optimum-neuron/pr_1113/en/_app/immutable/nodes/36.e51557af.js

import{s as Dt,a as qt,o as Pt,n as At}from"../chunks/scheduler.56725da7.js";import{S as Ot,i as Kt,e as s,s as a,c as r,h as en,a as o,d as n,b as i,f as N,g as m,j as g,k as h,l as ye,m as l,n as p,t as u,o as d,p as c}from"../chunks/index.18a26576.js";import{T as tn}from"../chunks/Tip.5b941656.js";import{D as ve}from"../chunks/Docstring.ae0283b4.js";import{C as Te}from"../chunks/CodeBlock.6dd2f5ab.js";import{H as M}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.0f5f04c9.js";function nn($e){let f,$="To avoid Neuron device out of memory, it’s suggested to finish all base inference and release the device memory before running the refiner.";return{c(){f=s("p"),f.textContent=$},l(b){f=o(b,"P",{"data-svelte-h":!0}),g(f)!=="svelte-1323ut2"&&(f.textContent=$)},m(b,Je){l(b,f,Je)},p:At,d(b){b&&n(f)}}}function ln($e){let f,$,b,Je,Z,Ze,j,vt='<em>There is a notebook version of that tutorial <a href="https://github.com/huggingface/optimum-neuron/blob/main/notebooks/stable-diffusion/stable-diffusion-xl-txt2img.ipynb" rel="nofollow">here</a></em>.',je,I,Ie,W,Nt="Stable Diffusion XL (SDXL) is a latent diffusion model for text-to-image. Compared to the previous versions of Stable Diffusion models, it improves the quality of generated images with a times larger UNet.",We,X,$t="🤗 <code>Optimum</code> extends <code>Diffusers</code> to support inference on the second generation of Neuron devices(powering Trainium and Inferentia 2). It aims at inheriting the ease of Diffusers on Neuron.",Xe,C,Ce,G,Zt="To deploy SDXL models, we will start by compiling the models. We support the export of following components in the pipeline to boost the speed:",Ge,S,jt="<li>Text encoder</li> <li>Second text encoder</li> <li>U-Net (a three times larger UNet than the one in Stable Diffusion pipeline)</li> <li>VAE encoder</li> <li>VAE decoder</li>",Se,x,It="You can either compile and export a Stable Diffusion XL Checkpoint via CLI or <code>NeuronStableDiffusionXLPipeline</code> class.",xe,k,ke,B,Wt="Here is an example of exporting SDXL components with <code>Optimum</code> CLI:",Be,V,Ve,U,Xt="<p>We recommend using a <code>inf2.8xlarge</code> or a larger instance for the model compilation. You will also be able to compile the model with the Optimum CLI on a CPU-only instance (needs ~35 GB memory), and then run the pre-compiled model on <code>inf2.xlarge</code> to reduce the expenses. In this case, don’t forget to disable validation of inference by adding the <code>--disable-validation</code> argument.</p>",Le,L,Re,R,Ct="Here is an example of exporting stable diffusion components with <code>NeuronStableDiffusionXLPipeline</code>:",ze,z,He,H,Qe,Q,Gt="With pre-compiled SDXL models, now generate an image with a text prompt on Neuron:",Ye,Y,Ee,y,St,Fe,E,qe,F,xt="With <code>NeuronStableDiffusionXLImg2ImgPipeline</code>, you can pass an initial image, and a text prompt to condition generated images:",De,q,Pe,D,kt='<thead><tr><th align="center"><code>image</code></th> <th align="center"><code>prompt</code></th> <th align="center">output</th> <th align="right"></th></tr></thead> <tbody><tr><td align="center"><img src="https://huggingface.co/datasets/optimum/documentation-images/resolve/main/intel/openvino/sd_xl/castle_friedrich.png" alt="castle photo" width="256" height="256"/></td> <td align="center"><strong><em>a dog running, lake, moat</em></strong></td> <td align="center"><img src="https://huggingface.co/datasets/optimum/documentation-images/resolve/main/neuron/models/06-sdxl-img2img.png" alt="castle with dog" width="250"/></td> <td align="right"></td></tr></tbody>',Ae,P,Oe,A,Bt="With <code>NeuronStableDiffusionXLInpaintPipeline</code>, pass the original