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ai-agent-book 精选快照(<2MB 代码与文档,来自 github.com/bojieli/ai-agent-book)
2026-08-20 13:12:50 +00:00

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<p class="kicker">05 &middot; METHOD</p>
<h1>Anatomy of the Building Blocks</h1>
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<p class="ct">Multi-Head Attention</p>
<p class="cd">h = 8 parallel heads; d_k = d_v = d_model/h = 64, so total compute stays close to single-head attention at full dimension.</p>
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<p class="ct">Position-wise Feed-Forward</p>
<p class="cd">FFN(x) = max(0, xW&#x2081;+b&#x2081;)W&#x2082;+b&#x2082;, applied identically to every position; inner dimension d_ff = 2048.</p>
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<p class="ct">Add &amp; Norm</p>
<p class="cd">Residual connection around each sub-layer: LayerNorm(x + Sublayer(x)); all sub-layers and embeddings output d_model = 512.</p>
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<p class="ct">Positional Encoding</p>
<p class="cd">Sine/cosine waves of different frequencies injected at the inputs, so the model can use token order; learned alternatives worked equally well.</p>
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<p><b>Two configurations:</b> base &mdash; d_model 512, d_ff 2048, h 8, dropout 0.1 &nbsp;|&nbsp; big &mdash; d_model 1024, d_ff 4096, h 16, dropout 0.3.</p>
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<p class="foot">Source: &sect;3.2&ndash;3.5 (paper p. 4&ndash;5); &sect;5.4 and Table 3 footnotes (paper p. 7&ndash;8).</p>
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