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	import{s as mr,n as dr,o as lr}from"../chunks/scheduler.8c3d61f6.js";import{S as fr,i as ur,g as u,s as t,r as a,A as gr,h as g,f as r,c as i,j as c,u as s,x as _,k as $,y as p,a as n,v as m,d,t as l,w as f}from"../chunks/index.da70eac4.js";import{D as h}from"../chunks/Docstring.567bc132.js";import{H as b,E as pr}from"../chunks/index.5d4ab994.js";function cr(ko){let y,Re,Me,Ve,D,Pe,R,Fo="Customized normalization layers for supporting various models in 🤗 Diffusers.",Ie,V,Ee,N,P,So,he,Oo="Norm layer modified to incorporate timestep embeddings.",Ge,I,Xe,z,E,Zo,_e,jo="Norm layer adaptive layer norm zero (adaLN-Zero).",qe,G,He,v,X,Mo,ve,Bo="Norm layer adaptive layer norm single (adaLN-single).",Do,ye,Uo='As proposed in PixArt-Alpha (see: <a href="https://arxiv.org/abs/2310.00426" rel="nofollow">https://arxiv.org/abs/2310.00426</a>; Section 2.3).',ke,q,Fe,L,H,Ro,Ne,Jo="GroupNorm layer modified to incorporate timestep embeddings.",Oe,k,je,x,F,Vo,ze,Ko="Adaptive normalization layer with a norm layer (layer_norm or rms_norm).",Be,O,Ue,A,j,Po,Le,Qo='RMS Norm as introduced in <a href="https://arxiv.org/abs/1910.07467" rel="nofollow">https://arxiv.org/abs/1910.07467</a> by Zhang et al.',Je,B,Ke,w,U,Io,xe,Wo='Global response normalization as introduced in ConvNeXt-v2 (<a href="https://arxiv.org/abs/2301.00808" rel="nofollow">https://arxiv.org/abs/2301.00808</a>).',Qe,J,We,K,Q,Ye,W,eo,C,Y,Eo,Ae,Yo="Norm layer adaptive layer norm zero (AdaLN-Zero).",oo,ee,ro,T,oe,Go,we,er="Norm layer adaptive layer norm zero (adaLN-Zero).",no,re,to,S,ne,Xo,Ce,or="Norm layer adaptive RMS normalization zero.",io,te,ao,ie,ae,so,se,mo,Z,me,qo,Te,rr="Norm layer adaptive layer norm zero (adaLN-Zero).",lo,de,fo,le,fe,uo,ue,go,M,ge,Ho,Se,nr="Adaptive RMS Norm used in Mochi.",po,pe,co,ce,$e,$o,be,bo,De,ho;return D=new b({props:{title:"Normalization layers",local:"normalization-layers",headingTag:"h1"}}),V=new b({props:{title:"AdaLayerNorm",local:"diffusers.models.normalization.AdaLayerNorm",headingTag:"h2"}}),P=new h({props:{name:"class diffusers.models.normalization.AdaLayerNorm",anchor:"diffusers.models.normalization.AdaLayerNorm",parameters:[{name:"embedding_dim",val:": int"},{name:"num_embeddings",val:": typing.Optional[int] = None"},{name:"output_dim",val:": typing.Optional[int] = None"},{name:"norm_elementwise_affine",val:": bool = False"},{name:"norm_eps",val:": float = 1e-05"},{name:"chunk_dim",val:": int = 0"}],parametersDescription:[{anchor:"diffusers.models.normalization.AdaLayerNorm.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaLayerNorm.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>, <em>optional</em>) — The size of the embeddings dictionary.",name:"num_embeddings"},{anchor:"diffusers.models.normalization.AdaLayerNorm.output_dim",description:"<strong>output_dim</strong> (<code>int</code>, <em>optional</em>) —",name:"output_dim"},{anchor:"diffusers.models.normalization.AdaLayerNorm.norm_elementwise_affine",description:"<strong>norm_elementwise_affine</strong> (<code>bool</code>, defaults to `False) —",name:"norm_elementwise_affine"},{anchor:"diffusers.models.normalization.AdaLayerNorm.norm_eps",description:"<strong>norm_eps</strong> (<code>bool</code>, defaults to <code>False</code>) —",name:"norm_eps"},{anchor:"diffusers.models.normalization.AdaLayerNorm.chunk_dim",description:"<strong>chunk_dim</strong> (<code>int</code>, defaults to <code>0</code>) —",name:"chunk_dim"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L28"}}),I=new b({props:{title:"AdaLayerNormZero",local:"diffusers.models.normalization.AdaLayerNormZero",headingTag:"h2"}}),E=new h({props:{name:"class diffusers.models.normalization.AdaLayerNormZero",anchor:"diffusers.models.normalization.AdaLayerNormZero",parameters:[{name:"embedding_dim",val:": int"},{name:"num_embeddings",val:": typing.Optional[int] = None"},{name:"norm_type",val:" = 'layer_norm'"},{name:"bias",val:" = True"}],parametersDescription:[{anchor:"diffusers.models.normalization.AdaLayerNormZero.