image and a mask of what you want to replace in the original image. Then replace the masked area with content described in a prompt.",Ke,O,et,K,Vt='<thead><tr><th align="center"><code>image</code></th> <th align="center"><code>mask_image</code></th> <th align="center"><code>prompt</code></th> <th align="right">output</th></tr></thead> <tbody><tr><td align="center"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/sdxl-text2img.png" alt="drawing" width="250"/></td> <td align="center"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/sdxl-inpaint-mask.png" alt="drawing" width="250"/></td> <td align="center"><strong><em>A deep sea diver floating</em></strong></td> <td align="right"><img src="https://huggingface.co/datasets/optimum/documentation-images/resolve/main/neuron/models/07-sdxl-inpaint.png" alt="drawing" width="250"/></td></tr></tbody>',tt,ee,nt,te,Lt='SDXL includes a <a href="https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0" rel="nofollow">refiner model</a> to denoise low-noise stage images generated from the base model. There are two ways to use the refiner:',lt,ne,Rt="<li>use the base and refiner model together to produce a refined image.</li> <li>use the base model to produce an image, and subsequently use the refiner model to add more details to the image.</li>",at,le,it,ae,st,T,zt,ot,ie,rt,se,mt,oe,Ht='<thead><tr><th align="center"><code>Base Image</code></th> <th align="right">Refined Image</th></tr></thead> <tbody><tr><td align="center"><img src="https://huggingface.co/datasets/optimum/documentation-images/resolve/main/neuron/models/09-sdxl-base-full.png" alt="drawing" width="250"/></td> <td align="right"><img src="https://huggingface.co/datasets/optimum/documentation-images/resolve/main/neuron/models/010-sdxl-refiner-detailed.png" alt="drawing" width="250"/></td></tr></tbody>',pt,v,ut,re,dt,J,me,wt,we,pe,ct,ue,gt,w,de,_t,_e,ce,ft,ge,ht,_,fe,Ut,Ue,he,Mt,Me,Qt='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 🤗 !',bt,Ne,yt;return Z=new M({props:{title:"Stable Diffusion XL",local:"stable-diffusion-xl",headingTag:"h2"}}),I=new M({props:{title:"Overview",local:"overview",headingTag:"h2"}}),C=new M({props:{title:"Export to Neuron",local:"export-to-neuron",headingTag:"h2"}}),k=new M({props:{title:"Option 1: CLI",local:"option-1-cli",headingTag:"h3"}}),V=new Te({props:{code:"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",highlighted:'optimum-cli <span class="hljs-built_in">export</span> neuron --model stabilityai/stable-diffusion-xl-base-1.0 \\\n  --batch_size 1 \\\n  --height 1024 `<span class="hljs-comment"># height in pixels of generated image, eg. 768, 1024` \\</span>\n  --width 1024 `<span class="hljs-comment"># width in pixels of generated image, eg. 768, 1024` \\</span>\n  --num_images_per_prompt 1 `<span class="hljs-comment"># number of images to generate per prompt, defaults to 1` \\</span>\n  --auto_cast matmul `<span class="hljs-comment"># cast only matrix multiplication operations` \\</span>\n  --auto_cast_type bf16 `<span class="hljs-comment"># cast operations from FP32 to BF16` \\</span>\n  sd_neuron_xl/',lang:"bash",wrap:!1}}),L=new M({props:{title:"Option 2: Python API",local:"option-2-python-api",headingTag:"h3"}}),z=new Te({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLPipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>model_id = <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>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>}
<span class="hljs-meta">&gt;&gt;&gt; </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-meta">&gt;&gt;&gt; </span>stable_diffusion_xl = NeuronStableDiffusionXLPipeline.from_pretrained(model_id, export=<span class="hljs-literal">True</span>, **compiler_args, **input_shapes)

