diffusers/pr_13966/en/_app/immutable/nodes/93.DNEtb7VC.js

import"../chunks/DsnmJJEf.js";import{i as N,h as x,C,H as c,D as m,E as S,s as U}from"../chunks/BtE7mKSK.js";import{p as w,o as T,s as e,f as y,a as p,b as k,c as _,d as f,r as u,n as D}from"../chunks/jDjavuwI.js";const L='{"title":"StableCascadeUNet","local":"stablecascadeunet","sections":[{"title":"StableCascadeUNet","local":"diffusers.models.StableCascadeUNet","sections":[],"depth":2}],"depth":1}';var P=f('<meta name="hf:doc:metadata"/>'),B=f('<p></p> <!> <!> <p>A UNet model from the <a href="../pipelines/stable_cascade">Stable Cascade pipeline</a>.</p> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!></div></div> <!> <p></p>',1);function A(b,g){w(g,!1),T(()=>{new URLSearchParams(window.location.search).get("fw")}),N();var t=B();x("1cwzcey",i=>{var d=P();U(d,"content",L),p(i,d)});var o=e(y(t),2);C(o,{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"});var n=e(o,2);c(n,{title:"StableCascadeUNet",local:"stablecascadeunet",headingTag:"h1"});var s=e(n,4);c(s,{title:"StableCascadeUNet",local:"diffusers.models.StableCascadeUNet",headingTag:"h2"});var a=e(s,2),r=_(a);m(r,{name:"class diffusers.models.StableCascadeUNet",anchor:"diffusers.models.StableCascadeUNet",source:"https://github.com/huggingface/diffusers/blob/vr_13966/src/diffusers/models/unets/unet_stable_cascade.py#L136",parameters:[{name:"in_channels",val:": int = 16"},{name:"out_channels",val:": int = 16"},{name:"timestep_ratio_embedding_dim",val:": int = 64"},{name:"patch_size",val:": int = 1"},{name:"conditioning_dim",val:": int = 2048"},{name:"block_out_channels",val:": tuple = (2048, 2048)"},{name:"num_attention_heads",val:": tuple = (32, 32)"},{name:"down_num_layers_per_block",val:": tuple = (8, 24)"},{name:"up_num_layers_per_block",val:": tuple = (24, 8)"},{name:"down_blocks_repeat_mappers",val:": tuple[int] | None = (1, 1)"},{name:"up_blocks_repeat_mappers",val:": tuple[int] | None = (1, 1)"},{name:"block_types_per_layer",val:": tuple = (('SDCascadeResBlock', 'SDCascadeTimestepBlock', 'SDCascadeAttnBlock'), ('SDCascadeResBlock', 'SDCascadeTimestepBlock', 'SDCascadeAttnBlock'))"},{name:"clip_text_in_channels",val:": int | None = None"},{name:"clip_text_pooled_in_channels",val:" = 1280"},{name:"clip_image_in_channels",val:": int | None = None"},{name:"clip_seq",val:" = 4"},{name:"effnet_in_channels",val:": int | None = None"},{name:"pixel_mapper_in_channels",val:": int | None = None"},{name:"kernel_size",val:" = 3"},{name:"dropout",val:": float | tuple[float] = (0.1, 0.1)"},{name:"self_attn",val:": bool | tuple[bool] = True"},{name:"timestep_conditioning_type",val:": tuple = ('sca', 'crp')"},{name:"switch_level",val:": tuple[bool] | None = None"}]});var l=e(r,2),h=_(l);m(h,{name:"forward",anchor:"diffusers.models.StableCascadeUNet.forward",source:"https://github.com/huggingface/diffusers/blob/vr_13966/src/diffusers/models/unets/unet_stable_cascade.py#L538",parameters:[{name:"sample",val:""},{name:"timestep_ratio",val:""},{name:"clip_text_pooled",val:""},{name:"clip_text",val:" = None"},{name:"clip_img",val:" = None"},{name:"effnet",val:" = None"},{name:"pixels",val:" = None"},{name:"sca",val:" = None"},{name:"crp",val:" = None"},{name:"return_dict",val:" = True"}],parametersDescription:[{anchor:"diffusers.models.StableCascadeUNet.forward.sample",description:"<strong>sample</strong> (<code>torch.Tensor</code>) &#x2014; The noisy input sample.",name:"sample"},{anchor:"diffusers.models.StableCascadeUNet.forward.timestep_ratio",description:`<strong>timestep_ratio</strong> (<code>torch.Tensor</code>) &#x2014;
Timestep ratio used to compute the timestep embedding.`,name:"timestep_ratio"},{anchor:"diffusers.models.StableCascadeUNet.forward.clip_text_pooled",description:`<strong>clip_text_pooled</strong> (<code>torch.Tensor</code>) &#x2014;
Pooled CLIP text embeddings.`,name:"clip_text_pooled"},{anchor:"diffusers.models.StableCascadeUNet.forward.clip_text",description:`<strong>clip_text</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Sequence-level CLIP text embeddings.`,name:"clip_text"},{anchor:"diffusers.models.StableCascadeUNet.forward.clip_img",description:`<strong>clip_img</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
CLIP image embeddings.`,name:"clip_img"},{anchor:"diffusers.models.StableCascadeUNet.forward.effnet",description:`<strong>effnet</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
EfficientNet feature map used as additional conditioning.`,name:"effnet"},{anchor:"diffusers.models.StableCascadeUNet.forward.pixels",description:`<strong>pixels</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Pixel-level conditioning tensor. If <code>None</code>, a tensor of zeros is used.`,name:"pixels"},{anchor:"diffusers.models.StableCascadeUNet.forward.sca",description:`<strong>sca</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Optional <code>sca</code> conditioning value used to build the timestep embedding.`,name:"sca"},{anchor:"diffusers.models.StableCascadeUNet.forward.crp",description:`<strong>crp</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Optional <code>crp</code> conditioning value used to build the timestep embedding.`,name:"crp"},{anchor:"diffusers.models.StableCascadeUNet.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>StableCascadeUNetOutput</code> instead of a plain tuple.`,name:"return_dict"}]}),u(l),u(a);var v=e(a,2);S(v,{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/en/api/models/stable_cascade_unet.md"}),D(2),p(b,t),k()}export{A as component};