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaLayerNormZero.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>) — The size of the embeddings dictionary.",name:"num_embeddings"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L131"}}),G=new b({props:{title:"AdaLayerNormSingle",local:"diffusers.models.normalization.AdaLayerNormSingle",headingTag:"h2"}}),X=new h({props:{name:"class diffusers.models.normalization.AdaLayerNormSingle",anchor:"diffusers.models.normalization.AdaLayerNormSingle",parameters:[{name:"embedding_dim",val:": int"},{name:"use_additional_conditions",val:": bool = False"}],parametersDescription:[{anchor:"diffusers.models.normalization.AdaLayerNormSingle.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaLayerNormSingle.use_additional_conditions",description:"<strong>use_additional_conditions</strong> (<code>bool</code>) — To use additional conditions for normalization or not.",name:"use_additional_conditions"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L236"}}),q=new b({props:{title:"AdaGroupNorm",local:"diffusers.models.normalization.AdaGroupNorm",headingTag:"h2"}}),H=new h({props:{name:"class diffusers.models.normalization.AdaGroupNorm",anchor:"diffusers.models.normalization.AdaGroupNorm",parameters:[{name:"embedding_dim",val:": int"},{name:"out_dim",val:": int"},{name:"num_groups",val:": int"},{name:"act_fn",val:": typing.Optional[str] = None"},{name:"eps",val:": float = 1e-05"}],parametersDescription:[{anchor:"diffusers.models.normalization.AdaGroupNorm.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaGroupNorm.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>) — The size of the embeddings dictionary.",name:"num_embeddings"},{anchor:"diffusers.models.normalization.AdaGroupNorm.num_groups",description:"<strong>num_groups</strong> (<code>int</code>) — The number of groups to separate the channels into.",name:"num_groups"},{anchor:"diffusers.models.normalization.AdaGroupNorm.act_fn",description:"<strong>act_fn</strong> (<code>str</code>, <em>optional</em>, defaults to <code>None</code>) — The activation function to use.",name:"act_fn"},{anchor:"diffusers.models.normalization.AdaGroupNorm.eps",description:"<strong>eps</strong> (<code>float</code>, <em>optional</em>, defaults to <code>1e-5</code>) — The epsilon value to use for numerical stability.",name:"eps"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L270"}}),k=new b({props:{title:"AdaLayerNormContinuous",local:"diffusers.models.normalization.AdaLayerNormContinuous",headingTag:"h2"}}),F=new h({props:{name:"class diffusers.models.normalization.AdaLayerNormContinuous",anchor:"diffusers.models.normalization.AdaLayerNormContinuous",parameters:[{name:"embedding_dim",val:": int"},{name:"conditioning_embedding_dim",val:": int"},{name:"elementwise_affine",val:" = True"},{name:"eps",val:" = 1e-05"},{name:"bias",val:" = True"},{name:"norm_type",val:" = 'layer_norm'"}],parametersDescription:[{anchor:"diffusers.models.normalization.AdaLayerNormContinuous.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — Embedding dimension to use during projection.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaLayerNormContinuous.conditioning_embedding_dim",description:"<strong>conditioning_embedding_dim</strong> (<code>int</code>) — Dimension of the input condition.",name:"conditioning_embedding_dim"},{anchor:"diffusers.models.normalization.AdaLayerNormContinuous.elementwise_affine",description:`<strong>elementwise_affine</strong> (<code>bool</code>, defaults to <code>True</code>) —
