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<h1><a href="https://nn.labml.ai/transformers/aft/index.html">一款无注意的变形金刚</a></h1>
<p>这是 <a href="https://pytorch.org">PyTorch 对</a>《<a href="https://papers.labml.ai/paper/2105.14103">无注意力的变形金刚》一文的</a>实现。</p>
<p>本文用一种新的高效运算取代了<a href="https://nn.labml.ai/transformers/mha.html">自我注意力层</a>，该运算的存储复杂度为O（Td），其中 T 是序列长度，<span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.69444em;vertical-align:0em;"></span><span class="mord mathnormal">d</span></span></span></span></span>是嵌入的维度。</p>
<p>本文介绍了 AFT 以及 AFT-Local 和 AFT-conv。这里我们实现了 aft-Local，它关注自回归模型中的 cloby 代币。</p>
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