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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="tensor-parallelism" 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="#tensor-parallelism"><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><!---->Tensor paralelliği<!----></span></h1><!--]--><!----> <p><a href="https://huggingface.co/spaces/nanotron/ultrascale-playbook?section=tensor_parallelism" rel="nofollow">Tensor parallelism</a>, bir modelin ağırlık matrislerini cihazlar arasında parçalar. Her cihaz, her katman için sütun bazlı (<code>"colwise"</code>) veya satır bazlı (<code>"rowwise"</code>) bir dilim tutar ve kısmi bir sonuç hesaplar. Katman sınırındaki bir <code>AllReduce</code> veya <code>AllGather</code>, kısmi sonuçları birleştirerek tam çıktıyı oluşturur. <a href="./context_parallelism">context parallelism</a>'den farklı olarak, cihaz başına <em>weight</em> belleğini azaltır; bu da bir modelin tek bir cihaza sığmadığı durumlarda işe yarar. Diğer stratejilerle karşılaştırmak için <a href="../training/distributed_inference">Distributed inference</a> bölümüne bakın.</p> <!--[1--><h2 class="relative group"><a id="load-a-sharded-model" 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="#load-a-sharded-model"><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><!---->Parçalı bir model yükleyin<!----></span></h2><!--]--><!----> <p>Modelin <a href="/docs/diffusers/v0.43.0/tr/api/models/overview#diffusers.ModelMixin.from_pretrained">from_pretrained()</a> metodunun <code>parallel_config</code> argümanına bir <a href="/docs/diffusers/v0.43.0/tr/api/parallel#diffusers.TensorParallelConfig">TensorParallelConfig</a> geçirin. <code>tp_degree</code>, parçalanacak cihaz sayısıdır ve modelin dikkat başlıklarının sayısına tam bölünmelidir. Modelin sınıfı, modül adlarını bir parçalama stiline eşleyen bir <code>_tp_plan</code> tanımlamalıdır. Bir modelin tensör paralelliğini destekleyip desteklemediğini kontrol etmek için, <a href="/docs/diffusers/v0.43.0/tr/api/models/flux2_transformer#diffusers.Flux2Transformer2DModel">Flux2Transformer2DModel</a> gibi, sınıfında bu özniteliği arayın.</p> <p>Başka bir modele plan eklemek için <a href="#add-tensor-parallelism-to-a-model">Bir modele tensör paralelliği ekleme</a> bölümüne bakın.</p> <p>Bu yöntemle yüklenirken, kontrol noktası okunurken parçalara ayrılır. Her rank, her ağırlığın yalnızca kendi dilimini okur ve doğrudan kendi GPU'suna yerleştirir; böylece hiçbir rank tam boyutlu bir ağırlık tutmaz. Rank başına bellek, <code>tp_degree</code> arttıkça azalır.</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> Kopyalandı</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> os
<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> torch <span class="hljs-keyword">import</span> distributed <span class="hljs-keyword">as</span> dist
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline, Flux2Transformer2DModel, TensorParallelConfig
<span class="hljs-keyword">def</span> <span class="hljs-title function_">main</span>():
dist.init_process_group(backend=<span class="hljs-string">&quot;nccl&quot;</span>)
rank, world_size = dist.get_rank(), dist.get_world_size()
<span class="hljs-comment"># torchrun sets LOCAL_RANK to this process&#x27;s GPU index on its node</span>
local_rank = <span class="hljs-built_in">int</span>(os.environ[<span class="hljs-string">&quot;LOCAL_RANK&quot;</span>])
device = torch.device(<span class="hljs-string">f&quot;cuda:<span class="hljs-subst">{local_rank}</span>&quot;</span>)
torch.cuda.set_device(device)
<span class="hljs-comment"># Each rank reads only its own shard of every planned weight, straight onto its own GPU.</span>
transformer = Flux2Transformer2DModel.from_pretrained(
<span class="hljs-string">&quot;black-forest-labs/FLUX.2-dev&quot;</span>,
subfolder=<span class="hljs-string">&quot;transformer&quot;</span>,
dtype=torch.bfloat16,
parallel_config=TensorParallelConfig(tp_degree=world_size),
)
pipeline = DiffusionPipeline.from_pretrained(
<span class="hljs-string">&quot;black-forest-labs/FLUX.2-dev&quot;</span>, transformer=transformer, dtype=torch.bfloat16
)
<span class="hljs-comment"># The transformer is already on its device; move the remaining components individually. Do not call</span>