	Boolean flag to denote if affine transformation should be applied.`,name:"elementwise_affine"},{anchor:"diffusers.models.normalization.AdaLayerNormContinuous.eps",description:"<strong>eps</strong> (<code>float</code>, defaults to 1e-5) — Epsilon factor.",name:"eps"},{anchor:"diffusers.models.normalization.AdaLayerNormContinuous.bias",description:"<strong>bias</strong> (<code>bias</code>, defaults to <code>True</code>) — Boolean flag to denote if bias should be use.",name:"bias"},{anchor:"diffusers.models.normalization.AdaLayerNormContinuous.norm_type",description:`<strong>norm_type</strong> (<code>str</code>, defaults to <code>"layer_norm"</code>) —
	Normalization layer to use. Values supported: “layer_norm”, “rms_norm”.`,name:"norm_type"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L308"}}),O=new b({props:{title:"RMSNorm",local:"diffusers.models.normalization.RMSNorm",headingTag:"h2"}}),j=new h({props:{name:"class diffusers.models.normalization.RMSNorm",anchor:"diffusers.models.normalization.RMSNorm",parameters:[{name:"dim",val:""},{name:"eps",val:": float"},{name:"elementwise_affine",val:": bool = True"},{name:"bias",val:": bool = False"}],parametersDescription:[{anchor:"diffusers.models.normalization.RMSNorm.dim",description:"<strong>dim</strong> (<code>int</code>) — Number of dimensions to use for <code>weights</code>. Only effective when <code>elementwise_affine</code> is True.",name:"dim"},{anchor:"diffusers.models.normalization.RMSNorm.eps",description:"<strong>eps</strong> (<code>float</code>) — Small value to use when calculating the reciprocal of the square-root.",name:"eps"},{anchor:"diffusers.models.normalization.RMSNorm.elementwise_affine",description:`<strong>elementwise_affine</strong> (<code>bool</code>, defaults to <code>True</code>) —
	Boolean flag to denote if affine transformation should be applied.`,name:"elementwise_affine"},{anchor:"diffusers.models.normalization.RMSNorm.bias",description:"<strong>bias</strong> (<code>bool</code>, defaults to False) — If also training the <code>bias</code> param.",name:"bias"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L511"}}),B=new b({props:{title:"GlobalResponseNorm",local:"diffusers.models.normalization.GlobalResponseNorm",headingTag:"h2"}}),U=new h({props:{name:"class diffusers.models.normalization.GlobalResponseNorm",anchor:"diffusers.models.normalization.GlobalResponseNorm",parameters:[{name:"dim",val:""}],parametersDescription:[{anchor:"diffusers.models.normalization.GlobalResponseNorm.dim",description:"<strong>dim</strong> (<code>int</code>) — Number of dimensions to use for the <code>gamma</code> and <code>beta</code>.",name:"dim"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L601"}}),J=new b({props:{title:"LuminaLayerNormContinuous",local:"diffusers.models.normalization.LuminaLayerNormContinuous",headingTag:"h2"}}),Q=new h({props:{name:"class diffusers.models.normalization.LuminaLayerNormContinuous",anchor:"diffusers.models.normalization.LuminaLayerNormContinuous",parameters:[{name:"embedding_dim",val:": int"},{name:"conditioning_embedding_dim",val:": int"},{name:"elementwise_affine",val:" = True"},{name:"eps",val:" = 1e-05"},{name:"bias",val:" = True"},{name:"norm_type",val:" = 'layer_norm'"},{name:"out_dim",val:": typing.Optional[int] = None"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L355"}}),W=new b({props:{title:"SD35AdaLayerNormZeroX",local:"diffusers.models.normalization.SD35AdaLayerNormZeroX",headingTag:"h2"}}),Y=new h({props:{name:"class diffusers.models.normalization.SD35AdaLayerNormZeroX",anchor:"diffusers.models.normalization.SD35AdaLayerNormZeroX",parameters:[{name:"embedding_dim",val:": int"},{name:"norm_type",val:": str = 'layer_norm'"},{name:"bias",val:": bool = True"}],parametersDescription:[{anchor:"diffusers.models.normalization.SD35AdaLayerNormZeroX.