&lt;CopyLLMTxtMenu containerStyle=<span class="hljs-string">&quot;float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;&quot;</span>&gt;&lt;/CopyLLMTxtMenu&gt;

<span class="hljs-comment"># Save locally or upload to the HuggingFace Hub</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>save_directory = <span class="hljs-string">&quot;sd_neuron_xl/&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>stable_diffusion_xl.save_pretrained(save_directory)
<span class="hljs-meta">&gt;&gt;&gt; </span>stable_diffusion_xl.push_to_hub(
<span class="hljs-meta">... </span>    save_directory, repository_id=<span class="hljs-string">&quot;my-neuron-repo&quot;</span>
<span class="hljs-meta">... </span>)`,lang:"python",wrap:!1}}),H=new M({props:{title:"Text-to-Image",local:"text-to-image",headingTag:"h2"}}),Y=new Te({props:{code:"ZnJvbSUyMG9wdGltdW0ubmV1cm9uJTIwaW1wb3J0JTIwTmV1cm9uU3RhYmxlRGlmZnVzaW9uWExQaXBlbGluZSUwQSUwQXN0YWJsZV9kaWZmdXNpb25feGwlMjAlM0QlMjBOZXVyb25TdGFibGVEaWZmdXNpb25YTFBpcGVsaW5lLmZyb21fcHJldHJhaW5lZCglMjJzZF9uZXVyb25feGwlMkYlMjIpJTBBcHJvbXB0JTIwJTNEJTIwJTIyQXN0cm9uYXV0JTIwaW4lMjBhJTIwanVuZ2xlJTJDJTIwY29sZCUyMGNvbG9yJTIwcGFsZXR0ZSUyQyUyMG11dGVkJTIwY29sb3JzJTJDJTIwZGV0YWlsZWQlMkMlMjA4ayUyMiUwQWltYWdlJTIwJTNEJTIwc3RhYmxlX2RpZmZ1c2lvbl94bChwcm9tcHQpLmltYWdlcyU1QjAlNUQ=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLPipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>stable_diffusion_xl = NeuronStableDiffusionXLPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl/&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>prompt = <span class="hljs-string">&quot;Astronaut in a jungle, cold color palette, muted colors, detailed, 8k&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>image = stable_diffusion_xl(prompt).images[<span class="hljs-number">0</span>]`,lang:"python",wrap:!1}}),E=new M({props:{title:"Image-to-Image",local:"image-to-image",headingTag:"h2"}}),q=new Te({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLImg2ImgPipeline
<span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image

prompt = <span class="hljs-string">&quot;a dog running, lake, moat&quot;</span>
url = <span class="hljs-string">&quot;https://huggingface.co/datasets/optimum/documentation-images/resolve/main/intel/openvino/sd_xl/castle_friedrich.png&quot;</span>
init_image = load_image(url).convert(<span class="hljs-string">&quot;RGB&quot;</span>)

pipe = NeuronStableDiffusionXLImg2ImgPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl/&quot;</span>)
image = pipe(prompt=prompt, image=init_image).images[<span class="hljs-number">0</span>]`,lang:"python",wrap:!1}}),P=new M({props:{title:"Inpaint",local:"inpaint",headingTag:"h2"}}),O=new Te({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLInpaintPipeline
<span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image

img_url = <span class="hljs-string">&quot;https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/sdxl-text2img.png&quot;</span>
mask_url = (
    <span class="hljs-string">&quot;https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/sdxl-inpaint-mask.png&quot;</span>
)

init_image = load_image(img_url).convert(<span class="hljs-string">&quot;RGB&quot;</span>)
mask_image = load_image(mask_url).convert(<span class="hljs-string">&quot;RGB&quot;</span>)
prompt = <span class="hljs-string">&quot;A deep sea diver floating&quot;</span>

pipe = NeuronStableDiffusionXLInpaintPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl/&quot;</span>)
image = pipe(prompt=prompt, image=init_image, mask_image=mask_image, strength=<span class="hljs-number">0.85</span>, guidance_scale=<span class="hljs-number">12.5</span>).images[<span class="hljs-number">0</span>]`,lang:"python",wrap:!1}}),ee=new M({props:{title:"Refine Image Quality",local:"refine-image-quality",headingTag:"h2"}}),le=new M({props:{title:"Base + Refiner Model",local:"base--refiner-model",headingTag:"h3"}}),ae=new Te({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLPipeline, NeuronStableDiffusionXLImg2ImgPipeline

