ad-4.5.6: Automatic Differentiation
Copyright(c) Edward Kmett 2010-2021
LicenseBSD3
Maintainerekmett@gmail.com
Stabilityexperimental
PortabilityGHC only
Safe HaskellSafe-Inferred
LanguageHaskell2010

Numeric.AD.Mode.Kahn

Description

This module provides reverse-mode Automatic Differentiation using post-hoc linear time topological sorting.

For reverse mode AD we use StableName to recover sharing information from the tape to avoid combinatorial explosion, and thus run asymptotically faster than it could without such sharing information, but the use of side-effects contained herein is benign.

Synopsis

Documentation

data AD s a Source #

Instances

Instances details
Mode a => Mode (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Associated Types

type Scalar (AD s a) Source #

Methods

isKnownConstant :: AD s a -> Bool Source #

asKnownConstant :: AD s a -> Maybe (Scalar (AD s a)) Source #

isKnownZero :: AD s a -> Bool Source #

auto :: Scalar (AD s a) -> AD s a Source #

(*^) :: Scalar (AD s a) -> AD s a -> AD s a Source #

(^*) :: AD s a -> Scalar (AD s a) -> AD s a Source #

(^/) :: AD s a -> Scalar (AD s a) -> AD s a Source #

zero :: AD s a Source #

Bounded a => Bounded (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

minBound :: AD s a #

maxBound :: AD s a #

Enum a => Enum (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

succ :: AD s a -> AD s a #

pred :: AD s a -> AD s a #

toEnum :: Int -> AD s a #

fromEnum :: AD s a -> Int #

enumFrom :: AD s a -> [AD s a] #

enumFromThen :: AD s a -> AD s a -> [AD s a] #

enumFromTo :: AD s a -> AD s a -> [AD s a] #

enumFromThenTo :: AD s a -> AD s a -> AD s a -> [AD s a] #

Floating a => Floating (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

pi :: AD s a #

exp :: AD s a -> AD s a #

log :: AD s a -> AD s a #

sqrt :: AD s a -> AD s a #

(**) :: AD s a -> AD s a -> AD s a #

logBase :: AD s a -> AD s a -> AD s a #

sin :: AD s a -> AD s a #

cos :: AD s a -> AD s a #

tan :: AD s a -> AD s a #

asin :: AD s a -> AD s a #

acos :: AD s a -> AD s a #

atan :: AD s a -> AD s a #

sinh :: AD s a -> AD s a #

cosh :: AD s a -> AD s a #

tanh :: AD s a -> AD s a #

asinh :: AD s a -> AD s a #

acosh :: AD s a -> AD s a #

atanh :: AD s a -> AD s a #

log1p :: AD s a -> AD s a #

expm1 :: AD s a -> AD s a #

log1pexp :: AD s a -> AD s a #

log1mexp :: AD s a -> AD s a #

RealFloat a => RealFloat (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

floatRadix :: AD s a -> Integer #

floatDigits :: AD s a -> Int #

floatRange :: AD s a -> (Int, Int) #

decodeFloat :: AD s a -> (Integer, Int) #

encodeFloat :: Integer -> Int -> AD s a #

exponent :: AD s a -> Int #

significand :: AD s a -> AD s a #

scaleFloat :: Int -> AD s a -> AD s a #

isNaN :: AD s a -> Bool #

isInfinite :: AD s a -> Bool #

isDenormalized :: AD s a -> Bool #

isNegativeZero :: AD s a -> Bool #

isIEEE :: AD s a -> Bool #

atan2 :: AD s a -> AD s a -> AD s a #

Num a => Num (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

(+) :: AD s a -> AD s a -> AD s a #

(-) :: AD s a -> AD s a -> AD s a #

(*) :: AD s a -> AD s a -> AD s a #

negate :: AD s a -> AD s a #

abs :: AD s a -> AD s a #

signum :: AD s a -> AD s a #

fromInteger :: Integer -> AD s a #

Read a => Read (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

readsPrec :: Int -> ReadS (AD s a) #

readList :: ReadS [AD s a] #

readPrec :: ReadPrec (AD s a) #

readListPrec :: ReadPrec [AD s a] #

Fractional a => Fractional (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

