach(t),jt=u(et,`, including
training scripts and example notebooks.`),et.forEach(t),Ws=l(e),x=r(e,"H2",{class:!0});var st=o(x);V=r(st,"A",{id:!0,class:!0,href:!0});var er=o(V);He=r(er,"SPAN",{});var sr=o(He);m(ue.$$.fragment,sr),sr.forEach(t),er.forEach(t),It=l(st),Ke=r(st,"SPAN",{});var tr=o(Ke);Ut=u(tr,"Available Pipelines:"),tr.forEach(t),st.forEach(t),Zs=l(e),R=r(e,"TABLE",{});var tt=o(R);Oe=r(tt,"THEAD",{});var ir=o(Oe);T=r(ir,"TR",{});var Ce=o(T);es=r(Ce,"TH",{});var rr=o(es);Gt=u(rr,"Pipeline"),rr.forEach(t),Wt=l(Ce),ss=r(Ce,"TH",{});var or=o(ss);Zt=u(or,"Tasks"),or.forEach(t),Nt=l(Ce),Ve=r(Ce,"TH",{align:!0});var nr=o(Ve);St=u(nr,"Colab"),nr.forEach(t),Ce.forEach(t),ir.forEach(t),Xt=l(tt),ts=r(tt,"TBODY",{});var ar=o(ts);P=r(ar,"TR",{});var Qe=o(P);is=r(Qe,"TD",{});var lr=o(is);ce=r(lr,"A",{href:!0,rel:!0});var dr=o(ce);Vt=u(dr,"pipeline_audio_diffusion.py"),dr.forEach(t),lr.forEach(t),Rt=l(Qe),rs=r(Qe,"TD",{});var pr=o(rs);os=r(pr,"EM",{});var fr=o(os);Bt=u(fr,"Unconditional Audio Generation"),fr.forEach(t),pr.forEach(t),Lt=l(Qe),Re=r(Qe,"TD",{align:!0});var ur=o(Re);me=r(ur,"A",{href:!0,rel:!0});var cr=o(me);Be=r(cr,"IMG",{src:!0,alt:!0}),cr.forEach(t),ur.forEach(t),Qe.forEach(t),ar.forEach(t),tt.forEach(t),Ns=l(e),J=r(e,"H2",{class:!0});var it=o(J);B=r(it,"A",{id:!0,class:!0,href:!0});var mr=o(B);ns=r(mr,"SPAN",{});var hr=o(ns);m(he.$$.fragment,hr),hr.forEach(t),mr.forEach(t),Ct=l(it),as=r(it,"SPAN",{});var gr=o(as);Qt=u(gr,"Examples:"),gr.forEach(t),it.forEach(t),Ss=l(e),j=r(e,"H3",{class:!0});var rt=o(j);L=r(rt,"A",{id:!0,class:!0,href:!0});var _r=o(L);ls=r(_r,"SPAN",{});var vr=o(ls);m(ge.$$.fragment,vr),vr.forEach(t),_r.forEach(t),zt=l(rt),ds=r(rt,"SPAN",{});var br=o(ds);Ft=u(br,"Audio Diffusion"),br.forEach(t),rt.forEach(t),Xs=l(e),m(_e.$$.fragment,e),Vs=l(e),I=r(e,"H3",{class:!0});var ot=o(I);C=r(ot,"A",{id:!0,class:!0,href:!0});var wr=o(C);ps=r(wr,"SPAN",{});var yr=o(ps);m(ve.$$.fragment,yr),yr.forEach(t),wr.forEach(t),Yt=l(ot),fs=r(ot,"SPAN",{});var $r=o(fs);qt=u($r,"Latent Audio Diffusion"),$r.forEach(t),ot.forEach(t),Rs=l(e),m(be.$$.fragment,e),Bs=l(e),U=r(e,"H3",{class:!0});var nt=o(U);Q=r(nt,"A",{id:!0,class:!0,href:!0});var Mr=o(Q);us=r(Mr,"SPAN",{});var Er=o(us);m(we.$$.fragment,Er),Er.forEach(t),Mr.forEach(t),Ht=l(nt),cs=r(nt,"SPAN",{});var Dr=o(cs);Kt=u(Dr,"Audio Diffusion with DDIM (faster)"),Dr.forEach(t),nt.forEach(t),Ls=l(e),m(ye.$$.fragment,e),Cs=l(e),G=r(e,"H3",{class:!0});var at=o(G);z=r(at,"A",{id:!0,class:!0,href:!0});var Ar=o(z);ms=r(Ar,"SPAN",{});var kr=o(ms);m($e.