import{s as ve,n as We,o as Ze}from"../chunks/scheduler.56725da7.js";import{S as Ge,i as Ve,e as c,s,c as o,h as Ie,a as M,d as n,b as a,f as de,g as i,j as y,k as fe,l as be,m as l,n as r,t as p,o as m,p as u}from"../chunks/index.18a26576.js";import{C as Le}from"../chunks/CopyLLMTxtMenu.f4001e5e.js";import{D as Ce}from"../chunks/Docstring.185d8bd7.js";import{C as ye}from"../chunks/CodeBlock.e59f1853.js";import{H as x}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.d7e7b6b3.js";function Be(_e){let d,E,k,Q,h,R,b,F,_,H,g,ge='Latent Consistency Models (LCMs) were proposed in <a href="https://huggingface.co/papers/2310.04378" rel="nofollow">Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference by Simian Luo, Yiqin Tan, Longbo Huang, Jian Li, and Hang Zhao</a>. LCMs enable inference with fewer steps on any pre-trained LDMs, including Stable Diffusion and SDXL.',Y,j,je="In <code>optimum-neuron</code>, you can:",D,w,we="<li>Use the class <code>NeuronLatentConsistencyModelPipeline</code> to compile and run inference of LCMs distilled from Stable Diffusion (SD) models.</li> <li>And continue to use the class <code>NeuronStableDiffusionXLPipeline</code> for LCMs distilled from SDXL models.</li>",P,J,Je='Here are examples to compile the LCMs of Stable Diffusion ( <a href="https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7" rel="nofollow">SimianLuo/LCM_Dreamshaper_v7</a> ) and Stable Diffusion XL( <a href="https://huggingface.co/latent-consistency/lcm-sdxl" rel="nofollow">latent-consistency/lcm-sdxl</a> ), and then run inference on AWS Inferentia 2 :',A,T,K,N,O,U,ee,X,te,$,ne,C,le,v,Te="Now we can generate images from text prompts on Inf2 using the pre-compiled model:",se,W,Ne="<li>LCM of Stable Diffusion</li>",ae,Z,oe,G,Ue="<li>LCM of Stable Diffusion XL</li>",ie,V,re,I,pe,f,L,he,q,B,me,S,Xe='Are there any other diffusion features that you want us to support in 🤗<code>Optimum-neuron</code>? Please file an issue to <a href="https://github.com/huggingface/optimum-neuron" rel="nofollow"><code>Optimum-neuron</code> Github repo</a> or discuss with us on <a href="https://discuss.huggingface.co/c/optimum/" rel="nofollow">HuggingFace’s community forum</a>, cheers 🤗 !',ue,z,ce;return h=new Le({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),b=new x({props:{title:"Latent Consistency Models",local:"latent-consistency-models",headingTag:"h1"}}),_=new x({props:{title:"Overview",local:"overview",headingTag:"h2"}}),T=new x({props:{title:"Export to Neuron",local:"export-to-neuron",headingTag:"h2"}}),N=new x({props:{title:"LCM of Stable Diffusion",local:"lcm-of-stable-diffusion",headingTag:"h3"}}),U=new ye({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronLatentConsistencyModelPipeline

model_id = <span class="hljs-string">&quot;SimianLuo/LCM_Dreamshaper_v7&quot;</span>
num_images_per_prompt = <span class="hljs-number">1</span>
input_shapes = {<span class="hljs-string">&quot;batch_size&quot;</span>: <span class="hljs-number">1</span>, <span class="hljs-string">&quot;height&quot;</span>: <span class="hljs-number">768</span>, <span class="hljs-string">&quot;width&quot;</span>: <span class="hljs-number">768</span>, <span class="hljs-string">&quot;num_images_per_prompt&quot;</span>: num_images_per_prompt}
compiler_args = {<span class="hljs-string">&quot;auto_cast&quot;</span>: <span class="hljs-string">&quot;matmul&quot;</span>, <span class="hljs-string">&quot;auto_cast_type&quot;</span>: <span class="hljs-string">&quot;bf16&quot;</span>}

stable_diffusion = NeuronLatentConsistencyModelPipeline.from_pretrained(
    model_id, export=<span class="hljs-literal">True</span>, **compiler_args, **input_shapes
)
save_directory = <span class="hljs-string">&quot;lcm_sd_neuron/&quot;</span>
stable_diffusion.save_pretrained(save_directory)

<span class="hljs-comment"># Push to hub</span>
stable_diffusion.push_to_hub(save_directory, repository_id=<span class="hljs-string">&quot;my-neuron-repo&quot;</span>)  <span class="hljs-comment"># Replace with your repo id, eg. &quot;Jingya/LCM_Dreamshaper_v7_neuronx&quot;</span>`,wrap:!1}}),X=new x({props:{title:"LCM of Stable Diffusion XL",local:"lcm-of-stable-diffusion-xl",headingTag:"h3"}}),$=new ye({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLPipeline

model_id = <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>
unet_id = <span class="hljs-string">&quot;latent-consistency/lcm-sdxl&quot;</span>
num_images_per_prompt = <span class="hljs-number">1</span>
input_shapes = {<span class="hljs-string">&quot;batch_size&quot;</span>: <span class="hljs-number">1</span>, <span class="hljs-string">&quot;height&quot;</span>: <span class="hljs-number">1024</span>, <span class="hljs-string">&quot;width&quot;</span>: <span class="hljs-number">1024</span>, <span class="hljs-string">&quot;num_images_per_prompt&quot;</span>: num_images_per_prompt}
compiler_args = {<span class="hljs-string">&quot;auto_cast&quot;</span>: <span class="hljs-string">&quot;matmul&quot;</span>, <span class="hljs-string">&quot;auto_cast_type&quot;</span>: <span class="hljs-string">&quot;bf16&quot;</span>}

stable_diffusion = NeuronStableDiffusionXLPipeline.from_pretrained(
    model_id, unet_id=unet_id, export=<span class="hljs-literal">True</span>, **compiler_args, **input_shapes
)
save_directory = <span class="hljs-string">&quot;lcm_sdxl_neuron/&quot;</span>
stable_diffusion.save_pretrained(save_directory)

