Changelog of @hackage/ad 4.5.6

4.5.6 [2024.05.01]

• Add specialized implementations of log1p, expm1, log1pexp, and log1mexp in Floating instances.

4.5.5 [2024.01.28]

• Numeric.AD.Mode.Reverse.Double now handles IEEE floating-point special values (e.g., NaN and Inf) correctly when ad is compiled with +ffi. Note that this increase in floating-point accuracy may come at a slight performance penalty in certain applications. If this negatively impacts your application, please mention this at https://github.com/ekmett/ad/issues/106.

4.5.4 [2023.02.19]

• Add a Num (Scalar (Scalar t)) constraint to On's Mode instance, which is required to make it typecheck with GHC 9.6.

  (Note that this constraint was already present implicitly due to superclass expansion, so this is not a breaking change. The only reason that it must be added explicitly with GHC 9.6 or later is due to 9.6 being more conservative with superclass expansion.)

4.5.3 [2023.01.21]

• Support building with GHC 9.6.

4.5.2 [2022.06.17]

• Fix a bug that would cause Numeric.AD.Mode.Reverse.diff and Numeric.AD.Mode.Reverse.Double.diff to compute different answers under certain circumstances when ad was compiled with the +ffi flag.

4.5.1 [2022.05.18]

• Allow building with transformers-0.6.*.

4.5 [2021.11.07]

• The build-type has been changed from Custom to Simple. To achieve this, the doctests test suite has been removed in favor of using cabal-docspec to run the doctests.
• Expose Dense mode AD again.
• Add a Dense.Representable mode, which is a variant of Dense that exploits Representable functors rather than Traversable functors.
• Representable can now also be useful as it can allow us to unjet to convert a value of type Jet f a safely back into Cofree f a.
• Improve Reverse.Double mode performance by increasing strictness and using an FFI-based tape.
• Reverse mode AD uses reifyTypeable internally. This means the region parameter/infinitesimals that mark each tape are Typeable, allowing you to do things like define instances of Exception that name the region parameter and perform similar shenanigans.
• Drastically reduce code duplication in Double-based modes, enabling more of them.
• Fixed a number of modes that were handling (**) improperly due to the aforementioned code duplication problem.
• Add a Tower.Double mode (internally) that uses lazy lists of strict doubles.
• Add a Kahn.Double mode (internally) that holds strict doubles in the graph.
• Switch to using pattern synonyms internally for detecting "known" zeros.
• Drop support for versions of GHC before 8.0
• The .Double modes have been modified to exploit the fact that we can definitely check a Double for equality with 0. In future releases we may require a typeclass that offers the ability to check for known zeroes for all types you process. This will allow us to improve the quality of the results, but may require you to either write an small instance declaration if you are processing some esoteric data type of your own, or put on/off a newtype that indicates to skip known zero optimizations or to use Eq. If there are particularly common types with tricky cases, a future ad-instances package might be the right way forward for them to find a home.
• Add Numeric.AD.Double, which tries to mix and match between all the different AD modes to produce optimal results but uses the various .Double specializations to reduce the amount of boxing and indirection on the heap.
• Add Numeric.AD.Halley.Double.
• Removed the fooNoEq variants from Newton.Double, Doubles always have an Eq instance.

4.4.1 [2020.10.13]

• Change the fixity of :- in Numeric.AD.Jet to be right-associative. Previously, it was infixl, which made things like x :- y :- z nearly unusable.
• Fix backpropagation error in Kahn mode.
• Fix bugs in the Erf instance for ForwardDouble.
• Add Numeric.AD.Mode.Reverse.Double, a variant of Numeric.AD.Mode.Reverse that is specialized to Double.
• Re-export Jet(..), headJet, tailJet and jet from Numeric.AD.

4.4 [2020.02.03]

• Generalize the type of stochasticGradientDescent:

  -stochasticGradientDescent :: (Traversable f, Fractional a, Ord a) => (forall s. Reifies s Tape => f (Scalar a) -> f (Reverse s a) -> Reverse s a) -> [f (Scalar a)] -> f a -> [f a]
  +stochasticGradientDescent :: (Traversable f, Fractional a, Ord a) => (forall s. Reifies s Tape => e            -> f (Reverse s a) -> Reverse s a) -> [e]            -> f a -> [f a]
  

4.3.6 [2019.02.28]

• Make the test suite pass when built against musl libc.