prompt = <span class="hljs-string">&quot;A majestic lion jumping from a big stone at night&quot;</span>
base = NeuronStableDiffusionXLPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl/&quot;</span>)
image = base(
    prompt=prompt,
    num_inference_steps=<span class="hljs-number">40</span>,
    denoising_end=<span class="hljs-number">0.8</span>,
    output_type=<span class="hljs-string">&quot;latent&quot;</span>,
).images[<span class="hljs-number">0</span>]
<span class="hljs-keyword">del</span> base  <span class="hljs-comment"># To avoid neuron device OOM</span>

refiner = NeuronStableDiffusionXLImg2ImgPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl_refiner/&quot;</span>)
image = refiner(
    prompt=prompt,
    num_inference_steps=<span class="hljs-number">40</span>,
    denoising_start=<span class="hljs-number">0.8</span>,
    image=image,
).images[<span class="hljs-number">0</span>]`,lang:"python",wrap:!1}}),ie=new M({props:{title:"Base to refiner model",local:"base-to-refiner-model",headingTag:"h3"}}),se=new Te({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionXLPipeline, NeuronStableDiffusionXLImg2ImgPipeline

prompt = <span class="hljs-string">&quot;A majestic lion jumping from a big stone at night&quot;</span>
base = NeuronStableDiffusionXLPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl/&quot;</span>)
image = base(prompt=prompt, output_type=<span class="hljs-string">&quot;latent&quot;</span>).images[<span class="hljs-number">0</span>]
<span class="hljs-keyword">del</span> base  <span class="hljs-comment"># To avoid neuron device OOM</span>

refiner = NeuronStableDiffusionXLImg2ImgPipeline.from_pretrained(<span class="hljs-string">&quot;sd_neuron_xl_refiner/&quot;</span>)
image = refiner(prompt=prompt, image=image[<span class="hljs-literal">None</span>, :]).images[<span class="hljs-number">0</span>]`,lang:"python",wrap:!1}}),v=new tn({props:{$$slots:{default:[nn]},$$scope:{ctx:$e}}}),re=new M({props:{title:"NeuronStableDiffusionXLPipeline",local:"optimum.neuron.NeuronStableDiffusionXLPipeline",headingTag:"h2"}}),me=new ve({props:{name:"class optimum.neuron.NeuronStableDiffusionXLPipeline",anchor:"optimum.neuron.NeuronStableDiffusionXLPipeline",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 | transformers.models.t5.tokenization_t5.T5Tokenizer | 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/vr_1113/optimum/neuron/modeling_diffusion.py#L1586"}}),pe=new ve({props:{name:"__call__",anchor:"optimum.neuron.NeuronStableDiffusionXLPipeline.__call__",parameters:[{name:"*args",val:""},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/optimum-neuron/blob/vr_1113/optimum/neuron/modeling_diffusion.py#L1094"}}),ue=new M({props:{title:"NeuronStableDiffusionXLImg2ImgPipeline",local:"optimum.neuron.NeuronStableDiffusionXLImg2ImgPipeline",headingTag:"h2"}}),de=new ve({props:{name:"class optimum.neuron.NeuronStableDiffusionXLImg2ImgPipeline",anchor:"optimum.neuron.NeuronStableDiffusionXLImg2ImgPipeline",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 | transformers.models.t5.tokenization_t5.T5Tokenizer | 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/vr_1113/optimum/neuron/modeling_diffusion.py#L1599"}}),ce=new ve({props:{name:"__call__",anchor:"optimum.neuron.NeuronStableDiffusionXLImg2ImgPipeline.__call__",parameters:[{name:"*args",val:""},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/optimum-neuron/blob/vr_1113/optimum/neuron/modeling_diffusion.py#L1094"}}),ge=new M({props:{title:"NeuronStableDiffusionXLInpaintPipeline",local:"optimum.neuron.NeuronStableDiffusionXLInpaintPipeline",headingTag:"h2"}}),fe=new ve({props:{name:"class optimum.neuron.NeuronStableDiffusionXLInpaintPipeline",anchor:"optimum.neuron.NeuronStableDiffusionXLInpaintPipeline",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 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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/vr_1113/optimum/neuron/modeling_diffusion.py#L1606"}}),he=new 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