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Update docs/source/en/optimization/fp16.md

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Sayak Paul
2025-06-24 14:05:26 +05:30
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@@ -156,7 +156,7 @@ Compilation is slow the first time, but once compiled, it is significantly faste
[Regional compilation](https://docs.pytorch.org/tutorials/recipes/regional_compilation.html) trims cold-start latency by compiling **only the small, frequently-repeated block(s)** of a model, typically a Transformer layer, enabling reuse of compiled artifacts for every subsequent occurrence.
For many diffusion architectures this delivers the *same* runtime speed-ups as full-graph compilation yet cuts compile time by **8–10 ×**.
To make this effortless, `ModelMixin` exposes **`compile_repeated_blocks`** API, a helper that wraps `torch.compile` around any sub-modules you designate as repeatable:
To make this effortless, [`ModelMixin`] exposes [`ModelMixin.compile_repeated_blocks`] API, a helper that wraps `torch.compile` around any sub-modules you designate as repeatable:
```py
# pip install -U diffusers