<span class="hljs-comment"># `pipeline.to(device)` — that would move every rank&#x27;s shards onto the same device.</span>
pipeline.text_encoder.to(device)
pipeline.vae.to(device)
generator = torch.Generator().manual_seed(<span class="hljs-number">42</span>)
image = pipeline(prompt=<span class="hljs-string">&quot;a cat holding a sign that says hello&quot;</span>, generator=generator).images[<span class="hljs-number">0</span>]
<span class="hljs-keyword">if</span> rank == <span class="hljs-number">0</span>:
image.save(<span class="hljs-string">&quot;output.png&quot;</span>)
dist.destroy_process_group()
<span class="hljs-keyword">if</span> __name__ == <span class="hljs-string">&quot;__main__&quot;</span>:
main()<!----></pre></div><!----> <p>Betik dosyasını <code>tensor_parallel_flux2.py</code> olarak kaydedin ve <code>torchrun</code> ile başlatın.</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> Kopyalandı</div><!----></button><!----></div> <pre class="language-shell "><!---->torchrun --nproc-per-node 4 tensor_parallel_flux2.py<!----></pre></div><!----> <p>Betik, <code>tp_degree</code> değerini <code>world_size</code> olarak ayarladığından, <code>--nproc-per-node 4</code> komutu dönüştürücüyü 4 GPU arasında paylaştırır.</p> <p>Sadece transformer parçalanır. Her rank, metin kodlayıcısının tam bir kopyasını tutar; bu nedenle her GPU'nun, metin kodlayıcı ile transformer'ın kendine düşen payı için yeterli belleğe sahip olması gerekir.</p> <!--[1--><h2 class="relative group"><a id="loading-performance" 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="#loading-performance"><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><!---->Yükleme performansı<!----></span></h2><!--]--><!----> <p><code>parallel_config</code> ile yükleme, tam modeli yükleyip ardından <code>enable_parallelism()</code> çağrılmasından daha hızlıdır ve rank başına daha az CPU belleği kullanır. Aşağıdaki tablo, 4x A10G (23GB) üzerinde <a href="https://huggingface.co/black-forest-labs/FLUX.2-dev" rel="nofollow">black-forest-labs/FLUX.2-dev</a> (yalnızca transformer, 32B parametre, bf16) için sonuçları göstermektedir.</p> <table><thead><tr><th>tp_degree</th><th>yöntem</th><th>yüklenme süresi</th><th>zirve CPU/rank</th></tr></thead><tbody><tr><td>4</td><td><code>from_pretrained(parallel_config=...)</code></td><td>12.5s</td><td>6,8 GB</td></tr><tr><td>4</td><td><code>from_pretrained</code> + <code>enable_parallelism</code></td><td>30.4s</td><td>64,1 GB</td></tr></tbody></table> <!--[1--><h2 class="relative group"><a id="limitations" 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="#limitations"><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><!---->Kısıtlamalar<!----></span></h2><!--]--><!----> <p>Tensor parallelism, bazı yükleme seçenekleri ve özelliklerle çalışmaz ve bölünmüş bir modeli kaydedemezsiniz.</p> <ul><li><code>parallel_config</code> ile tensor-parallel yükleme, <code>device_map</code>, <code>quantization_config</code>, <code>low_cpu_mem_usage=False</code>, <code>use_flashpack=True</code> veya safetensors olmayan ağırlıklarla çalışmaz. Bunların her biri, tam checkpoint'i sessizce yüklemek yerine bir hata fırlatır.</li> <li>Gergilik paralelliğinin, modelin nasıl bölündüğüne bakılmaksızın, kuantizasyon, offloading veya LoRA adaptörleriyle birleştirilmesi de bir hata oluşturur.</li> <li>Bellekte zaten bulunan bir modeli parçalamak için aynı yapılandırmayla <code>enable_parallelism()</code> çağrılır. Bu yöntem önce tam modeli yükler ve ardından parçalar; bu nedenle her rank, tam checkpoint için bellek gerektirir. Bu maliyeti önlemek için yükleme sırasında <code>parallel_config</code> kullanılır.</li> <li>Tensor-parallel bir modelin kaydedilmesi <a href="/docs/diffusers/v0.43.0/tr/api/models/overview#diffusers.ModelMixin.save_pretrained">save_pretrained()</a> içinde bir hata oluşturur. Modeli parçalara ayırmadan önce kaydedin.</li></ul> <!--[1--><h2 class="relative group"><a id="add-tensor-parallelism-to-a-model" 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="#add-tensor-parallelism-to-a-model"><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><!---->Bir modele tensör paralelliği ekleyin<!----></span></h2><!--]--><!----> <p>Bu bölüm, bir Diffusers modeline tensör paralelliği desteği eklemek isteyen katkıda bulunanlar içindir.