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.SD35AdaLayerNormZeroX.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>) — The size of the embeddings dictionary.",name:"num_embeddings"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L97"}}),ee=new b({props:{title:"AdaLayerNormZeroSingle",local:"diffusers.models.normalization.AdaLayerNormZeroSingle",headingTag:"h2"}}),oe=new h({props:{name:"class diffusers.models.normalization.AdaLayerNormZeroSingle",anchor:"diffusers.models.normalization.AdaLayerNormZeroSingle",parameters:[{name:"embedding_dim",val:": int"},{name:"norm_type",val:" = 'layer_norm'"},{name:"bias",val:" = True"}],parametersDescription:[{anchor:"diffusers.models.normalization.AdaLayerNormZeroSingle.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaLayerNormZeroSingle.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>) — The size of the embeddings dictionary.",name:"num_embeddings"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L174"}}),re=new b({props:{title:"LuminaRMSNormZero",local:"diffusers.models.normalization.LuminaRMSNormZero",headingTag:"h2"}}),ne=new h({props:{name:"class diffusers.models.normalization.LuminaRMSNormZero",anchor:"diffusers.models.normalization.LuminaRMSNormZero",parameters:[{name:"embedding_dim",val:": int"},{name:"norm_eps",val:": float"},{name:"norm_elementwise_affine",val:": bool"}],parametersDescription:[{anchor:"diffusers.models.normalization.LuminaRMSNormZero.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L206"}}),te=new b({props:{title:"LpNorm",local:"diffusers.models.normalization.LpNorm",headingTag:"h2"}}),ae=new h({props:{name:"class diffusers.models.normalization.LpNorm",anchor:"diffusers.models.normalization.LpNorm",parameters:[{name:"p",val:": int = 2"},{name:"dim",val:": int = -1"},{name:"eps",val:": float = 1e-12"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L621"}}),se=new b({props:{title:"CogView3PlusAdaLayerNormZeroTextImage",local:"diffusers.models.normalization.CogView3PlusAdaLayerNormZeroTextImage",headingTag:"h2"}}),me=new h({props:{name:"class diffusers.models.normalization.CogView3PlusAdaLayerNormZeroTextImage",anchor:"diffusers.models.normalization.CogView3PlusAdaLayerNormZeroTextImage",parameters:[{name:"embedding_dim",val:": int"},{name:"dim",val:": int"}],parametersDescription:[{anchor:"diffusers.models.normalization.CogView3PlusAdaLayerNormZeroTextImage.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) — The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.CogView3PlusAdaLayerNormZeroTextImage.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>) — The size of the embeddings dictionary.",name:"num_embeddings"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L404"}}),de=new b({props:{title:"CogVideoXLayerNormZero",local:"diffusers.models.normalization.CogVideoXLayerNormZero",headingTag:"h2"}}),fe=new h({props:{name:"class diffusers.models.normalization.CogVideoXLayerNormZero",anchor:"diffusers.models.normalization.CogVideoXLayerNormZero",parameters:[{name:"conditioning_dim",val:": int"},{name:"embedding_dim",val:": int"},{name:"elementwise_affine",val:": bool = True"},{name:"eps",val:": float = 1e-05"},{name:"bias",val:": bool = True"}],source:"https://github.com/huggingface/diffusers/blob/vr_11234/src/diffusers/models/normalization.py#L449"}}),ue=new b({props:{title:"MochiRMSNormZero",local:"diffusers.models.transformers.transformer_mochi.MochiRMSNormZero",headingTag:"h2"}}),ge=new h({props:{name:"class diffusers.models.transformers.transformer_mochi.MochiRMSNormZero",anchor:"diffusers.models.transformers.transformer_mochi.MochiRMSNormZero",parameters:[{name:"embedding_dim",val:": int"},{name:"hidden_dim",val:": int"},{name:"eps",val:": float = 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