diffusers/pr_10101/en/_app/immutable/nodes/17.dcb2bae0.js

import{s as Ae,o as he,n as pe}from"../chunks/scheduler.8c3d61f6.js";import{S as Pe,i as ge,g as f,s as i,r as h,A as $e,h as c,f as o,c as a,j as E,u as P,x as I,k as R,y as n,a as m,v as g,d as $,t as F,w as b}from"../chunks/index.da70eac4.js";import{T as ue}from"../chunks/Tip.1d9b8c37.js";import{D as Y}from"../chunks/Docstring.6b390b9a.js";import{H as _e,E as Fe}from"../chunks/EditOnGithub.1e64e623.js";function be(z){let s,u="This API is 🧪 experimental.";return{c(){s=f("p"),s.textContent=u},l(r){s=c(r,"P",{"data-svelte-h":!0}),I(s)!=="svelte-89q1io"&&(s.textContent=u)},m(r,w){m(r,s,w)},p:pe,d(r){r&&o(s)}}}function we(z){let s,u="This API is 🧪 experimental.";return{c(){s=f("p"),s.textContent=u},l(r){s=c(r,"P",{"data-svelte-h":!0}),I(s)!=="svelte-89q1io"&&(s.textContent=u)},m(r,w){m(r,s,w)},p:pe,d(r){r&&o(s)}}}function ve(z){let s,u,r,w,y,q,D,de='A Transformer model for image-like data from <a href="https://blog.fal.ai/auraflow/" rel="nofollow">AuraFlow</a>.',J,M,N,d,C,Z,H,fe='A 2D Transformer model as introduced in AuraFlow (<a href="https://blog.fal.ai/auraflow/" rel="nofollow">https://blog.fal.ai/auraflow/</a>).',ee,_,V,se,S,ce=`Enables fused QKV projections. For self-attention modules, all projection matrices (i.e., query, key, value)
are fused. For cross-attention modules, key and value projection matrices are fused.`,te,v,oe,x,G,re,X,le="Sets the attention processor to use to compute attention.",ne,p,L,ie,k,me="Disables the fused QKV projection if enabled.",ae,T,Q,j,O,U,B;return y=new _e({props:{title:"AuraFlowTransformer2DModel",local:"auraflowtransformer2dmodel",headingTag:"h1"}}),M=new _e({props:{title:"AuraFlowTransformer2DModel",local:"diffusers.AuraFlowTransformer2DModel",headingTag:"h2"}}),C=new Y({props:{name:"class diffusers.AuraFlowTransformer2DModel",anchor:"diffusers.AuraFlowTransformer2DModel",parameters:[{name:"sample_size",val:": int = 64"},{name:"patch_size",val:": int = 2"},{name:"in_channels",val:": int = 4"},{name:"num_mmdit_layers",val:": int = 4"},{name:"num_single_dit_layers",val:": int = 32"},{name:"attention_head_dim",val:": int = 256"},{name:"num_attention_heads",val:": int = 12"},{name:"joint_attention_dim",val:": int = 2048"},{name:"caption_projection_dim",val:": int = 3072"},{name:"out_channels",val:": int = 4"},{name:"pos_embed_max_size",val:": int = 1024"}],parametersDescription:[{anchor:"diffusers.AuraFlowTransformer2DModel.sample_size",description:`<strong>sample_size</strong> (<code>int</code>) &#x2014; The width of the latent images. This is fixed during training since
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The number of layers of Transformer blocks to use. These blocks use concatenated image and text
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projecting the <code>encoder_hidden_states</code>.",name:"caption_projection_dim"},{anchor:"diffusers.AuraFlowTransformer2DModel.out_channels",description:"<strong>out_channels</strong> (<code>int</code>, defaults to 16) &#x2014; Number of output channels.",name:"out_channels"},{anchor:"diffusers.AuraFlowTransformer2DModel.pos_embed_max_size",description:"<strong>pos_embed_max_size</strong> (<code>int</code>, defaults to 4096) &#x2014; Maximum positions to embed from the image latents.",name:"pos_embed_max_size"}],source:"https://github.com/huggingface/diffusers/blob/vr_10101/src/diffusers/models/transformers/auraflow_transformer_2d.py#L256"}}),V=new Y({props:{name:"fuse_qkv_projections",anchor:"diffusers.AuraFlowTransformer2DModel.fuse_qkv_projections",parameters:[],source:"https://github.com/huggingface/diffusers/blob/vr_10101/src/diffusers/models/transformers/auraflow_transformer_2d.py#L406"}}),v=new ue({props:{warning:!0,$$slots:{default:[be]},$$scope:{ctx:z}}}),G=new