diffusers/pr_13881/zh/optimization/neuron.html

<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;AWS Neuron&quot;,&quot;local&quot;:&quot;aws-neuron&quot;,&quot;sections&quot;:[],&quot;depth&quot;:1}"/>
		<link href="/docs/diffusers/main/zh/_app/immutable/entry/start.BjXnKLdN.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/BqKw7OfG.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/BbekZcyp.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/entry/app.C861NjaH.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/vgYqWUA9.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/JwskCAIl.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/DspwCNYP.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/DsnmJJEf.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/nodes/0.DGQv4KCz.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/D9q6WOrq.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/nodes/28.EgeO8bwW.js" rel="modulepreload">
		<link href="/docs/diffusers/main/zh/_app/immutable/chunks/DdZvggmf.js" rel="modulepreload">
		<!--11xqcdu--><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;AWS Neuron&quot;,&quot;local&quot;:&quot;aws-neuron&quot;,&quot;sections&quot;:[],&quot;depth&quot;:1}"/><!---->
		<link href="/docs/diffusers/main/zh/_app/immutable/assets/0.tn0RQdqM.css" rel="modulepreload"> <!--[--><!--[0--><!--[--><!--[0--><!--[--><p></p> <div class="items-center shrink-0 min-w-[100px] max-sm:min-w-[50px] justify-end ml-auto flex" style="float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"><div class="inline-flex rounded-md max-sm:rounded-sm"><button class="inline-flex items-center gap-1 h-7 max-sm:h-7 px-2 max-sm:px-1.5 text-sm font-medium text-gray-800 border border-r-0 rounded-l-md max-sm:rounded-l-sm border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-live="polite"><span class="inline-flex items-center justify-center rounded-md p-0.5 max-sm:p-0 hover:text-gray-800 dark:hover:text-gray-200"><svg class="sm:size-3.5 size-3" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----></span> <span>Copy page</span></button> <button class="inline-flex items-center justify-center w-6 max-sm:w-5 h-7 max-sm:h-7 disabled:pointer-events-none text-sm text-gray-500 hover:text-gray-700 dark:hover:text-white rounded-r-md max-sm:rounded-r-sm border border-l transition border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-haspopup="menu" aria-expanded="false" aria-label="Open copy menu"><svg class="transition-transform text-gray-400 overflow-visible sm:size-3.5 size-3 rotate-0" width="1em" height="1em" viewBox="0 0 12 7" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M1 1L6 6L11 1" stroke="currentColor"></path></svg><!----></button></div> <!--[-1--><!--]--></div><!----> <!--[0--><h1 class="relative group"><a id="aws-neuron" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#aws-neuron"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span>AWS Neuron</span></h1><!--]--><!----> <p>Diffusers 功能可在 <a href="https://aws.amazon.com/ec2/instance-types/inf2/" rel="nofollow">AWS Inf2 实例</a>上使用，这些是由 <a href="https://aws.amazon.com/machine-learning/inferentia/" rel="nofollow">Neuron 机器学习加速器</a>驱动的 EC2 实例。这些实例旨在提供更好的计算性能（更高的吞吐量、更低的延迟）和良好的成本效益，使其成为 AWS 用户将扩散模型部署到生产环境的良好选择。</p> <p><a href="https://huggingface.co/docs/optimum-neuron/en/index" rel="nofollow">Optimum Neuron</a> 是 Hugging Face 库与 AWS 加速器之间的接口，包括 AWS <a href="https://aws.amazon.com/machine-learning/trainium/" rel="nofollow">Trainium</a> 和 AWS <a href="https://aws.amazon.com/machine-learning/inferentia/" rel="nofollow">Inferentia</a>。它支持 Diffusers 中的许多功能，并具有类似的 API，因此如果您已经熟悉 Diffusers，学习起来更容易。一旦您创建了 AWS Inf2 实例，请安装 Optimum Neuron。</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600  " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copied</div><!----></button><!----></div> <pre class="language-bash "><!---->python -m pip install --upgrade-strategy eager optimum[neuronx]<!----></pre></div><!----> <blockquote class="tip"><p>我们提供预构建的 <a href="https://aws.amazon.com/marketplace/pp/prodview-gr3e6yiscria2" rel="nofollow">Hugging Face Neuron 深度学习 AMI</a>（DLAMI）和用于 Amazon SageMaker 的 Optimum Neuron 容器。建议正确设置您的环境。</p></blockquote> <p>下面的示例演示了如何在 inf2.8xlarge 实例上使用 Stable Diffusion XL 模型生成图像（一旦模型编译完成，您可以切换到更便宜的 inf2.xlarge 实例）。要生成一些图像，请使用 <code>NeuronStableDiffusionXLPipeline</code> 类，该类类似于 Diffusers 中的 <code>StableDiffusionXLPipeline</code> 类。</p> <p>与 Diffusers 不同，您需要将管道中的模型编译为 Neuron 格式，即 <code>.neuron</code>。运行以下命令将模型导出为 <code>.neuron</code> 格式。</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600  " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copied</div><!----></button><!----></div> <pre class="language-bash "><!---->optimum-cli <span class="hljs-built_in">export</span> neuron --model stabilityai/stable-diffusion-xl-base-1.0 \
  --batch_size 1 \
  --height 1024 `# 生成图像的高度（像素），例如 768, 1024` \
  --width 1024 `# 生成图像的宽度（像素），例如 768, 1024` \
  --num_images_per_prompt 1 `# 每个提示生成的图像数量，默认为 1` \
  --auto_cast matmul `# 仅转换矩阵乘法操作` \
  --auto_cast_type bf16 `# 将操作从 FP32 转换为 BF16` \
  sd_neuron_xl/<!----></pre></div><!----> <p>现在使用预编译的 SDXL 模型生成一些图像。</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600  " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copied</div><!----></button><!----></div> <pre class="language-python "><!----><span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> Neu
ronStableDiffusionXLPipeline

<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;a pig with wings flying in floating US dollar banknotes in the air, skyscrapers behind, warm 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>]<!----></pre></div><!----> <img src="https://huggingface.co/datasets/Jingya/document_images/resolve/main/optimum/neuron/sdxl_pig.png" width="256" height="256" alt="peggy generated by sdxl on inf2"/> <p>欢迎查看Optimum Neuron <a href="https://huggingface.co/docs/optimum-neuron/en/inference_tutorials/stable_diffusion#generate-images-with-stable-diffusion-models-on-aws-inferentia" rel="nofollow">文档</a>中更多不同用例的指南和示例！</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/diffusers/blob/main/docs/source/zh/optimization/neuron.md" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg><!----> <span><span class="underline">Update</span> on GitHub</span></a><!----> <p></p><!--]--><!----><!--]--><!--]--><!--]--> <!--[-1--><!--]--><!--]-->
			
			<script>
				{
					__sveltekit_1mjeex = {
						base: "/docs/diffusers/main/zh",
						assets: "/docs/diffusers/main/zh"
					};

					const element = document.currentScript.parentElement;

					Promise.all([
						import("/docs/diffusers/main/zh/_app/immutable/entry/start.BjXnKLdN.js"),
						import("/docs/diffusers/main/zh/_app/immutable/entry/app.C861NjaH.js")
					]).then(([kit, app]) => {
						kit.start(app, element, {
							node_ids: [0, 28],
							data: [null,null],
							form: null,
							error: null
						});
					});
				}
			</script>