</p> <p>Tensor paralelliği, yalnızca modül adlarını bir parçalama stiline eşleyen <code>_tp_plan</code> sınıf özniteliğini tanımlayan modellerde çalışır. Bu özniteliği yazmak, çoğunlukla gizli boyutu <em>genişleten</em> her projeksiyonu, onu geri <em>daraltan</em> projeksiyonla eşleştirmek anlamına gelir.</p> <p>Her anahtar en fazla bir <code>*</code> içerebilir ve <code>*</code> işaretinden önceki bölüm bir <a href="https://pytorch.org/docs/stable/generated/torch.nn.ModuleList.html" rel="nofollow"><code>nn.ModuleList</code></a>'ye çözümlenmelidir, böylece bir girdi tüm blokları kapsar. <code>*</code> içermeyen bir anahtar, modelin kendisine uygulanır. Yollar modele göre göreli olarak tanımlanır.</p> <!--[2--><h3 class="relative group"><a id="colwise-and-rowwise" 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="#colwise-and-rowwise"><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><!---->Colwise ve rowwise<!----></span></h3><!--]--><!----> <table><thead><tr><th>Stil</th><th>Parçalar</th><th>Her sıra</th><th>Kullanım alanları</th></tr></thead><tbody><tr><td><code>"colwise"</code></td><td>çıkış özellikleri (<code>weight</code> boyutu 0)</td><td>çıkışın bir dilimini hesaplar</td><td><code>to_q</code>, <code>to_k</code>, <code>to_v</code>, FFN iç projeksiyonu</td></tr><tr><td><code>"rowwise"</code></td><td>girdi özellikleri (<code>weight</code> boyutu 1)</td><td>kısmi bir toplam hesaplar</td><td><code>to_out.0</code>, FFN çıkış projeksiyonu</td></tr><tr><td><code>"rowwise_split_input"</code></td><td>girdi özellikleri (<code>weight</code> boyutu 1)</td><td>kopyalanmış girdinin diliminden kısmi bir toplam hesaplar</td><td>girdisi replike edilmiş, zaman adımları gömme değerini okuyan bir AdaLN modülasyon projeksiyonu gibi bağımsız bir projeksiyon</td></tr></tbody></table> <p><code>"colwise"</code> ve <code>"rowwise"</code> değerlerini her zaman bu sırayla eşleştirin. <code>"colwise"</code> projeksiyonu çıktısını parçalı (sharded) bırakır, ardından gelen <code>"rowwise"</code> projeksiyonu bu parçayı doğrudan tüketir ve blok sınırındaki tek bir <code>AllReduce</code> işlemi sonucu yeniden oluşturur. Bu çiftin başka bir şekilde parçalanması, ortada bir toplama (gather) işlemi zorunlu kılar ve çok daha fazla iletişim gerektirir.</p> <p>Attention'da sütun bazlı Q, K ve V projeksiyonları her rank'a başların bir alt kümesini verir, bu nedenle <code>tp_degree</code> baş sayısına tam bölünmelidir. Encoder-stream kopyaları (<code>add_q_proj</code>, <code>to_add_out</code>, <code>ff_context</code>), image-stream karşılıklarıyla aynı deseni izler.</p> <!--[2--><h3 class="relative group"><a id="fused-projections" 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="#fused-projections"><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><!---->Birleştirilmiş projeksiyonlar<!----></span></h3><!--]--><!----> <p>Tek bir <code>Linear</code>, parçalanan boyut boyunca birden fazla mantıksal tensörü paketlediğinde, düz <code>"colwise"</code>/<code>"rowwise"</code> dilimleri birleştirmenin üzerinden doğrudan geçer ve parçaları hizasız bırakır. Bunun yerine, her paketlenmiş bloğu bağımsız olarak parçalayan <code>PackedColwiseParallel</code>/<code>PackedRowwiseParallel</code> kullanın.</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> Kopyalandı</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-comment"># in src/diffusers/models/transformers/your_model.py</span>
<span class="hljs-keyword">from</span> ...hooks.tensor_parallel <span class="hljs-keyword">import</span> PackedColwiseParallel, PackedRowwiseParallel<!----></pre></div><!----> <p><code>blocks</code>, paketlenmiş boyutu bölen oransal tam sayılardan oluşan bir liste, geçirin. Örneğin, eşit yarımlara sahip bir SwiGLU gate ve up projection için <code>[1, 1]</code> veya <code>mlp_ratio=3</code> ile birleşik Q, K, V, gate ve up projection için <code>[1, 1, 1, 3, 3]</code> kullanın.</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> Kopyalandı</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-string">&quot;transformer_blocks.*.ff.linear_in&quot;</span>: PackedColwiseParallel([<span class="hljs-number">1</span>, <span class="hljs-number">1</span>]),<!----></pre></div><!----> <p>Blok boyutları yalnızca yapılandırmadan biliniyorsa, <code>blocks</code> parametresini atlayın ve mutlak boyutları <code>__init__</code> sırasında <code>Linear</code> üzerinde <code>_tp_packed_col_blocks</code> veya <code>_tp_packed_row_blocks</code> olarak saklayın.</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> Kopyalandı</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-comment"># in the attention module&#x27;s __init__</span>
