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    <title>Torch.compile on Duo&#39;s Tech Blog</title>
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      <title>torch.compile: The Mental Model That Actually Matters</title>
      <link>https://duoan.github.io/posts/torch-compile-from-bytecode-to-triton/</link>
      <pubDate>Sun, 31 May 2026 00:00:00 +0000</pubDate>
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      <description>&lt;h1 id=&#34;torchcompile-the-mental-model-that-actually-matters&#34;&gt;torch.compile: The Mental Model That Actually Matters&lt;/h1&gt;
&lt;p&gt;Most writeups of &lt;code&gt;torch.compile&lt;/code&gt; are either a flag cheat-sheet or a file-by-file museum tour. Neither helps when a training step is only 1.2× faster and you do not know whether to blame graph breaks, recompiles, or Inductor.&lt;/p&gt;
&lt;p&gt;The useful model is simpler: &lt;strong&gt;compile is specialization under recorded assumptions&lt;/strong&gt;. Dynamo captures a region, Inductor emits kernels tuned to that region, and guards decide whether the specialization still applies. Everything else — FX, AOTAutograd, Triton — is machinery in service of that contract.&lt;/p&gt;</description>
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