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| <link href="/docs/diffusers/main/en/_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: inline-end; margin-inline-start: 10px; display: inline-flex; position: relative; z-index: 10;"><div dir="ltr" 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 dir="auto">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="pruna" 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="#pruna"><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><!---->Pruna<!----></span></h1><!--]--><!----> <p><a href="https://github.com/PrunaAI/pruna" rel="nofollow">Pruna</a> هو إطار عمل لتحسين النماذج يقدم طرق تحسين متنوعة - مثل التكميم، والتقليم، والتخزين المؤقت، والتجميع - لتسريع الاستدلال وتقليل استهلاك الذاكرة. تُعرض نظرة عامة على طرق التحسين أدناه.</p> <table><thead><tr><th>تقنية</th><th>الوصف</th><th align="center">السرعة</th><th align="center">الذاكرة</th><th align="center">الجودة</th></tr></thead><tbody><tr><td><code>batcher</code></td><td>تجمع المدخلات المتعددة معًا لمعالجتها في وقت واحد، مما يحسّن الكفاءة الحسابية ويقلل من وقت المعالجة.</td><td align="center">✅</td><td align="center">❌</td><td align="center">➖</td></tr><tr><td><code>cacher</code></td><td>يخزّن النتائج الوسيطة للعمليات الحسابية لتسريع العمليات اللاحقة.</td><td align="center">✅</td><td align="center">➖</td><td align="center">➖</td></tr><tr><td><code>compiler</code></td><td>يُحسّن النموذج باستخدام تعليمات مخصصة للأجهزة المحددة.</td><td align="center">✅</td><td align="center">➖</td><td align="center">➖</td></tr><tr><td><code>distiller</code></td><td>يُدرّب نموذجًا أصغر وأبسط لمحاكاة نموذج أكبر وأكثر تعقيدًا.</td><td align="center">✅</td><td align="center">✅</td><td align="center">❌</td></tr><tr><td><code>quantizer</code></td><td>يقلل من دقة الأوزان والتفعيلات، مما يخفض متطلبات الذاكرة.</td><td align="center">✅</td><td align="center">✅</td><td align="center">❌</td></tr><tr><td><code>pruner</code></td><td>يزيل الاتصالات والعصبونات الأقل أهمية أو المتكررة، مما يؤدي إلى شبكة أكثر ندرة وكفاءة.</td><td align="center">✅</td><td align="center">✅</td><td align="center">❌</td></tr><tr><td><code>recoverer</code></td><td>يعيد أداء النموذج بعد الضغط.</td><td align="center">➖</td><td align="center">➖</td><td align="center">✅</td></tr><tr><td><code>factorizer</code></td><td>يقوم Factorization بدمج عدة عمليات ضرب مصفوفات صغيرة في عملية واحدة كبيرة مدمجة.</td><td align="center">✅</td><td align="center">➖</td><td align="center">➖</td></tr><tr><td><code>enhancer</code></td><td>يعزز مخرجات النموذج من خلال تطبيق خوارزميات ما بعد المعالجة مثل إزالة الضوضاء أو رفع الدقة.</td><td align="center">❌</td><td align="center">-</td><td align="center">✅</td></tr></tbody></table> <p>✅ (يحسّن)، ➖ (نفس الشيء تقريبًا)، ❌ (يُضعف)</p> <p>استكشف مجموعة طرق التحسين الكاملة في <a href="https://docs.pruna.ai/en/stable/docs_pruna/user_manual/configure.html#configure-algorithms" rel="nofollow">توثيق Pruna</a>.</p> <!--[1--><h2 class="relative group"><a id="installation" 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="#installation"><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><!---->التثبيت<!----></span></h2><!--]--><!----> <p>قم بتثبيت Pruna باستخدام الأمر التالي.</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> تم النسخ</div><!----></button><!----></div> <pre class="language-bash "><!---->pip install pruna<!----></pre></div><!----> <!--[1--><h2 class="relative group"><a id="optimize-diffusers-models" 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="#optimize-diffusers-models"><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><!---->تحسين نماذج Diffusers<!