4.3.5 [2018.01.18]

• Add Semigroup instance for Id.

4.3.4

• Support doctest-0.12

4.3.3

• Revamp Setup.hs to use cabal-doctest. This makes it build with Cabal-2.0, and makes the doctests work with cabal new-build and sandboxes.

4.3.2.1

• GHC 8 support
• Fix Kahn mode's ** implementation
• Fix multiple problems in Erf and InvErf methods

4.3.2

• Added NoEq versions of several combinators that can be used when Eq isn't available on the numeric type involved.

4.3.1

• Further improvements have been made in the performance of Sparse mode, at least asymptotically, when used on functions with many variables. Since this is the target use-case for Sparse in the first place, this seems like a good trade-off. Note: this results in an API change, but only in the API of an Internal module, so this is treated as a minor version bump.

4.3

• Made drastic improvements in the performance of Tower and Sparse modes thanks to the help of Björn von Sydow.
• Added constrained convex optimization.
• Incorporated some suggestions from herbie for improving floating point accuracy.

4.2.4

• Added Newton.Double modules for performance.

4.2.3

• reflection 2 support

4.2.2

• Major bug fix for grads, jacobians, and anything that uses Sparse mode in Numeric.AD. Derivatives after the first two were previously incorrect.

4.2.1.1

• Support nats version 1

4.2.1

• Added stochasticGradientDescent.

4.2

• Removed broken Directed mode.
• Added Numeric.AD.Rank1 combinators and moved most infinitesimal handling back out of the modes and into an AD wrapper.

4.1

• Fixed a bug in the type of conjugateGradientAscent and conjugateGradientDescent that prevent users from being able to ever call it.

4.0.0.1

• Added the missing instances.h header file to extra-source-files.

4.0

• An overhaul permitting monomorphic modes was completed by @alang9.
• Add a ForwardDouble monomorphic mode

3.4

• Added support for erf and inverf, etc. from Data.Number.Erf.
• Split the infinitesimal and mode into two separate parameters to facilitate inlining and easier extension of the API.

3.3.1

• Build system improvements
• Removed unused LANGUAGE pragmas
• Added HLint configuration
• We now use exactly the same versions of the packages used to build ad when running the doctests.

3.3

• Renamed Reverse to Kahn and Wengert to Reverse. We use Arthur Kahn's topological sorting algorithm to sort the tape after the fact in Kahn mode, while the stock Reverse mode builds a Wengert list as it goes, which is more efficient in practice.

3.2.2

• Export of the conjugateGradientDescent and gradientDescent from Numeric.AD

3.2.1

• conjugateGradientDescent now stops before it starts returning NaN results.

3.2

• Renamed Chain to Wengert to reflect its use of Wengert lists for reverse mode.
• Renamed lift to auto to avoid conflict with the more prevalent transformers library.
• Fixed a bug in Numeric.AD.Forward.gradWith', which caused it to return the wrong value for the primal.

3.1.4

• Added a better "convergence" test for findZero
• Compute tan and tanh derivatives directly.

3.1.3

• Added conjugateGradientDescent and conjugateGradientAscent to Numeric.AD.Newton.

3.1.2

• Dependency bump

3.1

• Added Chain mode, which is Reverse using a linear tape that doesn't need to be sorted.
• Added a suite of doctests.
• Bug fix in Forward mode. It was previously yielding incorrect results for anything that used bind or bind' internally.

3.0

• Moved the contents of Numeric.AD.Mode.Mixed into Numeric.AD
• Split off Numeric.AD.Variadic for the variadic combinators
• Removed the UU, FU, UF, and FF type aliases.
• Stopped exporting the types for Mode and AD from almost every module. Import Numeric.AD.Types if necessary.
• Renamed Tensors to Jet
• Dependency bump to be compatible with ghc 7.4.1 and mtl 2.1
• More aggressive zero tracking.
• diff (**n) 0 for constant n and diff (0**) both now yield the correct answer for all modes.