import{s as ct,o as ot,n as tt}from"../chunks/scheduler.5c93273d.js";import{S as wt,i as Jt,g as J,s as c,r as y,A as ft,h as f,f as s,c as o,j as it,u,x as m,k as rt,y as mt,a as p,v as h,d as U,t as j,w as I}from"../chunks/index.e43dd92b.js";import{C as x}from"../chunks/CodeBlock.6896320e.js";import{H as Tt,E as yt}from"../chunks/getInferenceSnippets.7a494bf3.js";import{H as ut,a as O}from"../chunks/HfOption.d50154c3.js";function ht(b){let l,w="使用 T-GATE 加速 <code>PixArtAlphaPipeline</code>：",i,a,d;return a=new x({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> PixArtAlphaPipeline
<span class="hljs-keyword">from</span> tgate <span class="hljs-keyword">import</span> TgatePixArtLoader

pipe = PixArtAlphaPipeline.from_pretrained(<span class="hljs-string">&quot;PixArt-alpha/PixArt-XL-2-1024-MS&quot;</span>, torch_dtype=torch.float16)

gate_step = <span class="hljs-number">8</span>
inference_step = <span class="hljs-number">25</span>
pipe = TgatePixArtLoader(
       pipe,
       gate_step=gate_step,
       num_inference_steps=inference_step,
).to(<span class="hljs-string">&quot;cuda&quot;</span>)

image = pipe.tgate(
       <span class="hljs-string">&quot;An alpaca made of colorful building blocks, cyberpunk.&quot;</span>,
       gate_step=gate_step,
       num_inference_steps=inference_step,
).images[<span class="hljs-number">0</span>]`,wrap:!1}}),{c(){l=J("p"),l.innerHTML=w,i=c(),y(a.$$.fragment)},l(e){l=f(e,"P",{"data-svelte-h":!0}),m(l)!=="svelte-4mgysz"&&(l.innerHTML=w),i=o(e),u(a.$$.fragment,e)},m(e,r){p(e,l,r),p(e,i,r),h(a,e,r),d=!0},p:tt,i(e){d||(U(a.$$.fragment,e),d=!0)},o(e){j(a.$$.fragment,e),d=!1},d(e){e&&(s(l),s(i)),I(a,e)}}}function Ut(b){let l,w="使用 T-GATE 加速 <code>StableDiffusionXLPipeline</code>：",i,a,d;return a=new x({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionXLPipeline
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DPMSolverMultistepScheduler
<span class="hljs-keyword">from</span> tgate <span class="hljs-keyword">import</span> TgateSDXLLoader

pipe = StableDiffusionXLPipeline.from_pretrained(
            <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>,
            torch_dtype=torch.float16,
            variant=<span class="hljs-string">&quot;fp16&quot;</span>,
            use_safetensors=<span class="hljs-literal">True</span>,
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

gate_step = <span class="hljs-number">10</span>
inference_step = <span class="hljs-number">25</span>
pipe = TgateSDXLLoader(
       pipe,
       gate_step=gate_step,
       num_inference_steps=inference_step,
).to(<span class="hljs-string">&quot;cuda&quot;</span>)

image = pipe.tgate(
       <span class="hljs-string">&quot;Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.&quot;</span>,
       gate_step=gate_step,
       num_inference_steps=inference_step
).images[<span class="hljs-number">0</span>]`,wrap:!1}}),{c(){l=J("p"),l.innerHTML=w,i=c(),y(a.$$.fragment)},l(e){l=f(e,"P",{"data-svelte-h":!0}),m(l)!=="svelte-1r8lruj"&&(l.innerHTML=w),i=o(e),u(a.$$.fragment,e)},m(e,r){p(e,l,r),p(e,i,r),h(a,e,r),d=!0},p:tt,i(e){d||(U(a.$$.fragment,e),d=!0)},o(e){j(a.$$.fragment,e),d=!1},d(e){e&&(s(l),s(i)),I(a,e)}}}function jt(b){let l,w=`使用 [DeepCache](<a href="https://github.co" rel="nofollow">https://github.co</a> 加速 <code>StableDiffusionXLPipeline</code>
m/horseee/DeepCache) 和 T-GATE：`,i,a,d;return a=new x({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionXLPipeline
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DPMSolverMultistepScheduler
<span class="hljs-keyword">from</span> tgate <span class="hljs-keyword">import</span> TgateSDXLDeepCacheLoader

pipe = StableDiffusionXLPipeline.from_pretrained(
            <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>,
            torch_dtype=torch.float16,
            variant=<span class="hljs-string">&quot;fp16&quot;</span>,
            use_safetensors=<span class="hljs-literal">True</span>,
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

gate_step = <span class="hljs-number">10</span>
inference_step = <span class="hljs-number">25</span>
pipe = TgateSDXLDeepCacheLoader(
       pipe,
       cache_interval=<span class="hljs-number">3</span>,
       cache_branch_id=<span class="hljs-number">0</span>,
).to(<span class="hljs-string">&quot;cuda&quot;</span>)

image = pipe.tgate(
       <span class="hljs-string">&quot;Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.&quot;</span>,
       gate_step=gate_step,
       num_inference_steps=inference_step
).images[<span class="hljs-number">0</span>]`,wrap:!1}}),{c(){l=J("p"),l.innerHTML=w,i=c(),y(a.$$.fragment)},l(e){l=f(e,"P",{"data-svelte-h":!0}),m(l)!=="svelte-h6fosh"&&(l.innerHTML=w),i=o(e),u(a.$$.fragment,e)},m(e,r){p(e,l,r),p(e,i,r),h(a,e,r),d=!0},p:tt,i(e){d||(U(a.$$.fragment,e),d=!0)},o(e){j(a.$$.fragment,e),d=!1},d(e){e&&(s(l),s(i)),I(a,e)}}}function It(b){let l,w="使用 T-GATE 加速 <code>latent-consistency/lcm-sdxl</code>：",i,a,d;return a=new x({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionXLPipeline
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> UNet2DConditionModel, LCMScheduler
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DPMSolverMultistepScheduler
<span class="hljs-keyword">from</span> tgate <span class="hljs-keyword">import</span> TgateSDXLLoader

unet = UNet2DConditionModel.from_pretrained(
    <span class="hljs-string">&quot;latent-consistency/lcm-sdxl&quot;</span>,
    torch_dtype=torch.float16,
    variant=<span class="hljs-string">&quot;fp16&quot;</span>,
)
pipe = StableDiffusionXLPipeline.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>,
    unet=unet,
    torch_dtype=torch.float16,
    variant=<span class="hljs-string">&quot;fp16&quot;</span>,
)
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)

gate_step = <span class="hljs-number">1</span>
inference_step = <span class="hljs-number">4</span>
pipe = TgateSDXLLoader(
       pipe,
       gate_step=gate_step,
       num_inference_steps=inference_step,
       lcm=<span class="hljs-literal">True</span>
).to(<span class="hljs-string">&quot;cuda&quot;</span>)

image = pipe.tgate(
       <span class="hljs-string">&quot;Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.&quot;</span>,
       gate_step=gate_step,
       num_inference_steps=inference_step
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