(/) :: AD s a -> AD s a -> AD s a #

recip :: AD s a -> AD s a #

fromRational :: Rational -> AD s a #

Real a => Real (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

toRational :: AD s a -> Rational #

RealFrac a => RealFrac (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

properFraction :: Integral b => AD s a -> (b, AD s a) #

truncate :: Integral b => AD s a -> b #

round :: Integral b => AD s a -> b #

ceiling :: Integral b => AD s a -> b #

floor :: Integral b => AD s a -> b #

Show a => Show (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

showsPrec :: Int -> AD s a -> ShowS #

show :: AD s a -> String #

showList :: [AD s a] -> ShowS #

Erf a => Erf (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

erf :: AD s a -> AD s a #

erfc :: AD s a -> AD s a #

erfcx :: AD s a -> AD s a #

normcdf :: AD s a -> AD s a #

InvErf a => InvErf (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

inverf :: AD s a -> AD s a #

inverfc :: AD s a -> AD s a #

invnormcdf :: AD s a -> AD s a #

Eq a => Eq (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

(==) :: AD s a -> AD s a -> Bool #

(/=) :: AD s a -> AD s a -> Bool #

Ord a => Ord (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

Methods

compare :: AD s a -> AD s a -> Ordering #

(<) :: AD s a -> AD s a -> Bool #

(<=) :: AD s a -> AD s a -> Bool #

(>) :: AD s a -> AD s a -> Bool #

(>=) :: AD s a -> AD s a -> Bool #

max :: AD s a -> AD s a -> AD s a #

min :: AD s a -> AD s a -> AD s a #

type Scalar (AD s a) Source # 
Instance details

Defined in Numeric.AD.Internal.Type

type Scalar (AD s a) = Scalar a

data Kahn a Source #

Kahn is a Mode using reverse-mode automatic differentiation that provides fast diffFU, diff2FU, grad, grad2 and a fast jacobian when you have a significantly smaller number of outputs than inputs.

Instances

Instances details
Num a => Jacobian (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Associated Types

type D (Kahn a) Source #

Methods

unary :: (Scalar (Kahn a) -> Scalar (Kahn a)) -> D (Kahn a) -> Kahn a -> Kahn a Source #

lift1 :: (Scalar (Kahn a) -> Scalar (Kahn a)) -> (D (Kahn a) -> D (Kahn a)) -> Kahn a -> Kahn a Source #

lift1_ :: (Scalar (Kahn a) -> Scalar (Kahn a)) -> (D (Kahn a) -> D (Kahn a) -> D (Kahn a)) -> Kahn a -> Kahn a Source #

binary :: (Scalar (Kahn a) -> Scalar (Kahn a) -> Scalar (Kahn a)) -> D (Kahn a) -> D (Kahn a) -> Kahn a -> Kahn a -> Kahn a Source #

lift2 :: (Scalar (Kahn a) -> Scalar (Kahn a) -> Scalar (Kahn a)) -> (D (Kahn a) -> D (Kahn a) -> (D (Kahn a), D (Kahn a))) -> Kahn a -> Kahn a -> Kahn a Source #

lift2_ :: (Scalar (Kahn a) -> Scalar (Kahn a) -> Scalar (Kahn a)) -> (D (Kahn a) -> D (Kahn a) -> D (Kahn a) -> (D (Kahn a), D (Kahn a))) -> Kahn a -> Kahn a -> Kahn a Source #

