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 # Hyperoptax: Parallel hyperparameter tuning with JAX
 
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 pip install --upgrade "jax[cpu]"
 # or GPU/TPU – see the official JAX installation guide
 ```
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 ## 🥜 In a nutshell
 
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 All optimizers follow the same stateless pattern: `Optimizer.init` returns a `(state, optimizer)` pair, and `optimizer.optimize` runs the search loop. Your objective function must have the signature `fn(key, params) -> scalar`. Importantly, `params` can be _any_ PyTree.
 
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 ```python
 import jax
 from hyperoptax import BayesianSearch, LogSpace, LinearSpace
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