----></span></h2><!--]--><!----> <p>تدعم نماذج Diffusers مجموعة واسعة من خوارزميات التحسين كما هو موضح أدناه.</p> <div class="flex justify-center"><img src="https://huggingface.co/datasets/PrunaAI/documentation-images/resolve/main/diffusers/diffusers_combinations.png" alt="Overview of the supported optimization algorithms for diffusers models"/></div> <p>يُحسّن المثال أدناه <a href="https://huggingface.co/black-forest-labs/FLUX.1-dev" rel="nofollow">black-forest-labs/FLUX.1-dev</a> باستخدام مزيج من خوارزميات factorizer وcompiler وcacher. يُسرّع هذا المزيج الاستدلال حتى 4.2 أضعاف ويقلل ذروة استخدام ذاكرة GPU من 34.7GB إلى 28.0GB، مع الحفاظ على جودة المخرجات شبه المتطابقة.</p> <blockquote class="tip"><p>راجع وثائق <a href="https://docs.pruna.ai/en/stable/docs_pruna/user_manual/configure.html" rel="nofollow">تحسين Pruna</a> لمعرفة المزيد حول تقنيات التحسين المستخدمة في هذا المثال.</p></blockquote> <div class="flex justify-center"><img src="https://huggingface.co/datasets/PrunaAI/documentation-images/resolve/main/diffusers/flux_combination.png" alt="Optimization techniques used for FLUX.1-dev showing the combination of factorizer, compiler, and cacher algorithms"/></div> <p>ابدأ بتعريف <code>SmashConfig</code> بخوارزميات التحسين المراد استخدامها. لتحسين النموذج، قم بتغليف خط الأنابيب و<code>SmashConfig</code> باستخدام <code>smash</code> ثم استخدم خط الأنابيب بشكل طبيعي للاستدلال.</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> تم النسخ</div><!----></button><!----></div> <pre class="language-python "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> FluxPipeline | |
| <span class="hljs-keyword">from</span> pruna <span class="hljs-keyword">import</span> PrunaModel, SmashConfig, smash | |
| <span class="hljs-comment"># load the model</span> | |
| <span class="hljs-comment"># Try segmind/Segmind-Vega or black-forest-labs/FLUX.1-schnell with a small GPU memory</span> | |
| pipe = FluxPipeline.from_pretrained( | |
| <span class="hljs-string">"black-forest-labs/FLUX.1-dev"</span>, | |
| dtype=torch.bfloat16 | |
| ).to(<span class="hljs-string">"cuda"</span>) <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| <span class="hljs-comment"># define the configuration</span> | |
| smash_config = SmashConfig() | |
| smash_config[<span class="hljs-string">"factorizer"</span>] = <span class="hljs-string">"qkv_diffusers"</span> | |
| smash_config[<span class="hljs-string">"compiler"</span>] = <span class="hljs-string">"torch_compile"</span> | |
| smash_config[<span class="hljs-string">"torch_compile_target"</span>] = <span class="hljs-string">"module_list"</span> | |
| smash_config[<span class="hljs-string">"cacher"</span>] = <span class="hljs-string">"fora"</span> | |
| smash_config[<span class="hljs-string">"fora_interval"</span>] = <span class="hljs-number">2</span> | |
| <span class="hljs-comment"># for the best results in terms of speed you can add these configs</span> | |
| <span class="hljs-comment"># however they will increase your warmup time from 1.5 min to 10 min</span> | |
| <span class="hljs-comment"># smash_config["torch_compile_mode"] = "max-autotune-no-cudagraphs"</span> | |
| <span class="hljs-comment"># smash_config["quantizer"] = "torchao"</span> | |
| <span class="hljs-comment"># smash_config["torchao_quant_type"] = "fp8dq"</span> | |
| <span class="hljs-comment"># smash_config["torchao_excluded_modules"] = "norm+embedding"</span> | |
| <span class="hljs-comment"># optimize the model</span> | |
| smashed_pipe = smash(pipe, smash_config) | |
| <span class="hljs-comment"># run the model</span> | |