Num a => Mode (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Associated Types

type Scalar (Kahn a) Source #

(Num a, Bounded a) => Bounded (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

minBound :: Kahn a #

maxBound :: Kahn a #

(Num a, Enum a) => Enum (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

succ :: Kahn a -> Kahn a #

pred :: Kahn a -> Kahn a #

toEnum :: Int -> Kahn a #

fromEnum :: Kahn a -> Int #

enumFrom :: Kahn a -> [Kahn a] #

enumFromThen :: Kahn a -> Kahn a -> [Kahn a] #

enumFromTo :: Kahn a -> Kahn a -> [Kahn a] #

enumFromThenTo :: Kahn a -> Kahn a -> Kahn a -> [Kahn a] #

Floating a => Floating (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

pi :: Kahn a #

exp :: Kahn a -> Kahn a #

log :: Kahn a -> Kahn a #

sqrt :: Kahn a -> Kahn a #

(**) :: Kahn a -> Kahn a -> Kahn a #

logBase :: Kahn a -> Kahn a -> Kahn a #

sin :: Kahn a -> Kahn a #

cos :: Kahn a -> Kahn a #

tan :: Kahn a -> Kahn a #

asin :: Kahn a -> Kahn a #

acos :: Kahn a -> Kahn a #

atan :: Kahn a -> Kahn a #

sinh :: Kahn a -> Kahn a #

cosh :: Kahn a -> Kahn a #

tanh :: Kahn a -> Kahn a #

asinh :: Kahn a -> Kahn a #

acosh :: Kahn a -> Kahn a #

atanh :: Kahn a -> Kahn a #

log1p :: Kahn a -> Kahn a #

expm1 :: Kahn a -> Kahn a #

log1pexp :: Kahn a -> Kahn a #

log1mexp :: Kahn a -> Kahn a #

RealFloat a => RealFloat (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Num a => Num (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

(+) :: Kahn a -> Kahn a -> Kahn a #

(-) :: Kahn a -> Kahn a -> Kahn a #

(*) :: Kahn a -> Kahn a -> Kahn a #

negate :: Kahn a -> Kahn a #

abs :: Kahn a -> Kahn a #

signum :: Kahn a -> Kahn a #

fromInteger :: Integer -> Kahn a #

Fractional a => Fractional (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

(/) :: Kahn a -> Kahn a -> Kahn a #

recip :: Kahn a -> Kahn a #

fromRational :: Rational -> Kahn a #

Real a => Real (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

toRational :: Kahn a -> Rational #

RealFrac a => RealFrac (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

properFraction :: Integral b => Kahn a -> (b, Kahn a) #

truncate :: Integral b => Kahn a -> b #

round :: Integral b => Kahn a -> b #

ceiling :: Integral b => Kahn a -> b #

floor :: Integral b => Kahn a -> b #

Show a => Show (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

showsPrec :: Int -> Kahn a -> ShowS #

show :: Kahn a -> String #

showList :: [Kahn a] -> ShowS #

MuRef (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Associated Types

type DeRef (Kahn a) :: Type -> Type #

Methods

mapDeRef :: Applicative f => (forall b. (MuRef b, DeRef (Kahn a) ~ DeRef b) => b -> f u) -> Kahn a -> f (DeRef (Kahn a) u) #

Erf a => Erf (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

erf :: Kahn a -> Kahn a #

erfc :: Kahn a -> Kahn a #

erfcx :: Kahn a -> Kahn a #

normcdf :: Kahn a -> Kahn a #

InvErf a => InvErf (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

inverf :: Kahn a -> Kahn a #

inverfc :: Kahn a -> Kahn a #

invnormcdf :: Kahn a -> Kahn a #

(Num a, Eq a) => Eq (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

(==) :: Kahn a -> Kahn a -> Bool #

(/=) :: Kahn a -> Kahn a -> Bool #

(Num a, Ord a) => Ord (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

compare :: Kahn a -> Kahn a -> Ordering #

(<) :: Kahn a -> Kahn a -> Bool #

(<=) :: Kahn a -> Kahn a -> Bool #

(>) :: Kahn a -> Kahn a -> Bool #

(>=) :: Kahn a -> Kahn a -> Bool #

max :: Kahn a -> Kahn a -> Kahn a #

min :: Kahn a -> Kahn a -> Kahn a #

Num a => Grad (Kahn a) [a] (a, [a]) a Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