<span class="hljs-comment"># Push to hub</span>
stable_diffusion.push_to_hub(save_directory, repository_id=<span class="hljs-string">&quot;my-neuron-repo&quot;</span>)   <span class="hljs-comment"># Replace with your repo id, eg. &quot;Jingya/lcm-sdxl-neuronx&quot;</span>`,wrap:!1}}),C=new x({props:{title:"Text-to-Image",local:"text-to-image",headingTag:"h2"}}),Z=new ye({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronLatentConsistencyModelPipeline

pipe = NeuronLatentConsistencyModelPipeline.from_pretrained(<span class="hljs-string">&quot;Jingya/LCM_Dreamshaper_v7_neuronx&quot;</span>)
prompts = [<span class="hljs-string">&quot;Self-portrait oil painting, a beautiful cyborg with golden hair, 8k&quot;</span>] * <span class="hljs-number">2</span>

images = pipe(prompt=prompts, num_inference_steps=<span class="hljs-number">4</span>, guidance_scale=<span class="hljs-number">8.0</span>).images`,wrap:!1}}),V=new ye({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLPipeline

pipe = NeuronStableDiffusionXLPipeline.from_pretrained(<span class="hljs-string">&quot;Jingya/lcm-sdxl-neuronx&quot;</span>)
prompts = [<span class="hljs-string">&quot;a close-up picture of an old man standing in the rain&quot;</span>] * <span class="hljs-number">2</span>

images = pipe(prompt=prompts, num_inference_steps=<span class="hljs-number">4</span>, guidance_scale=<span class="hljs-number">8.0</span>).images`,wrap:!1}}),I=new x({props:{title:"NeuronLatentConsistencyModelPipeline",local:"optimum.neuron.NeuronLatentConsistencyModelPipeline",headingTag:"h2"}}),L=new Ce({props:{name:"class optimum.neuron.NeuronLatentConsistencyModelPipeline",anchor:"optimum.neuron.NeuronLatentConsistencyModelPipeline",parameters:[{name:"config",val:": dict[str, typing.Any]"},{name:"configs",val:": dict[str, 'PretrainedConfig']"},{name:"neuron_configs",val:": dict[str, 'NeuronDefaultConfig']"},{name:"data_parallel_mode",val:": typing.Literal['none', 'unet', 'transformer', 'all']"},{name:"scheduler",val:": diffusers.schedulers.scheduling_utils.SchedulerMixin | None"},{name:"vae_decoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeDecoder"},{name:"text_encoder",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"text_encoder_2",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"unet",val:": torch.jit._script.ScriptModule | NeuronModelUnet | None = None"},{name:"transformer",val:": torch.jit._script.ScriptModule | NeuronModelTransformer | None = None"},{name:"vae_encoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeEncoder | None = None"},{name:"image_encoder",val:": torch.jit._script.ScriptModule | None = None"},{name:"safety_checker",val:": torch.jit._script.ScriptModule | None = None"},{name:"tokenizer",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | transformers.models.t5.tokenization_t5.T5Tokenizer | None = None"},{name:"tokenizer_2",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | None = None"},{name:"feature_extractor",val:": transformers.models.clip.feature_extraction_clip.CLIPFeatureExtractor | None = None"},{name:"controlnet",val:": torch.jit._script.ScriptModule | list[torch.jit._script.ScriptModule]| NeuronControlNetModel | NeuronMultiControlNetModel | None = None"},{name:"requires_aesthetics_score",val:": bool = False"},{name:"force_zeros_for_empty_prompt",val:": bool = True"},{name:"add_watermarker",val:": bool | None = None"},{name:"model_save_dir",val:": str | pathlib.Path | tempfile.TemporaryDirectory | None = None"},{name:"model_and_config_save_paths",val:": dict[str, tuple[str, pathlib.Path]] | None = None"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.1/optimum/neuron/modeling_diffusion.py#L1567"}}),B=new Ce({props:{name:"__call__",anchor:"optimum.neuron.NeuronLatentConsistencyModelPipeline.__call__",parameters:[{name:"*args",val:""},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.1/optimum/neuron/modeling_diffusion.py#L1106"}}),{c(){d=c("meta"),E=s(),k=c("p"),Q=s(),o(h.$$.fragment),R=s(),o(b.$$.fragment),F=s(),o(_.$$.fragment),H=s(),g=c("p"),g.innerHTML=ge,Y=s(),j=c("p"),j.innerHTML=je,D=s(),w=c("ul"),w.innerHTML=we,P=s(),J=c("p"),J.innerHTML=Je,A=s(),o(T.$$.fragment),K=s(),o(N.$$.fragment),O=s(),o(U.$$.fragment),ee=s(),o(X.$$.fragment),te=s(),o($.$$.fragment),ne=s(),o(C.$$.fragment),le=s(),v=c("p"),v.textContent=Te,se=s(),W=c("ul"),W.innerHTML=Ne,ae=s(),o(Z.$$.fragment),oe=s(),G=c("ul"),G.innerHTML=Ue,ie=s(),o(V.$$.fragment),re=s(),o(I.$$.fragment),pe=s(),f=c("div"),o(L.$$.fragment),he=s(),q=c("div"),o(B.$$.fragment),me=s(),S=c("p"),S.innerHTML=Xe,ue=s(),z=c("p"),this.h()},l(e){const 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