| smashed_pipe(<span class="hljs-string">"a knitted purple prune"</span>).images[<span class="hljs-number">0</span>]<!----></pre></div><!----> <div class="flex justify-center"><img src="https://huggingface.co/datasets/PrunaAI/documentation-images/resolve/main/diffusers/flux_smashed_comparison.png"/></div> <p>بعد التحسين، يمكننا مشاركة النموذج المحسّن وتحميله باستخدام Hugging Face Hub.</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> تم النسخ</div><!----></button><!----></div> <pre class="language-python "><!----><span class="hljs-comment"># save the model</span> | |
| smashed_pipe.save_to_hub(<span class="hljs-string">"<username>/FLUX.1-dev-smashed"</span>) | |
| <span class="hljs-comment"># load the model</span> | |
| smashed_pipe = PrunaModel.from_hub(<span class="hljs-string">"<username>/FLUX.1-dev-smashed"</span>)<!----></pre></div><!----> <!--[1--><h2 class="relative group"><a id="evaluate-and-benchmark-diffusers-models" 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="#evaluate-and-benchmark-diffusers-models"><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><!---->تقييم نماذج Diffusers ومعايرتها<!----></span></h2><!--]--><!----> <p>توفّر Pruna الوكيل <a href="https://docs.pruna.ai/en/stable/docs_pruna/user_manual/evaluate.html" rel="nofollow">EvaluationAgent</a> لتقييم جودة نماذجك المُحسَّنة.</p> <p>يمكننا تحديد المقاييس التي نهتم بها، مثل الوقت الكلي ومعدل الإنتاجية، بالإضافة إلى مجموعة البيانات التي سنقيّم عليها. كما يمكننا تعريف نموذج ومروره إلى <code>EvaluationAgent</code>.</p> <div class="flex space-x-2 items-center my-1.5 mr-8 h-7 !pl-0 -mx-3 md:mx-0"><!--[--><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd border-gray-800 bg-black dark:bg-gray-700 text-white">النموذج المُحسَّن</div><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd text-gray-500 cursor-pointer opacity-90 hover:text-gray-700 dark:hover:text-gray-200 hover:shadow-sm">نموذج مستقل</div><!--]--></div> <div class="language-select"><div><p>يمكننا تحميل نموذج محسّن وتقييمه باستخدام <code>EvaluationAgent</code> ثم تمريره إلى <code>Task</code>.</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> تم النسخ</div><!----></button><!----></div> <pre class="language-python "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> FluxPipeline | |
| <span class="hljs-keyword">from</span> pruna <span class="hljs-keyword">import</span> PrunaModel | |
| <span class="hljs-keyword">from</span> pruna.data.pruna_datamodule <span class="hljs-keyword">import</span> PrunaDataModule | |
| <span class="hljs-keyword">from</span> pruna.evaluation.evaluation_agent <span class="hljs-keyword">import</span> EvaluationAgent | |
| <span class="hljs-keyword">from</span> pruna.evaluation.metrics <span class="hljs-keyword">import</span> ( | |
| ThroughputMetric, | |
| TorchMetricWrapper, | |
| TotalTimeMetric, | |
| ) | |
| <span class="hljs-keyword">from</span> pruna.evaluation.task <span class="hljs-keyword">import</span> Task | |
| <span class="hljs-comment"># define the device</span> | |
| device = <span class="hljs-string">"cuda"</span> <span class="hljs-keyword">if</span> torch.cuda.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">"mps"</span> <span class="hljs-keyword">if</span> torch.backends.mps.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">"cpu"</span> | |
| <span class="hljs-comment"># load the model</span> | |
| <span class="hljs-comment"># Try PrunaAI/Segmind-Vega-smashed or PrunaAI/FLUX.1-dev-smashed with a small GPU memory</span> | |
| smashed_pipe = PrunaModel.from_hub(<span class="hljs-string">"PrunaAI/FLUX.1-dev-smashed"</span>) | |
