<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Neural Network Architecture on 中文AI术语词典</title><link>https://terms-en.ai-term-hub.com/zh/tags/neural-network-architecture/</link><description>Recent content in Neural Network Architecture on 中文AI术语词典</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Sat, 18 Jul 2026 11:44:45 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/zh/tags/neural-network-architecture/index.xml" rel="self" type="application/rss+xml"/><item><title>Encoder</title><link>https://terms-en.ai-term-hub.com/zh/terms/encoder/</link><pubDate>Sat, 18 Jul 2026 10:59:51 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/zh/terms/encoder/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>编码器处理原始输入序列或数据结构，并将它们转换为潜在空间表示，通常称为嵌入或代码。它们是 Transformer 和自编码器等架构的核心部分。&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>编码器是神经网络的组件，它将输入数据转换为压缩的、有意义的表示形式。&lt;/p>
&lt;h2 id="key-concepts">Key Concepts&lt;/h2>
&lt;ul>
&lt;li>特征提取&lt;/li>
&lt;li>潜在空间&lt;/li>
&lt;li>序列处理&lt;/li>
&lt;li>压缩&lt;/li>
&lt;/ul>
&lt;h2 id="use-cases">Use Cases&lt;/h2>
&lt;ul>
&lt;li>在 Transformer 模型中处理输入文本&lt;/li>
&lt;li>在去噪自编码器中压缩图像&lt;/li>
&lt;li>从评论中提取情感特征&lt;/li>
&lt;/ul>
&lt;h2 id="code-example">Code Example&lt;/h2>
&lt;div class="highlight">&lt;pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;">&lt;code class="language-python" data-lang="python">&lt;span style="display:flex;">&lt;span>&lt;span style="color:#f92672">import&lt;/span> torch.nn &lt;span style="color:#66d9ef">as&lt;/span> nn
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span>
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span>&lt;span style="color:#66d9ef">class&lt;/span> &lt;span style="color:#a6e22e">SimpleEncoder&lt;/span>(nn&lt;span style="color:#f92672">.&lt;/span>Module):
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span> &lt;span style="color:#66d9ef">def&lt;/span> __init__(self, input_dim, hidden_dim):
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span> super()&lt;span style="color:#f92672">.&lt;/span>__init__()
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span> self&lt;span style="color:#f92672">.&lt;/span>fc &lt;span style="color:#f92672">=&lt;/span> nn&lt;span style="color:#f92672">.&lt;/span>Linear(input_dim, hidden_dim)
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span> 
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span> &lt;span style="color:#66d9ef">def&lt;/span> &lt;span style="color:#a6e22e">forward&lt;/span>(self, x):
&lt;/span>&lt;/span>&lt;span style="display:flex;">&lt;span> &lt;span style="color:#66d9ef">return&lt;/span> torch&lt;span style="color:#f92672">.&lt;/span>relu(self&lt;span style="color:#f92672">.&lt;/span>fc(x))
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/div>&lt;h2 id="related-terms">Related Terms&lt;/h2>
&lt;ul>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/decoder-%E8%A7%A3%E7%A0%81%E5%99%A8/">Decoder (解码器)&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/transformer-%E8%BD%AC%E6%8D%A2%E5%99%A8%E6%9E%B6%E6%9E%84/">Transformer (转换器架构)&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/autoencoder-%E8%87%AA%E7%BC%96%E7%A0%81%E5%99%A8/">Autoencoder (自编码器)&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/latent-variable-%E6%BD%9C%E5%8F%98%E9%87%8F/">Latent Variable (潜变量)&lt;/a>&lt;/li>
&lt;/ul></description></item></channel></rss>