import{S as Hi,i as Oi,s as qi,e as a,k as f,w as m,t as r,M as Ki,c as i,d as l,m as u,a as o,x as d,h as p,b as c,N as Li,G as t,g as n,y as _,L as er,q as M,o as y,B as w,v as lr}from"../../chunks/vendor-hf-doc-builder.js";import{I as Il}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{C as v}from"../../chunks/CodeBlock-hf-doc-builder.js";function tr(Ca){let C,Rl,I,B,Pe,H,Yt,ze,Bt,$l,O,q,At,St,Nl,K,ee,Ia,Xl,Xe,kt,Yl,le,te,Ra,Bl,R,Le,gt,Gt,se,Qt,Vt,Al,h,Ft,He,Dt,Pt,ae,zt,Lt,ie,Ht,Ot,re,qt,Kt,Sl,kl,gl,$,A,Oe,pe,es,qe,ls,Gl,N,S,Ke,oe,ts,el,ss,Ql,Ye,as,Vl,Be,ll,is,Fl,k,rs,tl,ps,os,Dl,ne,Pl,Ae,ns,zl,ce,Ll,Se,cs,Hl,fe,Ol,g,fs,ue,us,ms,ql,me,Kl,ke,ds,et,de,lt,ge,_s,tt,_e,st,Me,Ms,at,J,ys,ye,ws,hs,we,Us,Js,Ge,Ts,bs,it,E,sl,Es,Ws,he,al,vs,Zs,il,xs,js,rt,Ue,pt,U,Cs,rl,Is,Rs,pl,$s,Ns,ol,Xs,Ys,nl,Bs,As,ot,Je,nt,G,Ss,cl,ks,gs,ct,Te,ft,T,Gs,fl,Qs,Vs,ul,Fs,Ds,ml,Ps,zs,ut,be,Ee,Ls,Hs,mt,Qe,dl,_l,Os,dt,X,Q,Ml,We,qs,yl,Ks,_t,W,wl,ea,la,hl,ta,sa,ve,aa,ia,Mt,Ze,yt,Y,V,Ul,xe,ra,Jl,pa,wt,Ve,oa,ht,je,Ut,F,na,Ce,ca,fa,Jt,Fe,ua,Tt,Z,Tl,bl,ma,da,El,Wl,_a,Ma,vl,Zl,ya,bt,b,wa,xl,ha,Ua,jl,Ja,Ta,Ie,ba,Ea,Et,D,Wa,Re,va,Za,Wt;return H=new Il({}),pe=new Il({}),oe=new Il({}),ne=new v({props:{code:"Z2l0JTIwY2xvbmUlMjBodHRwcyUzQSUyRiUyRmdpdGh1Yi5jb20lMkZodWdnaW5nZmFjZSUyRmRpZmZ1c2VycyUwQWNkJTIwZGlmZnVzZXJzJTBBcGlwJTIwaW5zdGFsbCUyMC1lJTIwLg==",highlighted:`git <span class="hljs-built_in">clone</span> https://github.com/huggingface/diffusers
<span class="hljs-built_in">cd</span> diffusers
pip install -e .`}}),ce=new v({props:{code:"Y2QlMjBleGFtcGxlcyUyRmluc3RydWN0X3BpeDJwaXg=",highlighted:'<span class="hljs-built_in">cd</span> examples/instruct_pix2pix'}}),fe=new v({props:{code:"cGlwJTIwaW5zdGFsbCUyMC1yJTIwcmVxdWlyZW1lbnRzLnR4dA==",highlighted:"pip install -r requirements.txt"}}),me=new v({props:{code:"YWNjZWxlcmF0ZSUyMGNvbmZpZw==",highlighted:"accelerate config"}}),de=new v({props:{code:"YWNjZWxlcmF0ZSUyMGNvbmZpZyUyMGRlZmF1bHQ=",highlighted:"accelerate config default"}}),_e=new v({props:{code:"ZnJvbSUyMGFjY2VsZXJhdGUudXRpbHMlMjBpbXBvcnQlMjB3cml0ZV9iYXNpY19jb25maWclMEElMEF3cml0ZV9iYXNpY19jb25maWcoKQ==",highlighted:`<span class="hljs-keyword">from</span> accelerate.utils <span class="hljs-keyword">import</span> write_basic_config