| <span class="hljs-comment"># Define the metrics</span> | |
| metrics = [ | |
| TotalTimeMetric(n_iterations=<span class="hljs-number">20</span>, n_warmup_iterations=<span class="hljs-number">5</span>), | |
| ThroughputMetric(n_iterations=<span class="hljs-number">20</span>, n_warmup_iterations=<span class="hljs-number">5</span>), | |
| TorchMetricWrapper(<span class="hljs-string">"clip"</span>), | |
| ] | |
| <span class="hljs-comment"># Define the datamodule</span> | |
| datamodule = PrunaDataModule.from_string(<span class="hljs-string">"LAION256"</span>) | |
| datamodule.limit_datasets(<span class="hljs-number">10</span>) | |
| <span class="hljs-comment"># Define the task and evaluation agent</span> | |
| task = Task(metrics, datamodule=datamodule, device=device) | |
| eval_agent = EvaluationAgent(task) | |
| <span class="hljs-comment"># Evaluate smashed model and offload it to CPU</span> | |
| smashed_pipe.move_to_device(device) | |
| smashed_pipe_results = eval_agent.evaluate(smashed_pipe) | |
| smashed_pipe.move_to_device(<span class="hljs-string">"cpu"</span>)<!----></pre></div><!----><!----></div><!----> <div hidden=""><p>بدلاً من مقارنة النموذج المُحسَّن بالنموذج الأساسي، يمكنك أيضًا تقييم نموذج <code>diffusers</code> المستقل. وهذا مفيد إذا كنت ترغب في تقييم أداء النموذج دون التحسين. يمكننا القيام بذلك باستخدام غلاف <code>PrunaModel</code> وتشغيل <code>EvaluationAgent</code> عليه.</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> تم النسخ</div><!----></button><!----></div> <pre class="language-python "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> FluxPipeline | |
| <span class="hljs-keyword">from</span> pruna <span class="hljs-keyword">import</span> PrunaModel | |
| <span class="hljs-comment"># load the model</span> | |
| <span class="hljs-comment"># Try PrunaAI/Segmind-Vega-smashed or PrunaAI/FLUX.1-dev-smashed with a small GPU memory</span> | |
| pipe = FluxPipeline.from_pretrained( | |
| <span class="hljs-string">"black-forest-labs/FLUX.1-dev"</span>, | |
| dtype=torch.bfloat16 | |
| ).to(<span class="hljs-string">"cpu"</span>) | |
| wrapped_pipe = PrunaModel(model=pipe)<!----></pre></div><!----><!----></div><!----><!----></div><!----> <p>الآن وقد اطلعت على كيفية تحسين نماذجك وتقييمها، يمكنك البدء في استخدام Pruna لتحسين نماذجك الخاصة. لحسن الحظ، لدينا العديد من الأمثلة لمساعدتك على البدء.</p> <blockquote class="tip"><p>لمزيد من التفاصيل حول إجراء اختبارات الأداء على Flux، اطّلع على منشور المدونة <a href="https://huggingface.co/blog/PrunaAI/flux-fastest-image-generation-endpoint" rel="nofollow">إعلان FLUX-Juiced: أسرع نقطة نهاية لتوليد الصور (أسرع بـ 2.6 مرة)!</a> ومساحة <a href="https://huggingface.co/spaces/PrunaAI/InferBench" rel="nofollow">InferBench</a>.</p></blockquote> <!--[1--><h2 class="relative group"><a id="reference" 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="#reference"><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><!---->مرجع<!----></span></h2><!--]--><!----> <ul><li><a href="https://github.com/PrunaAI/pruna" rel="nofollow">Pruna</a></li> <li>تحسين <a href="https://docs.pruna.ai/en/stable/docs_pruna/user_manual/configure.html#configure-algorithms" rel="nofollow">Pruna</a></li> <li><a href="https://docs.pruna.ai/en/stable/docs_pruna/user_manual/evaluate.html" rel="nofollow">تقييم Pruna</a></li> <li><a href="https://docs.pruna.ai/en/stable/docs_pruna/tutorials/index.html" rel="nofollow">دروس Pruna</a></li></ul> <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/en/optimization/pruna.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--><!--]--><!--]--> | |
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