<span class="hljs-variable language_">self</span>.to_out._tp_packed_row_blocks = [<span class="hljs-variable language_">self</span>.inner_dim, <span class="hljs-variable language_">self</span>.mlp_hidden_dim]<!----></pre></div><!----> <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> Kopyalandı</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-comment"># in the model&#x27;s _tp_plan</span>
<span class="hljs-string">&quot;single_transformer_blocks.*.attn.to_out&quot;</span>: PackedRowwiseParallel(),<!----></pre></div><!----> <p><a href="https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/transformers/transformer_flux2.py" rel="nofollow"><code>transformer_flux2.py</code></a> içindeki plan her iki biçimi de kullanır. Çift akışlı SwiGLU çifti <code>blocks</code> değerini doğrudan iletir. Birleşik tek akışlı QKV ve MLP projeksiyonu, boyutları <code>mlp_ratio</code> ve <code>mlp_mult_factor</code> değerlerine bağlı olduğu için, bu boyutları <code>Flux2ParallelSelfAttention.__init__</code> içindeki <code>Linear</code> nesnesinde saklar.</p> <!--[2--><h3 class="relative group"><a id="what-to-leave-out" 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="#what-to-leave-out"><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><!---->Dışarıda bırakılacaklar<!----></span></h3><!--]--><!----> <p>Plan dışı bırakılan modüller her sırada kopyalanır. Normalizasyon katmanlarını, yama ve metin gömme katmanlarını ile son <code>norm_out</code> ve <code>proj_out</code> katmanlarını dışarıda bırakın. Bunlar küçük olduğu için bunları bölümlere ayırmak az miktarda bellek tasarrufu sağlar ve iletişim yükü ekler. AdaLN modülasyonu (<code>img_mod</code> ve <code>txt_mod</code>) genellikle dışarıda bırakılacak kadar küçüktür. MiniMax-H3’ün <code>adaln_proj.linear</code> gibi büyük olduğunda, <code>"rowwise_split_input"</code> ile bölümlere ayırın.</p> <!--[2--><h3 class="relative group"><a id="constraints-and-verification" 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="#constraints-and-verification"><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><!---->Kısıtlamalar ve doğrulama<!----></span></h3><!--]--><!----> <ul><li><code>tp_degree</code>, <code>config.num_attention_heads</code>'i tam olarak bölmelidir.</li> <li>Her paketlenmiş blok, yalnızca toplamları değil, <em>tek tek</em> <code>tp_degree</code> değerine bölünebilir olmalıdır.</li></ul> <p><a href="/docs/diffusers/v0.43.0/tr/api/models/overview#diffusers.ModelMixin.from_pretrained">from_pretrained()</a> ve <code>enable_parallelism()</code>, herhangi bir ağırlık yüklenmeden veya bölünmeden önce her iki kontrolü de yapar.</p> <p>Yeni bir planı gözle değil, sayısal olarak doğrulayın: sabit bir tohumla tek bir cihazda üretim yapın, ardından tensor paralelliği altında tekrar üretin ve çıktıları karşılaştırın. Yanlış yerleştirilmiş bir <code>"colwise"</code>/<code>"rowwise"</code> genellikle yine de çalışır ve makul görünen ancak yanlış bir görüntü üretir.</p> <blockquote class="tip"><p>Benzer bir mimari için mevcut bir plandan başlayın.</p> <ul><li><a href="https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/transformers/transformer_qwenimage.py" rel="nofollow"><code>transformer_qwenimage.py</code></a> dosyasında füzyonlu projeksiyonlar bulunmadığından, her giriş düz bir <code>"colwise"</code> veya <code>"rowwise"</code> değeridir.</li> <li><a href="https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/transformers/transformer_flux.py" rel="nofollow"><code>transformer_flux.py</code></a> tek bir paketlenmiş satır bazlı projeksiyon ekler.</li> <li><a href="https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/transformers/transformer_flux2.py" rel="nofollow"><code>transformer_flux2.py</code></a> her iki paketli stili de kullanır.</li></ul></blockquote> <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/tensor_parallelism.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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