Y({props:{name:"set_attn_processor",anchor:"diffusers.AuraFlowTransformer2DModel.set_attn_processor",parameters:[{name:"processor",val:": typing.Union[diffusers.models.attention_processor.AttnProcessor, diffusers.models.attention_processor.CustomDiffusionAttnProcessor, diffusers.models.attention_processor.AttnAddedKVProcessor, diffusers.models.attention_processor.AttnAddedKVProcessor2_0, diffusers.models.attention_processor.JointAttnProcessor2_0, diffusers.models.attention_processor.PAGJointAttnProcessor2_0, diffusers.models.attention_processor.PAGCFGJointAttnProcessor2_0, diffusers.models.attention_processor.FusedJointAttnProcessor2_0, diffusers.models.attention_processor.AllegroAttnProcessor2_0, diffusers.models.attention_processor.AuraFlowAttnProcessor2_0, diffusers.models.attention_processor.FusedAuraFlowAttnProcessor2_0, diffusers.models.attention_processor.FluxAttnProcessor2_0, diffusers.models.attention_processor.FluxAttnProcessor2_0_NPU, diffusers.models.attention_processor.FusedFluxAttnProcessor2_0, diffusers.models.attention_processor.FusedFluxAttnProcessor2_0_NPU, diffusers.models.attention_processor.CogVideoXAttnProcessor2_0, diffusers.models.attention_processor.FusedCogVideoXAttnProcessor2_0, diffusers.models.attention_processor.XFormersAttnAddedKVProcessor, diffusers.models.attention_processor.XFormersAttnProcessor, diffusers.models.attention_processor.AttnProcessorNPU, diffusers.models.attention_processor.AttnProcessor2_0, diffusers.models.attention_processor.MochiVaeAttnProcessor2_0, diffusers.models.attention_processor.StableAudioAttnProcessor2_0, diffusers.models.attention_processor.HunyuanAttnProcessor2_0, diffusers.models.attention_processor.FusedHunyuanAttnProcessor2_0, diffusers.models.attention_processor.PAGHunyuanAttnProcessor2_0, diffusers.models.attention_processor.PAGCFGHunyuanAttnProcessor2_0, diffusers.models.attention_processor.LuminaAttnProcessor2_0, diffusers.models.attention_processor.MochiAttnProcessor2_0, diffusers.models.attention_processor.FusedAttnProcessor2_0, diffusers.models.attention_processor.CustomDiffusionXFormersAttnProcessor, diffusers.models.attention_processor.CustomDiffusionAttnProcessor2_0, diffusers.models.attention_processor.SlicedAttnProcessor, diffusers.models.attention_processor.SlicedAttnAddedKVProcessor, diffusers.models.attention_processor.IPAdapterAttnProcessor, diffusers.models.attention_processor.IPAdapterAttnProcessor2_0, diffusers.models.attention_processor.IPAdapterXFormersAttnProcessor, diffusers.models.attention_processor.PAGIdentitySelfAttnProcessor2_0, diffusers.models.attention_processor.PAGCFGIdentitySelfAttnProcessor2_0, diffusers.models.attention_processor.LoRAAttnProcessor, diffusers.models.attention_processor.LoRAAttnProcessor2_0, diffusers.models.attention_processor.LoRAXFormersAttnProcessor, diffusers.models.attention_processor.LoRAAttnAddedKVProcessor, typing.Dict[str, typing.Union[diffusers.models.attention_processor.AttnProcessor, diffusers.models.attention_processor.CustomDiffusionAttnProcessor, diffusers.models.attention_processor.AttnAddedKVProcessor, diffusers.models.attention_processor.AttnAddedKVProcessor2_0, diffusers.models.attention_processor.JointAttnProcessor2_0, diffusers.models.attention_processor.PAGJointAttnProcessor2_0, diffusers.models.attention_processor.PAGCFGJointAttnProcessor2_0, diffusers.models.attention_processor.FusedJointAttnProcessor2_0, diffusers.models.attention_processor.AllegroAttnProcessor2_0, diffusers.models.attention_processor.AuraFlowAttnProcessor2_0, diffusers.models.attention_processor.FusedAuraFlowAttnProcessor2_0, diffusers.models.attention_processor.FluxAttnProcessor2_0, diffusers.models.attention_processor.FluxAttnProcessor2_0_NPU, diffusers.models.attention_processor.FusedFluxAttnProcessor2_0, diffusers.models.attention_processor.FusedFluxAttnProcessor2_0_NPU, 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The instantiated processor class or a dictionary of processor classes that will be set as the processor
for <strong>all</strong> <code>Attention</code> layers.</p>
