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import{s as $e,n as ve,o as ye}from"../chunks/scheduler.8c3d61f6.js";import{S as ze,i as Ne,g as i,s as a,r as l,A as xe,h as s,f as o,c as r,j as O,u as f,x as F,k as H,y as d,a as n,v as u,d as c,t as p,w as g}from"../chunks/index.da70eac4.js";import{D as ie}from"../chunks/Docstring.ee4b6913.js";import{H as V,E as Ae}from"../chunks/EditOnGithub.1e64e623.js";function Le(ue){let _,q,I,j,v,R,y,ce="Customized normalization layers for supporting various models in 🤗 Diffusers.",U,z,B,h,N,se,P,pe="Norm layer modified to incorporate timestep embeddings.",J,x,K,b,A,me,S,ge="Norm layer adaptive layer norm zero (adaLN-Zero).",Q,L,W,m,w,de,D,_e="Norm layer adaptive layer norm single (adaLN-single).",le,E,he='As proposed in PixArt-Alpha (see: <a href="https://arxiv.org/abs/2310.00426" rel="nofollow">https://arxiv.org/abs/2310.00426</a>; Section 2.3).',X,T,Y,$,C,fe,Z,be="GroupNorm layer modified to incorporate timestep embeddings.",ee,G,te,M,oe;return v=new V({props:{title:"Normalization layers",local:"normalization-layers",headingTag:"h1"}}),z=new V({props:{title:"AdaLayerNorm",local:"diffusers.models.normalization.AdaLayerNorm",headingTag:"h2"}}),N=new ie({props:{name:"class diffusers.models.normalization.AdaLayerNorm",anchor:"diffusers.models.normalization.AdaLayerNorm",parameters:[{name:"embedding_dim",val:": int"},{name:"num_embeddings",val:": Optional = None"},{name:"output_dim",val:": Optional = 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>) &#x2014; 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>) &#x2014; 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>) &#x2014;",name:"output_dim"},{anchor:"diffusers.models.normalization.AdaLayerNorm.norm_elementwise_affine",description:"<strong>norm_elementwise_affine</strong> (<code>bool</code>, defaults to `False) &#x2014;",name:"norm_elementwise_affine"},{anchor:"diffusers.models.normalization.AdaLayerNorm.norm_eps",description:"<strong>norm_eps</strong> (<code>bool</code>, defaults to <code>False</code>) &#x2014;",name:"norm_eps"},{anchor:"diffusers.models.normalization.AdaLayerNorm.chunk_dim",description:"<strong>chunk_dim</strong> (<code>int</code>, defaults to <code>0</code>) &#x2014;",name:"chunk_dim"}],source:"https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/normalization.py#L31"}}),x=new V({props:{title:"AdaLayerNormZero",local:"diffusers.models.normalization.AdaLayerNormZero",headingTag:"h2"}}),A=new ie({props:{name:"class diffusers.models.normalization.AdaLayerNormZero",anchor:"diffusers.models.normalization.AdaLayerNormZero",parameters:[{name:"embedding_dim",val:": int"},{name:"num_embeddings",val:": Optional = 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>) &#x2014; The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaLayerNormZero.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>) &#x2014; The size of the embeddings dictionary.",name:"num_embeddings"}],source:"https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/normalization.py#L100"}}),L=new V({props:{title:"AdaLayerNormSingle",local:"diffusers.models.normalization.AdaLayerNormSingle",headingTag:"h2"}}),w=new ie({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>) &#x2014; 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>) &#x2014; To use additional conditions for normalization or not.",name:"use_additional_conditions"}],source:"https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/normalization.py#L206"}}),T=new V({props:{title:"AdaGroupNorm",local:"diffusers.models.normalization.AdaGroupNorm",headingTag:"h2"}}),C=new ie({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:": Optional = None"},{name:"eps",val:": float = 1e-05"}],parametersDescription:[{anchor:"diffusers.models.normalization.AdaGroupNorm.embedding_dim",description:"<strong>embedding_dim</strong> (<code>int</code>) &#x2014; The size of each embedding vector.",name:"embedding_dim"},{anchor:"diffusers.models.normalization.AdaGroupNorm.num_embeddings",description:"<strong>num_embeddings</strong> (<code>int</code>) &#x2014; The size of the embeddings dictionary.",name:"num_embeddings"},{anchor:"diffusers.models.normalization.AdaGroupNorm.num_groups",description:"<strong>num_groups</strong> (<code>int</code>) &#x2014; 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