$$.fragment,kr),kr.forEach(t),Ar.forEach(t),Ot=l(at),hs=r(at,"SPAN",{});var xr=o(hs);ei=u(xr,"Variations, in-painting, out-painting etc."),xr.forEach(t),at.forEach(t),Qs=l(e),m(Me.$$.fragment,e),zs=l(e),W=r(e,"H2",{class:!0});var lt=o(W);F=r(lt,"A",{id:!0,class:!0,href:!0});var Tr=o(F);gs=r(Tr,"SPAN",{});var Pr=o(gs);m(Ee.$$.fragment,Pr),Pr.forEach(t),Tr.forEach(t),si=l(lt),_s=r(lt,"SPAN",{});var Jr=o(_s);ti=u(Jr,"AudioDiffusionPipeline"),Jr.forEach(t),lt.forEach(t),Fs=l(e),w=r(e,"DIV",{class:!0});var M=o(w);m(De.$$.fragment,M),ii=l(M),Ae=r(M,"P",{});var dt=o(Ae);ri=u(dt,"This model inherits from "),Le=r(dt,"A",{href:!0});var jr=o(Le);oi=u(jr,"DiffusionPipeline"),jr.forEach(t),ni=u(dt,`. Check the superclass documentation for the generic methods the
library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)`),dt.forEach(t),ai=l(M),Y=r(M,"DIV",{class:!0});var pt=o(Y);m(ke.$$.fragment,pt),li=l(pt),vs=r(pt,"P",{});var Ir=o(vs);di=u(Ir,"Generate random mel spectrogram from audio input and convert to audio."),Ir.forEach(t),pt.forEach(t),pi=l(M),q=r(M,"DIV",{class:!0});var ft=o(q);m(xe.$$.fragment,ft),fi=l(ft),bs=r(ft,"P",{});var Ur=o(bs);ui=u(Ur,"Reverse step process: recover noisy image from generated image."),Ur.forEach(t),ft.forEach(t),ci=l(M),H=r(M,"DIV",{class:!0});var ut=o(H);m(Te.$$.fragment,ut),mi=l(ut),ws=r(ut,"P",{});var Gr=o(ws);hi=u(Gr,"Returns default number of steps recommended for inference"),Gr.forEach(t),ut.forEach(t),gi=l(M),K=r(M,"DIV",{class:!0});var ct=o(K);m(Pe.$$.fragment,ct),_i=l(ct),ys=r(ct,"P",{});var Wr=o(ys);vi=u(Wr,"Spherical Linear intERPolation"),Wr.forEach(t),ct.forEach(t),M.forEach(t),Ys=l(e),Z=r(e,"H2",{class:!0});var mt=o(Z);O=r(mt,"A",{id:!0,class:!0,href:!0});var Zr=o(O);$s=r(Zr,"SPAN",{});var Nr=o($s);m(Je.$$.fragment,Nr),Nr.forEach(t),Zr.forEach(t),bi=l(mt),Ms=r(mt,"SPAN",{});var Sr=o(Ms);wi=u(Sr,"Mel"),Sr.forEach(t),mt.forEach(t),qs=l(e),b=r(e,"DIV",{class:!0});var y=o(b);m(je.$$.fragment,y),yi=l(y),ee=r(y,"DIV",{class:!0});var ht=o(ee);m(Ie.$$.fragment,ht),$i=l(ht),Es=r(ht,"P",{});var Xr=o(Es);Mi=u(Xr,"Convert slice of audio to spectrogram."),Xr.forEach(t),ht.forEach(t),Ei=l(y),se=r(y,"DIV",{class:!0});var gt=o(se);m(Ue.$$.fragment,gt),Di=l(gt),Ds=r(gt,"P",{});var Vr=o(Ds);Ai=u(Vr,"Get slice of audio."),Vr.forEach(t),gt.forEach(t),ki=l(y),te=r(y,"DIV",{class:!0});var _t=o(te);m(Ge.$$.fragment,_t),xi=l(_t),As=r(_t,"P",{});var Rr=o(As);Ti=u(Rr,"Get number of slices in audio."),Rr.forEach(t),_t.forEach(t),Pi=l(y),ie=r(y,"DIV",{class:!0});var vt=o(ie);m(We.$$.fragment,vt),Ji=l(vt),ks=r(vt,"P",{});var Br=o(ks);ji=u(Br,"Get sample rate:"),Br.forEach(t),vt.forEach(t),Ii=l(y),re=r(y,"DIV",{class:!0});var bt=o(re);m(Ze.