owl 0.3.0 · OCaml Package

owl

Parameters

module A : Owl_types.NdarraySig

Signature

type arr = A.arr

type elt = A.elt

type trace_op

type t =

| F of float
| Arr of arr
| DF of t * t * int
| DR of t * t Stdlib.ref * trace_op * int Stdlib.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 tag : unit -> int

val primal : t -> t

val primal' : t -> t

val adjval : t -> t

val adjref : t -> t Stdlib.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 copy_primal' : t -> t

val clip_by_l2norm : elt -> t -> t

val to_trace : t list -> string

to_trace [t0; t1; ...] outputs the trace of computation graph on the terminal in a human-readable format.

val to_dot : t list -> string

to_dot [t0; t1; ...] outputs the trace of computation graph in the dot file format which you can use other tools further visualisation, such as Graphviz.

val pp_num : Stdlib.Format.formatter -> t -> unit

pp_num t pretty prints the abstract number used in Algodiff.

package owl

Parameters

Signature