pack :: Kahn a -> [Kahn a] -> Kahn a Source #

unpack :: ([a] -> [a]) -> [a] Source #

unpack' :: ([a] -> (a, [a])) -> (a, [a]) Source #

Grad i o o' a => Grad (Kahn a -> i) (a -> o) (a -> o') a Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

Methods

pack :: (Kahn a -> i) -> [Kahn a] -> Kahn a Source #

unpack :: ([a] -> [a]) -> a -> o Source #

unpack' :: ([a] -> (a, [a])) -> a -> o' Source #

type D (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

type D (Kahn a) = Id a
type Scalar (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

type Scalar (Kahn a) = a
type DeRef (Kahn a) Source # 
Instance details

Defined in Numeric.AD.Internal.Kahn

type DeRef (Kahn a) = Tape a

auto :: Mode t => Scalar t -> t Source #

Embed a constant

Gradient

grad :: (Traversable f, Num a) => (forall s. f (AD s (Kahn a)) -> AD s (Kahn a)) -> f a -> f a Source #

The grad function calculates the gradient of a non-scalar-to-scalar function with kahn-mode AD in a single pass.

>>> grad (\[x,y,z] -> x*y+z) [1,2,3]
[2,1,1]
>>> grad (\[x,y] -> x**y) [0,2]
[0.0,NaN]

grad' :: (Traversable f, Num a) => (forall s. f (AD s (Kahn a)) -> AD s (Kahn a)) -> f a -> (a, f a) Source #

The grad' function calculates the result and gradient of a non-scalar-to-scalar function with kahn-mode AD in a single pass.

>>> grad' (\[x,y,z] -> 4*x*exp y+cos z) [1,2,3]
(28.566231899122155,[29.5562243957226,29.5562243957226,-0.1411200080598672])

gradWith :: (Traversable f, Num a) => (a -> a -> b) -> (forall s. f (AD s (Kahn a)) -> AD s (Kahn a)) -> f a -> f b Source #

grad g f function calculates the gradient of a non-scalar-to-scalar function f with kahn-mode AD in a single pass. The gradient is combined element-wise with the argument using the function g.

grad = gradWith (_ dx -> dx)
id = gradWith const

gradWith' :: (Traversable f, Num a) => (a -> a -> b) -> (forall s. f (AD s (Kahn a)) -> AD s (Kahn a)) -> f a -> (a, f b) Source #

grad' g f calculates the result and gradient of a non-scalar-to-scalar function f with kahn-mode AD in a single pass the gradient is combined element-wise with the argument using the function g.

grad' == gradWith' (_ dx -> dx)

Jacobian

jacobian :: (Traversable f, Functor g, Num a) => (forall s. f (AD s (Kahn a)) -> g (AD s (Kahn a))) -> f a -> g (f a) Source #

The jacobian function calculates the jacobian of a non-scalar-to-non-scalar function with kahn AD lazily in m passes for m outputs.

>>> jacobian (\[x,y] -> [y,x,x*y]) [2,1]
[[0,1],[1,0],[1,2]]
>>> jacobian (\[x,y] -> [exp y,cos x,x+y]) [1,2]
[[0.0,7.38905609893065],[-0.8414709848078965,0.0],[1.0,1.0]]

jacobian' :: (Traversable f, Functor g, Num a) => (forall s. f (AD s (Kahn a)) -> g (AD s (Kahn a))) -> f a -> g (a, f a) Source #