$$.fragment,bt),Ui=l(bt),xs=r(bt,"P",{});var Lr=o(xs);Gi=u(Lr,"Converts spectrogram to audio."),Lr.forEach(t),bt.forEach(t),Wi=l(y),oe=r(y,"DIV",{class:!0});var wt=o(oe);m(Ne.$$.fragment,wt),Zi=l(wt),Ts=r(wt,"P",{});var Cr=o(Ts);Ni=u(Cr,"Load audio."),Cr.forEach(t),wt.forEach(t),Si=l(y),ne=r(y,"DIV",{class:!0});var yt=o(ne);m(Se.$$.fragment,yt),Xi=l(yt),Ps=r(yt,"P",{});var Qr=o(Ps);Vi=u(Qr,"Set resolution."),Qr.forEach(t),yt.forEach(t),y.forEach(t),this.h()},h(){n(D,"name","hf:doc:metadata"),n(D,"content",JSON.stringify(so)),n(N,"id","audio-diffusion"),n(N,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(N,"href","#audio-diffusion"),n(A,"class","relative group"),n(S,"id","overview"),n(S,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(S,"href","#overview"),n(k,"class","relative group"),n(pe,"href","https://github.com/teticio/audio-diffusion"),n(pe,"rel","nofollow"),n(fe,"href","https://github.com/teticio/audio-diffusion"),n(fe,"rel","nofollow"),n(V,"id","available-pipelines"),n(V,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(V,"href","#available-pipelines"),n(x,"class","relative group"),n(Ve,"align","center"),n(ce,"href","https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/audio_diffusion/pipeline_audio_diffusion.py"),n(ce,"rel","nofollow"),Hr(Be.src,Li="https://colab.research.google.com/assets/colab-badge.svg")||n(Be,"src",Li),n(Be,"alt","Open In Colab"),n(me,"href","https://colab.research.google.com/github/teticio/audio-diffusion/blob/master/notebooks/audio_diffusion_pipeline.ipynb"),n(me,"rel","nofollow"),n(Re,"align","center"),n(B,"id","examples"),n(B,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(B,"href","#examples"),n(J,"class","relative group"),n(L,"id","audio-diffusion"),n(L,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(L,"href","#audio-diffusion"),n(j,"class","relative group"),n(C,"id","latent-audio-diffusion"),n(C,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(C,"href","#latent-audio-diffusion"),n(I,"class","relative group"),n(Q,"id","audio-diffusion-with-ddim-faster"),n(Q,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(Q,"href","#audio-diffusion-with-ddim-faster"),n(U,"class","relative group"),n(z,"id","variations-inpainting-outpainting-etc"),n(z,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(z,"href","#variations-inpainting-outpainting-etc"),n(G,"class","relative group"),n(F,"id","diffusers.AudioDiffusionPipeline"),n(F,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(F,"href","#diffusers.AudioDiffusionPipeline"),n(W,"class","relative