<p>If <code>processor</code> is a dict, the key needs to define the path to the corresponding cross attention
processor. This is strongly recommended when setting trainable attention processors.`,name:"processor"}],source:"https://github.com/huggingface/diffusers/blob/vr_10101/src/diffusers/models/transformers/auraflow_transformer_2d.py#L371"}}),L=new Y({props:{name:"unfuse_qkv_projections",anchor:"diffusers.AuraFlowTransformer2DModel.unfuse_qkv_projections",parameters:[],source:"https://github.com/huggingface/diffusers/blob/vr_10101/src/diffusers/models/transformers/auraflow_transformer_2d.py#L432"}}),T=new ue({props:{warning:!0,$$slots:{default:[we]},$$scope:{ctx:z}}}),j=new Fe({props:{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/en/api/models/aura_flow_transformer2d.md"}}),{c(){s=f("meta"),u=i(),r=f("p"),w=i(),h(y.$$.fragment),q=i(),D=f("p"),D.innerHTML=de,J=i(),h(M.$$.fragment),N=i(),d=f("div"),h(C.$$.fragment),Z=i(),H=f("p"),H.innerHTML=fe,ee=i(),_=f("div"),h(V.$$.fragment),se=i(),S=f("p"),S.textContent=ce,te=i(),h(v.$$.fragment),oe=i(),x=f("div"),h(G.$$.fragment),re=i(),X=f("p"),X.textContent=le,ne=i(),p=f("div"),h(L.$$.fragment),ie=i(),k=f("p"),k.textContent=me,ae=i(),h(T.$$.fragment),Q=i(),h(j.$$.fragment),O=i(),U=f("p"),this.h()},l(e){const t=$e("svelte-u9bgzb",document.head);s=c(t,"META",{name:!0,content:!0}),t.forEach(o),u=a(e),r=c(e,"P",{}),E(r).forEach(o),w=a(e),P(y.$$.fragment,e),q=a(e),D=c(e,"P",{"data-svelte-h":!0}),I(D)!=="svelte-1cl4wve"&&(D.innerHTML=de),J=a(e),P(M.$$.fragment,e),N=a(e),d=c(e,"DIV",{class:!0});var l=E(d);P(C.$$.fragment,l),Z=a(l),H=c(l,"P",{"data-svelte-h":!0}),I(H)!=="svelte-xp13t2"&&(H.innerHTML=fe),ee=a(l),_=c(l,"DIV",{class:!0});var A=E(_);P(V.$$.fragment,A),se=a(A),S=c(A,"P",{"data-svelte-h":!0}),I(S)!=="svelte-1254b9i"&&(S.textContent=ce),te=a(A),P(v.$$.fragment,A),A.forEach(o),oe=a(l),x=c(l,"DIV",{class:!0});var W=E(x);P(G.$$.fragment,W),re=a(W),X=c(W,"P",{"data-svelte-h":!0}),I(X)!=="svelte-1o77hl2"&&(X.textContent=le),W.forEach(o),ne=a(l),p=c(l,"DIV",{class:!0});var K=E(p);P(L.$$.fragment,K),ie=a(K),k=c(K,"P",{"data-svelte-h":!0}),I(k)!=="svelte-1vhtc74"&&(k.textContent=me),ae=a(K),P(T.$$.fragment,K),K.forEach(o),l.forEach(o),Q=a(e),P(j.$$.fragment,e),O=a(e),U=c(e,"P",{}),E(U).forEach(o),this.h()},h(){R(s,"name","hf:doc:metadata"),R(s,"content",xe),R(_,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),R(x,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),R(p,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),R(d,"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,t){n(document.head,s),m(e,u,t),m(e,r,t),m(e,w,t),g(y,e,t),m(e,q,t),m(e,D,t),m(e,J,t),g(M,e,t),m(e,N,t),m(e,d,t),g(C,d,null),n(d,Z),n(d,H),n(d,ee),n(d,_),g(V,_,null),n(_,se),n(_,S),n(_,te),g(v,_,null),n(d,oe),n(d,x),g(G,x,null),n(x,re),n(x,X),n(d,ne),n(d,p),g(L,p,null),n(p,ie),n(p,k),n(p,ae),g(T,p,null),m(e,Q,t),g(j,e,t),m(e,O,t),m(e,U,t),B=!0},p(e,[t]){const l={};t&2&&(l.$$scope={dirty:t,ctx:e}),v.$set(l);const A={};t&2&&(A.$$scope={dirty:t,ctx:e}),T.$set(A)},i(e){B||($(y.$$.fragment,e),$(M.$$.fragment,e),$(C.$$.fragment,e),$(V.$$.fragment,e),$(v.$$.fragment,e),$(G.$$.fragment,e),$(L.$$.fragment,e),$(T.$$.fragment,e),$(j.$$.fragment,e),B=!0)},o(e){F(y.$$.fragment,e),F(M.$$.fragment,e),F(C.$$.fragment,e),F(V.$$.fragment,e),F(v.$$.fragment,e),F(G.$$.fragment,e),F(L.$$.fragment,e),F(T.$$.fragment,e),F(j.$$.fragment,e),B=!1},d(e){e&&(o(u),o(r),o(w),o(q),o(D),o(J),o(N),o(d),o(Q),o(O),o(U)),o(s),b(y,e),b(M,e),b(C),b(V),b(v),b(G),b(L),b(T),b(j,e)}}}const xe='{"title":"AuraFlowTransformer2DModel","local":"auraflowtransformer2dmodel","sections":[{"title":"AuraFlowTransformer2DModel","local":"diffusers.AuraFlowTransformer2DModel","sections":[],"depth":2}],"depth":1}';function Te(z){return he(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class Ge extends Pe{constructor(s){super(),ge(this,s,Te,ve,Ae,{})}}export{Ge as component};