diffusers/pr_13843/en/_app/immutable/nodes/18.db4c2cd3.js

import{s as ie,n as me,o as fe}from"../chunks/scheduler.53228c21.js";import{S as ce,i as pe,e as a,s as n,c as f,h as ue,a as l,d as r,b as s,f as j,g as c,j as K,k as F,l as C,m as o,n as p,t as u,o as g,p as h}from"../chunks/index.cac5d66a.js";import{C as ge}from"../chunks/CopyLLMTxtMenu.fefa00c9.js";import{D as re}from"../chunks/Docstring.1ffb398c.js";import{C as he}from"../chunks/CodeBlock.606cbaf4.js";import{H as oe,E as _e}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.64289e00.js";function $e(ne){let d,N,U,O,$,P,T,V,v,se='A Diffusion Transformer model for 3D data from <a href="https://github.com/rhymes-ai/Allegro" rel="nofollow">Allegro</a> was introduced in <a href="https://huggingface.co/papers/2410.15458" rel="nofollow">Allegro: Open the Black Box of Commercial-Level Video Generation Model</a> by RhymesAI.',z,b,ae="The model can be loaded with the following code snippet.",G,M,I,y,H,i,D,Q,_,w,ee,E,le='The <a href="/docs/diffusers/pr_13843/en/api/models/allegro_transformer3d#diffusers.AllegroTransformer3DModel">AllegroTransformer3DModel</a> forward method.',q,x,R,m,A,te,L,de='The output of <a href="/docs/diffusers/pr_13843/en/api/models/transformer2d#diffusers.Transformer2DModel">Transformer2DModel</a>.',S,k,W,Z,J;return $=new ge({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),T=new oe({props:{title:"AllegroTransformer3DModel",local:"allegrotransformer3dmodel",headingTag:"h1"}}),M=new he({props:{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMEFsbGVncm9UcmFuc2Zvcm1lcjNETW9kZWwlMEElMEF0cmFuc2Zvcm1lciUyMCUzRCUyMEFsbGVncm9UcmFuc2Zvcm1lcjNETW9kZWwuZnJvbV9wcmV0cmFpbmVkKCUyMnJoeW1lcy1haSUyRkFsbGVncm8lMjIlMkMlMjBzdWJmb2xkZXIlM0QlMjJ0cmFuc2Zvcm1lciUyMiUyQyUyMHRvcmNoX2R0eXBlJTNEdG9yY2guYmZsb2F0MTYpLnRvKCUyMmN1ZGElMjIp",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AllegroTransformer3DModel

transformer = AllegroTransformer3DModel.from_pretrained(<span class="hljs-string">&quot;rhymes-ai/Allegro&quot;</span>, subfolder=<span class="hljs-string">&quot;transformer&quot;</span>, torch_dtype=torch.bfloat16).to(<span class="hljs-string">&quot;cuda&quot;</span>)`,lang:"python",wrap:!1}}),y=new oe({props:{title:"AllegroTransformer3DModel",local:"diffusers.AllegroTransformer3DModel",headingTag:"h2"}}),D=new re({props:{name:"class diffusers.AllegroTransformer3DModel",anchor:"diffusers.AllegroTransformer3DModel",parameters:[{name:"patch_size",val:": int = 2"},{name:"patch_size_t",val:": int = 1"},{name:"num_attention_heads",val:": int = 24"},{name:"attention_head_dim",val:": int = 96"},{name:"in_channels",val:": int = 4"},{name:"out_channels",val:": int = 4"},{name:"num_layers",val:": int = 32"},{name:"dropout",val:": float = 0.0"},{name:"cross_attention_dim",val:": int = 2304"},{name:"attention_bias",val:": bool = True"},{name:"sample_height",val:": int = 90"},{name:"sample_width",val:": int = 160"},{name:"sample_frames",val:": int = 22"},{name:"activation_fn",val:": str = 'gelu-approximate'"},{name:"norm_elementwise_affine",val:": bool = False"},{name:"norm_eps",val:": float = 1e-06"},{name:"caption_channels",val:": int = 4096"},{name:"interpolation_scale_h",val:": float = 2.0"},{name:"interpolation_scale_w",val:": float = 2.0"},{name:"interpolation_scale_t",val:": float = 2.2"}],source:"https://github.com/huggingface/diffusers/blob/vr_13843/src/diffusers/models/transformers/transformer_allegro.py#L174"}}),w=new