group"),n(Le,"href","/docs/diffusers/v0.18.2/en/api/diffusion_pipeline#diffusers.DiffusionPipeline"),n(Y,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(q,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(H,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(K,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(w,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(O,"id","diffusers.Mel"),n(O,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),n(O,"href","#diffusers.Mel"),n(Z,"class","relative group"),n(ee,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(se,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(te,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(ie,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(re,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(oe,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(ne,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),n(b,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8")},m(e,d){s(document.head,D),p(e,Js,d),p(e,A,d),s(A,N),s(N,ze),h(ae,ze,null),s(A,Mt),s(A,Fe),s(Fe,Et),p(e,js,d),p(e,k,d),s(k,S),s(S,Ye),h(le,Ye,null),s(k,Dt),s(k,qe),s(qe,At),p(e,Is,d),p(e,de,d),s(de,pe),s(pe,kt),s(de,xt),p(e,Us,d),p(e,Xe,d),s(Xe,Tt),p(e,Gs,d),p(e,X,d),s(X,Pt),s(X,fe),s(fe,Jt),s(X,jt),p(e,Ws,d),p(e,x,d),s(x,V),s(V,He),h(ue,He,null),s(x,It),s(x,Ke),s(Ke,Ut),p(e,Zs,d),p(e,R,d),s(R,Oe),s(Oe,T),s(T,es),s(es,Gt),s(T,Wt),s(T,ss),s(ss,Zt),s(T,Nt),s(T,Ve),s(Ve,St),s(R,Xt),s(R,ts),s(ts,P),s(P,is),s(is,ce),s(ce,Vt),s(P,Rt),s(P,rs),s(rs,os),s(os,Bt),s(P,Lt),s(P,Re),s(Re,me),s(me,Be),p(e,Ns,d),p(e,J,d),s(J,B),s(B,ns),h(he,ns,null),s(J,Ct),s(J,as),s(as,Qt),p(e,Ss,d),p(e,j,d),s(j,L),s(L,ls),h(ge,ls,null),s(j,zt),s(j,ds),s(ds,Ft),p(e,Xs,d),h(_e,e,d),p(e,Vs,d),p(e,I,d),s(I,C),s(C,ps),h(ve,ps,null),s(I,Yt),s(I,fs),s(fs,qt),p(e,Rs,d),h(be,e,d),p(e,Bs,d),p(e,U,d),s(U,Q),s(Q,us),h(we,us,null),s(U,Ht),s(U,cs),s(cs,Kt),p(e,Ls,d),h(ye,e,d),p(e,Cs,d),p(e,G,d),s(G,z),s(z,ms),h($e,ms,null),s(G,Ot),s(G,hs),s(hs,ei),p(e,Qs,d),h(Me,e,d),p(e,zs,d),p(e,W,d),s(W,F),s(F,gs),h(Ee,gs,null),s(W,si),s(W,_s),s(_s,ti),p(e,Fs,d),p(e,w,d),h(De,w,null),s(w,ii),s(w,Ae),s(Ae,ri),s(Ae,Le),s(Le,oi),s(Ae,ni),s(w,ai),s(w,Y),h(ke,Y,null),s(Y,li),s(Y,vs),s(vs,di),s(w,pi),s(w,q),h(xe,q,null),s(q,fi),s(q,bs),s(bs,ui),s(w,ci),s(w,H),h(Te,H,null),s(H,mi),s(H,ws),s(ws,hi),s(w,gi),s(w,K),h(Pe,K,null),s(K,_i),s(K,ys),s(ys,vi),p(e,Ys,d),p(e,Z,d),s(Z,O),s(O,$s),h(Je,$s,null),s(Z,bi),s(Z,Ms),s(Ms,wi),p(e,qs,d),p(e,b,d),h(je,b,null),s(b,yi),s(b,ee),h(Ie,ee,null),s(ee,$i),s(ee,Es),s(Es,Mi),s(b,Ei),s(b,se),h(Ue,se,null),s(se,Di),s(se,Ds),s(Ds,Ai),s(b,ki),s(b,te),h(Ge,te,null),s(te,xi),s(te,As),s(As,Ti),s(b,Pi),s(b,ie),h(We,ie,null),s(ie,Ji),s(ie,ks),s(ks,ji),s(b,Ii),s(b,re),h(Ze,re,null),s(re,Ui),s(re,xs),s(xs,Gi),s(b,Wi),s(b,oe),h(Ne,oe,null),s(oe,Zi),s(oe,Ts),s(Ts,Ni),s(b,Si),s(b,ne),h(Se,ne,null),s(ne,Xi),s(ne,Ps),s(Ps,Vi),Hs=!0},p:Kr,i(e){Hs||(g(ae.