write_basic_config()`}}),Ue=new v({props:{code:"ZXhwb3J0JTIwTU9ERUxfTkFNRSUzRCUyMnJ1bndheW1sJTJGc3RhYmxlLWRpZmZ1c2lvbi12MS01JTIyJTBBZXhwb3J0JTIwREFUQVNFVF9JRCUzRCUyMmZ1c2luZyUyRmluc3RydWN0cGl4MnBpeC0xMDAwLXNhbXBsZXMlMjI=",highlighted:`<span class="hljs-built_in">export</span> MODEL_NAME=<span class="hljs-string">&quot;runwayml/stable-diffusion-v1-5&quot;</span>
<span class="hljs-built_in">export</span> DATASET_ID=<span class="hljs-string">&quot;fusing/instructpix2pix-1000-samples&quot;</span>`}}),Je=new v({props:{code:"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",highlighted:`accelerate launch --mixed_precision=<span class="hljs-string">&quot;fp16&quot;</span> train_instruct_pix2pix.py \\
    --pretrained_model_name_or_path=<span class="hljs-variable">$MODEL_NAME</span> \\
    --dataset_name=<span class="hljs-variable">$DATASET_ID</span> \\
    --enable_xformers_memory_efficient_attention \\
    --resolution=256 --random_flip \\
    --train_batch_size=4 --gradient_accumulation_steps=4 --gradient_checkpointing \\
    --max_train_steps=15000 \\
    --checkpointing_steps=5000 --checkpoints_total_limit=1 \\
    --learning_rate=5e-05 --max_grad_norm=1 --lr_warmup_steps=0 \\
    --conditioning_dropout_prob=0.05 \\
    --mixed_precision=fp16 \\
    --seed=42 \\
    --push_to_hub`}}),Te=new v({props:{code:"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",highlighted:`accelerate launch --mixed_precision=<span class="hljs-string">&quot;fp16&quot;</span> train_instruct_pix2pix.py \\
    --pretrained_model_name_or_path=<span class="hljs-variable">$MODEL_NAME</span> \\
    --dataset_name=<span class="hljs-variable">$DATASET_ID</span> \\
    --enable_xformers_memory_efficient_attention \\
    --resolution=256 --random_flip \\
    --train_batch_size=4 --gradient_accumulation_steps=4 --gradient_checkpointing \\
    --max_train_steps=15000 \\
    --checkpointing_steps=5000 --checkpoints_total_limit=1 \\
    --learning_rate=5e-05 --max_grad_norm=1 --lr_warmup_steps=0 \\
    --conditioning_dropout_prob=0.05 \\
    --mixed_precision=fp16 \\
    --val_image_url=<span class="hljs-string">&quot;https://hf.co/datasets/diffusers/diffusers-images-docs/resolve/main/mountain.png&quot;</span> \\
    --validation_prompt=<span class="hljs-string">&quot;make the mountains snowy&quot;</span> \\
    --seed=42 \\
    --report_to=wandb \\
    --push_to_hub`}}),We=new Il({}),Ze=new v({props:{code:"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",highlighted:`accelerate launch --mixed_precision=<span class="hljs-string">&quot;fp16&quot;</span> --multi_gpu train_instruct_pix2pix.py \\
 --pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5 \\
 --dataset_name=sayakpaul/instructpix2pix-1000-samples \\
 --use_ema \\
 --enable_xformers_memory_efficient_attention \\
 --resolution=512 --random_flip \\
 --train_batch_size=4 --gradient_accumulation_steps=4 --gradient_checkpointing \\
 --max_train_steps=15000 \\
 --checkpointing_steps=5000 --checkpoints_total_limit=1 \\
 --learning_rate=5e-05 --lr_warmup_steps=0 \\
 --conditioning_dropout_prob=0.05 \\
 --mixed_precision=fp16 \\
 --seed=42 \\
 --push_to_hub`}}),xe=new Il({}),je=new v({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> PIL
<span class="hljs-keyword">import</span> requests
<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionInstructPix2PixPipeline

model_id = <span class="hljs-string">&quot;your_model_id&quot;</span>  <span class="hljs-comment"># &lt;- \uC774\uB97C \uC218\uC815\uD558\uC138\uC694.</span>
pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to(<span class="hljs-string">&quot;cuda&quot;</span>)
generator = torch.Generator(<span class="hljs-string">&quot;cuda&quot;</span>).manual_seed(<span class="hljs-number">0</span>)

url = <span class="hljs-string">&quot;https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/test_pix2pix_4.png&quot;</span>


<span class="hljs-keyword">def</span> <span class="hljs-title function_">download_image</span>(<span class="hljs-params">url</span>):
   image = PIL.Image.<span class="hljs-built_in">open</span>(requests.get(url, stream=<span class="hljs-literal">True</span>).raw)
   image = PIL.ImageOps.exif_transpose(image)
   image = image.convert(<span class="hljs-string">&quot;RGB&quot;</span>)
   <span class="hljs-keyword">return</span> image


image = download_image(url)
prompt = <span class="hljs-string">&quot;wipe out the lake&quot;</span>
num_inference_steps = <span class="hljs-number">20</span>
image_guidance_scale = <span class="hljs-number">1.5</span>
guidance_scale = <span class="hljs-number">10</span>

edited_image = pipe(
   prompt,
   image=image,
   num_inference_steps=num_inference_steps,
   image_guidance_scale=image_guidance_scale,
   guidance_scale=guidance_scale,
   generator=generator,
).images[<span class="hljs-number">0</span>]
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