re({props:{name:"forward",anchor:"diffusers.AllegroTransformer3DModel.forward",parameters:[{name:"hidden_states",val:": Tensor"},{name:"encoder_hidden_states",val:": Tensor"},{name:"timestep",val:": LongTensor"},{name:"attention_mask",val:": torch.Tensor | None = None"},{name:"encoder_attention_mask",val:": torch.Tensor | None = None"},{name:"image_rotary_emb",val:": tuple[torch.Tensor, torch.Tensor] | None = None"},{name:"return_dict",val:": bool = True"}],parametersDescription:[{anchor:"diffusers.AllegroTransformer3DModel.forward.hidden_states",description:`<strong>hidden_states</strong> (<code>torch.Tensor</code> of shape <code>(batch_size, num_channels, num_frames, height, width)</code>) &#x2014;
Input <code>hidden_states</code>.`,name:"hidden_states"},{anchor:"diffusers.AllegroTransformer3DModel.forward.encoder_hidden_states",description:`<strong>encoder_hidden_states</strong> (<code>torch.Tensor</code> of shape <code>(batch_size, sequence_len, embed_dims)</code>) &#x2014;
Conditional embeddings (embeddings computed from the input conditions such as prompts) to use.`,name:"encoder_hidden_states"},{anchor:"diffusers.AllegroTransformer3DModel.forward.timestep",description:`<strong>timestep</strong> (<code>torch.LongTensor</code>) &#x2014;
Used to indicate denoising step.`,name:"timestep"},{anchor:"diffusers.AllegroTransformer3DModel.forward.attention_mask",description:`<strong>attention_mask</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Self-attention mask applied to <code>hidden_states</code>.`,name:"attention_mask"},{anchor:"diffusers.AllegroTransformer3DModel.forward.encoder_attention_mask",description:`<strong>encoder_attention_mask</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Cross-attention mask applied to <code>encoder_hidden_states</code>.`,name:"encoder_attention_mask"},{anchor:"diffusers.AllegroTransformer3DModel.forward.image_rotary_emb",description:`<strong>image_rotary_emb</strong> (<code>tuple</code> of <code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Pre-computed rotary positional embeddings.`,name:"image_rotary_emb"},{anchor:"diffusers.AllegroTransformer3DModel.forward.return_dict",description:`<strong>return_dict</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) &#x2014;
Whether or not to return a <code>~models.transformer_2d.Transformer2DModelOutput</code> instead of a plain
tuple.`,name:"return_dict"}],source:"https://github.com/huggingface/diffusers/blob/vr_13843/src/diffusers/models/transformers/transformer_allegro.py#L305",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>If <code>return_dict</code> is True, an <code>~models.transformer_2d.Transformer2DModelOutput</code> is returned, otherwise a
<code>tuple</code> where the first element is the sample tensor.</p>
`}}),x=new oe({props:{title:"Transformer2DModelOutput",local:"diffusers.models.modeling_outputs.Transformer2DModelOutput",headingTag:"h2"}}),A=new re({props:{name:"class diffusers.models.modeling_outputs.Transformer2DModelOutput",anchor:"diffusers.models.modeling_outputs.Transformer2DModelOutput",parameters:[{name:"sample",val:": torch.Tensor"}],parametersDescription:[{anchor:"diffusers.models.modeling_outputs.Transformer2DModelOutput.sample",description:`<strong>sample</strong> (<code>torch.Tensor</code> of shape <code>(batch_size, num_channels, height, width)</code> or <code>(batch size, num_vector_embeds - 1, num_latent_pixels)</code> if <a href="/docs/diffusers/pr_13843/en/api/models/transformer2d#diffusers.Transformer2DModel">Transformer2DModel</a> is discrete) &#x2014;