$$.fragment,e),g(le.$$.fragment,e),g(ue.$$.fragment,e),g(he.$$.fragment,e),g(ge.$$.fragment,e),g(_e.$$.fragment,e),g(ve.$$.fragment,e),g(be.$$.fragment,e),g(we.$$.fragment,e),g(ye.$$.fragment,e),g($e.$$.fragment,e),g(Me.$$.fragment,e),g(Ee.$$.fragment,e),g(De.$$.fragment,e),g(ke.$$.fragment,e),g(xe.$$.fragment,e),g(Te.$$.fragment,e),g(Pe.$$.fragment,e),g(Je.$$.fragment,e),g(je.$$.fragment,e),g(Ie.$$.fragment,e),g(Ue.$$.fragment,e),g(Ge.$$.fragment,e),g(We.$$.fragment,e),g(Ze.$$.fragment,e),g(Ne.$$.fragment,e),g(Se.$$.fragment,e),Hs=!0)},o(e){_(ae.$$.fragment,e),_(le.$$.fragment,e),_(ue.$$.fragment,e),_(he.$$.fragment,e),_(ge.$$.fragment,e),_(_e.$$.fragment,e),_(ve.$$.fragment,e),_(be.$$.fragment,e),_(we.$$.fragment,e),_(ye.$$.fragment,e),_($e.$$.fragment,e),_(Me.$$.fragment,e),_(Ee.$$.fragment,e),_(De.$$.fragment,e),_(ke.$$.fragment,e),_(xe.$$.fragment,e),_(Te.$$.fragment,e),_(Pe.$$.fragment,e),_(Je.$$.fragment,e),_(je.$$.fragment,e),_(Ie.$$.fragment,e),_(Ue.$$.fragment,e),_(Ge.$$.fragment,e),_(We.$$.fragment,e),_(Ze.$$.fragment,e),_(Ne.$$.fragment,e),_(Se.$$.fragment,e),Hs=!1},d(e){t(D),e&&t(Js),e&&t(A),v(ae),e&&t(js),e&&t(k),v(le),e&&t(Is),e&&t(de),e&&t(Us),e&&t(Xe),e&&t(Gs),e&&t(X),e&&t(Ws),e&&t(x),v(ue),e&&t(Zs),e&&t(R),e&&t(Ns),e&&t(J),v(he),e&&t(Ss),e&&t(j),v(ge),e&&t(Xs),v(_e,e),e&&t(Vs),e&&t(I),v(ve),e&&t(Rs),v(be,e),e&&t(Bs),e&&t(U),v(we),e&&t(Ls),v(ye,e),e&&t(Cs),e&&t(G),v($e),e&&t(Qs),v(Me,e),e&&t(zs),e&&t(W),v(Ee),e&&t(Fs),e&&t(w),v(De),v(ke),v(xe),v(Te),v(Pe),e&&t(Ys),e&&t(Z),v(Je),e&&t(qs),e&&t(b),v(je),v(Ie),v(Ue),v(Ge),v(We),v(Ze),v(Ne),v(Se)}}}const so={local:"audio-diffusion",sections:[{local:"overview",title:"Overview"},{local:"available-pipelines",title:"Available Pipelines:"},{local:"examples",sections:[{local:"audio-diffusion",title:"Audio Diffusion"},{local:"latent-audio-diffusion",title:"Latent Audio Diffusion"},{local:"audio-diffusion-with-ddim-faster",title:"Audio Diffusion with DDIM (faster)"},{local:"variations-inpainting-outpainting-etc",title:"Variations, in-painting, out-painting etc."}],title:"Examples:"},{local:"diffusers.AudioDiffusionPipeline",title:"AudioDiffusionPipeline"},{local:"diffusers.Mel",title:"Mel"}],title:"Audio Diffusion"};function to(Bi){return Or(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class ao extends zr{constructor(D){super();Fr(this,D,to,eo,Yr,{})}}export{ao as default,so as metadata};
