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Update tutorials/docs-10-using-turing-autodiff/index.qmd
Co-authored-by: Tor Erlend Fjelde <[email protected]>
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tutorials/docs-10-using-turing-autodiff/index.qmd

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As of Turing version v0.30, the global configuration flag for the AD backend has been removed in favour of [`AdTypes.jl`](https://github.com/SciML/ADTypes.jl), allowing users to specify the AD backend for individual samplers independently.
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Users can pass the `adtype` keyword argument to the sampler constructor to select the desired AD backend, with the default being `AutoForwardDiff(; chunksize=0)`.
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For `ForwardDiff`, pass `adtype=AutoForwardDiff(; chunksize)` to the sampler constructor. A `chunksize` of 0 permits the chunk size to be automatically determined. For more information regarding the selection of `chunksize`, please refer to [related section of `ForwardDiff`'s documentation](https://juliadiff.org/ForwardDiff.jl/dev/user/advanced/#Configuring-Chunk-Size).
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For `ForwardDiff`, pass `adtype=AutoForwardDiff(; chunksize)` to the sampler constructor. A `chunksize` of `nothing` permits the chunk size to be automatically determined. For more information regarding the selection of `chunksize`, please refer to [related section of `ForwardDiff`'s documentation](https://juliadiff.org/ForwardDiff.jl/dev/user/advanced/#Configuring-Chunk-Size).
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For `ReverseDiff`, pass `adtype=AutoReverseDiff()` to the sampler constructor. An additional keyword argument called `compile` can be provided to `AutoReverseDiff`. It specifies whether to pre-record the tape only once and reuse it later (`compile` is set to `false` by default, which means no pre-recording). This can substantially improve performance, but risks silently incorrect results if not used with care.
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