The jacobian' function calculates both the result and the Jacobian of a nonscalar-to-nonscalar function, using m invocations of kahn AD, where m is the output dimensionality. Applying fmap snd to the result will recover the result of jacobian | An alias for gradF'

ghci> jacobian' ([x,y] -> [y,x,x*y]) [2,1] [(1,[0,1]),(2,[1,0]),(2,[1,2])]

jacobianWith :: (Traversable f, Functor g, Num a) => (a -> a -> b) -> (forall s. f (AD s (Kahn a)) -> g (AD s (Kahn a))) -> f a -> g (f b) Source #

'jacobianWith g f' calculates the Jacobian of a non-scalar-to-non-scalar function f with kahn AD lazily in m passes for m outputs.

Instead of returning the Jacobian matrix, the elements of the matrix are combined with the input using the g.

jacobian = jacobianWith (_ dx -> dx)
jacobianWith const = (f x -> const x <$> f x)

jacobianWith' :: (Traversable f, Functor g, Num a) => (a -> a -> b) -> (forall s. f (AD s (Kahn a)) -> g (AD s (Kahn a))) -> f a -> g (a, f b) Source #

jacobianWith g f' calculates both the result and the Jacobian of a nonscalar-to-nonscalar function f, using m invocations of kahn AD, where m is the output dimensionality. Applying fmap snd to the result will recover the result of jacobianWith

Instead of returning the Jacobian matrix, the elements of the matrix are combined with the input using the g.

jacobian' == jacobianWith' (_ dx -> dx)

Hessian

hessian :: (Traversable f, Num a) => (forall s. f (AD s (On (Kahn (Kahn a)))) -> AD s (On (Kahn (Kahn a)))) -> f a -> f (f a) Source #

Compute the hessian via the jacobian of the gradient. gradient is computed in Kahn mode and then the jacobian is computed in Kahn mode.

However, since the grad f :: f a -> f a is square this is not as fast as using the forward-mode jacobian of a reverse mode gradient provided by hessian.

>>> hessian (\[x,y] -> x*y) [1,2]
[[0,1],[1,0]]

hessianF :: (Traversable f, Functor g, Num a) => (forall s. f (AD s (On (Kahn (Kahn a)))) -> g (AD s (On (Kahn (Kahn a))))) -> f a -> g (f (f a)) Source #

Compute the order 3 Hessian tensor on a non-scalar-to-non-scalar function via the Kahn-mode Jacobian of the Kahn-mode Jacobian of the function.

Less efficient than hessianF.

>>> hessianF (\[x,y] -> [x*y,x+y,exp x*cos y]) [1,2 :: RDouble]
[[[0.0,1.0],[1.0,0.0]],[[0.0,0.0],[0.0,0.0]],[[-1.131204383757,-2.471726672005],[-2.471726672005,1.131204383757]]]

Derivatives

diff :: Num a => (forall s. AD s (Kahn a) -> AD s (Kahn a)) -> a -> a Source #

Compute the derivative of a function.

>>> diff sin 0
1.0
>>> cos 0
1.0

diff' :: Num a => (forall s. AD s (Kahn a) -> AD s (Kahn a)) -> a -> (a, a) Source #

The diff' function calculates the value and derivative, as a pair, of a scalar-to-scalar function.

>>> diff' sin 0
(0.0,1.0)

diffF :: (Functor f, Num a) => (forall s. AD s (Kahn a) -> f (AD s (Kahn a))) -> a -> f a Source #

Compute the derivatives of a function that returns a vector with regards to its single input.

>>> diffF (\a -> [sin a, cos a]) 0
[1.0,0.0]

diffF' :: (Functor f, Num a) => (forall s. AD s (Kahn a) -> f (AD s (Kahn a))) -> a -> f (a, a) Source #

Compute the derivatives of a function that returns a vector with regards to its single input as well as the primal answer.

>>> diffF' (\a -> [sin a, cos a]) 0
[(0.0,1.0),(1.0,0.0)]