The hidden states output conditioned on the <code>encoder_hidden_states</code> input. If discrete, returns probability
distributions for the unnoised latent pixels.`,name:"sample"}],source:"https://github.com/huggingface/diffusers/blob/vr_13843/src/diffusers/models/modeling_outputs.py#L21"}}),k=new _e({props:{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/en/api/models/allegro_transformer3d.md"}}),{c(){d=a("meta"),N=n(),U=a("p"),O=n(),f($.$$.fragment),P=n(),f(T.$$.fragment),V=n(),v=a("p"),v.innerHTML=se,z=n(),b=a("p"),b.textContent=ae,G=n(),f(M.$$.fragment),I=n(),f(y.$$.fragment),H=n(),i=a("div"),f(D.$$.fragment),Q=n(),_=a("div"),f(w.$$.fragment),ee=n(),E=a("p"),E.innerHTML=le,q=n(),f(x.$$.fragment),R=n(),m=a("div"),f(A.$$.fragment),te=n(),L=a("p"),L.innerHTML=de,S=n(),f(k.$$.fragment),W=n(),Z=a("p"),this.h()},l(e){const t=ue("svelte-u9bgzb",document.head);d=l(t,"META",{name:!0,content:!0}),t.forEach(r),N=s(e),U=l(e,"P",{}),j(U).forEach(r),O=s(e),c($.$$.fragment,e),P=s(e),c(T.$$.fragment,e),V=s(e),v=l(e,"P",{"data-svelte-h":!0}),K(v)!=="svelte-x6xll5"&&(v.innerHTML=se),z=s(e),b=l(e,"P",{"data-svelte-h":!0}),K(b)!=="svelte-1vuni30"&&(b.textContent=ae),G=s(e),c(M.$$.fragment,e),I=s(e),c(y.$$.fragment,e),H=s(e),i=l(e,"DIV",{class:!0});var B=j(i);c(D.$$.fragment,B),Q=s(B),_=l(B,"DIV",{class:!0});var X=j(_);c(w.$$.fragment,X),ee=s(X),E=l(X,"P",{"data-svelte-h":!0}),K(E)!=="svelte-gusng3"&&(E.innerHTML=le),X.forEach(r),B.forEach(r),q=s(e),c(x.$$.fragment,e),R=s(e),m=l(e,"DIV",{class:!0});var Y=j(m);c(A.$$.fragment,Y),te=s(Y),L=l(Y,"P",{"data-svelte-h":!0}),K(L)!=="svelte-42k425"&&(L.innerHTML=de),Y.forEach(r),S=s(e),c(k.$$.fragment,e),W=s(e),Z=l(e,"P",{}),j(Z).forEach(r),this.h()},h(){F(d,"name","hf:doc:metadata"),F(d,"content",Te),F(_,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),F(i,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),F(m,"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){C(document.head,d),o(e,N,t),o(e,U,t),o(e,O,t),p($,e,t),o(e,P,t),p(T,e,t),o(e,V,t),o(e,v,t),o(e,z,t),o(e,b,t),o(e,G,t),p(M,e,t),o(e,I,t),p(y,e,t),o(e,H,t),o(e,i,t),p(D,i,null),C(i,Q),C(i,_),p(w,_,null),C(_,ee),C(_,E),o(e,q,t),p(x,e,t),o(e,R,t),o(e,m,t),p(A,m,null),C(m,te),C(m,L),o(e,S,t),p(k,e,t),o(e,W,t),o(e,Z,t),J=!0},p:me,i(e){J||(u($.$$.fragment,e),u(T.$$.fragment,e),u(M.$$.fragment,e),u(y.$$.fragment,e),u(D.$$.fragment,e),u(w.$$.fragment,e),u(x.$$.fragment,e),u(A.$$.fragment,e),u(k.$$.fragment,e),J=!0)},o(e){g($.$$.fragment,e),g(T.$$.fragment,e),g(M.$$.fragment,e),g(y.$$.fragment,e),g(D.$$.fragment,e),g(w.$$.fragment,e),g(x.$$.fragment,e),g(A.$$.fragment,e),g(k.$$.fragment,e),J=!1},d(e){e&&(r(N),r(U),r(O),r(P),r(V),r(v),r(z),r(b),r(G),r(I),r(H),r(i),r(q),r(R),r(m),r(S),r(W),r(Z)),r(d),h($,e),h(T,e),h(M,e),h(y,e),h(D),h(w),h(x,e),h(A),h(k,e)}}}const Te='{"title":"AllegroTransformer3DModel","local":"allegrotransformer3dmodel","sections":[{"title":"AllegroTransformer3DModel","local":"diffusers.AllegroTransformer3DModel","sections":[],"depth":2},{"title":"Transformer2DModelOutput","local":"diffusers.models.modeling_outputs.Transformer2DModelOutput","sections":[],"depth":2}],"depth":1}';function ve(ne){return fe(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class Ae extends ce{constructor(d){super(),pe(this,d,ve,$e,ie,{})}}export{Ae as component};