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docs/src/API/ad.md

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The choices for the auto-AD fill-ins with quick descriptions are:
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- `AutoForwardDiff()`: The fastest choice for small optimizations
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- `AutoReverseDiff(compile=false)`: A fast choice for large scalar optimizations
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- `AutoTracker()`: Like ReverseDiff but GPU-compatible
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- `AutoZygote()`: The fastest choice for non-mutating array-based (BLAS) functions
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- `AutoFiniteDiff()`: Finite differencing, not optimal but always applicable
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- `AutoModelingToolkit()`: The fastest choice for large scalar optimizations
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- `AutoEnzyme()`: Highly performant AD choice for type stable and optimized code
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- `AutoForwardDiff()`: The fastest choice for small optimizations
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- `AutoReverseDiff(compile=false)`: A fast choice for large scalar optimizations
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- `AutoTracker()`: Like ReverseDiff but GPU-compatible
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- `AutoZygote()`: The fastest choice for non-mutating array-based (BLAS) functions
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- `AutoFiniteDiff()`: Finite differencing, not optimal but always applicable
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- `AutoModelingToolkit()`: The fastest choice for large scalar optimizations
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- `AutoEnzyme()`: Highly performant AD choice for type stable and optimized code
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## Automatic Differentiation Choice API
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docs/src/API/optimization_function.md

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```@docs
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SciMLBase.OptimizationFunction
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```
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```

docs/src/API/optimization_state.md

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```@docs
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Optimization.OptimizationState
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```
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```

docs/src/API/optimization_stats.md

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```@docs
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SciMLBase.OptimizationStats
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```
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```

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