package owl

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package owl
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Parameters

module M : MatrixSig
module A : NdarraySig with type elt = M.elt and type arr = M.arr

Signature

type arr = A.arr
type mat = M.mat
type elt = M.elt
type padding = A.padding
type trace_op
type t =
  1. | F of float
  2. | Arr of arr
  3. | Mat of mat
  4. | DF of t * t * int
  5. | DR of t * t Pervasives.ref * trace_op * int Pervasives.ref * int
module Maths : sig ... end

Simple wrappers of matrix and ndarray module, so you don't have to pack and unpack stuff all the time. Some operations just interface to those already defined in the Maths module.

module Mat : sig ... end
module Arr : sig ... end
val diff : (t -> t) -> t -> t

diff f x returns the exat derivative of a function f : scalar -> scalar at point x. Simply calling diff f will return its derivative function g of the same type, i.e. g : scalar -> scalar.

Keep calling this function will give you higher-order derivatives of f, i.e. f |> diff |> diff |> diff |> ...

val diff' : (t -> t) -> t -> t * t

similar to diff, but return (f x, diff f x).

val grad : (t -> t) -> t -> t

gradient of f : (vector -> scalar) at x, reverse ad.

val grad' : (t -> t) -> t -> t * t

similar to grad, but return (f x, grad f x).

val jacobian : (t -> t) -> t -> t

jacobian of f : (vector -> vector) at x, both x and y are row vectors.

val jacobian' : (t -> t) -> t -> t * t

similar to jacobian, but return (f x, jacobian f x)

val jacobianv : (t -> t) -> t -> t -> t

jacobian vector product of f : (vector -> vector) at x along v, forward ad. Namely, it calcultes (jacobian x) v

val jacobianv' : (t -> t) -> t -> t -> t * t

similar to jacobianv', but return (f x, jacobianv f x v)

val jacobianTv : (t -> t) -> t -> t -> t

transposed jacobian vector product of f : (vector -> vector) at x along v, backward ad. Namely, it calculates transpose ((jacobianv f x v)).

val jacobianTv' : (t -> t) -> t -> t -> t * t

similar to jacobianTv, but return (f x, transpose (jacobianv f x v))

val hessian : (t -> t) -> t -> t

hessian of f : (scalar -> scalar) at x.

val hessian' : (t -> t) -> t -> t * t

simiarl to hessian, but return (f x, hessian f x)

val hessianv : (t -> t) -> t -> t -> t

hessian vector product of f : (scalar -> scalar) at x along v. Namely, it calculates (hessian x) v.

val hessianv' : (t -> t) -> t -> t -> t * t

similar to hessianv, but return (f x, hessianv f x v).

val laplacian : (t -> t) -> t -> t

laplacian of f : (scalar -> scalar) at x.

val laplacian' : (t -> t) -> t -> t * t

simiar to laplacian, but return (f x, laplacian f x).

val gradhessian : (t -> t) -> t -> t * t

return (grad f x, hessian f x), f : (scalar -> scalar)

val gradhessian' : (t -> t) -> t -> t * t * t

return (f x, grad f x, hessian f x)

val gradhessianv : (t -> t) -> t -> t -> t * t

return (grad f x v, hessian f x v)

val gradhessianv' : (t -> t) -> t -> t -> t * t * t

return (f x, grad f x v, hessian f x v)

val pack_flt : elt -> t
val unpack_flt : t -> elt
val pack_arr : arr -> t
val unpack_arr : t -> arr
val pack_mat : mat -> t
val unpack_mat : t -> mat
val tag : unit -> int
val primal : t -> t
val primal' : t -> t
val adjval : t -> t
val adjref : t -> t Pervasives.ref
val tangent : t -> t
val make_forward : t -> t -> int -> t
val make_reverse : t -> int -> t
val reverse_prop : t -> t -> unit
val type_info : t -> string
val shape : t -> int array
val clip_by_l2norm : elt -> t -> t
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