Module Optimise.Algodiff

module A : sig ... end
type t = Owl_neural_neuron.Make(Owl_optimise_generic.Make(Owl_algodiff_generic.Make(A))).Optimise.Algodiff.t =
  1. | F of A.elt
  2. | Arr of A.arr
  3. | DF of t * t * int
  4. | DR of t * t Stdlib.ref * op * int Stdlib.ref * int * int Stdlib.ref
and adjoint = t -> t Stdlib.ref -> (t * t) list -> (t * t) list
and register = t list -> t list
and label = string * t list
and op = adjoint * register * label
val tag : unit -> int
val primal : t -> t
val primal' : t -> t
val zero : t -> t
val reset_zero : t -> t
val tangent : t -> t
val adjref : t -> t Stdlib.ref
val adjval : t -> t
val shape : t -> int array
val is_float : t -> bool
val is_arr : t -> bool
val row_num : t -> int
val col_num : t -> int
val numel : t -> int
val clip_by_value : amin:A.elt -> amax:A.elt -> t -> t
val clip_by_l2norm : A.elt -> t -> t
val copy_primal' : t -> t
val tile : t -> int array -> t
val repeat : t -> int array -> t
val pack_elt : A.elt -> t
val unpack_elt : t -> A.elt
val pack_flt : float -> t
val _f : float -> t
val unpack_flt : t -> float
val pack_arr : A.arr -> t
val unpack_arr : t -> A.arr
val deep_info : t -> string
val type_info : t -> string
val error_binop : string -> t -> t -> 'a
val error_uniop : string -> t -> 'a
val make_forward : t -> t -> int -> t
val make_reverse : t -> int -> t
val reverse_prop : t -> t -> unit
val diff : (t -> t) -> t -> t
val diff' : (t -> t) -> t -> t * t
val grad : (t -> t) -> t -> t
val grad' : (t -> t) -> t -> t * t
val jacobian : (t -> t) -> t -> t
val jacobian' : (t -> t) -> t -> t * t
val jacobianv : (t -> t) -> t -> t -> t
val jacobianv' : (t -> t) -> t -> t -> t * t
val jacobianTv : (t -> t) -> t -> t -> t
val jacobianTv' : (t -> t) -> t -> t -> t * t
val hessian : (t -> t) -> t -> t
val hessian' : (t -> t) -> t -> t * t
val hessianv : (t -> t) -> t -> t -> t
val hessianv' : (t -> t) -> t -> t -> t * t
val laplacian : (t -> t) -> t -> t
val laplacian' : (t -> t) -> t -> t * t
val gradhessian : (t -> t) -> t -> t * t
val gradhessian' : (t -> t) -> t -> t * t * t
val gradhessianv : (t -> t) -> t -> t -> t * t
val gradhessianv' : (t -> t) -> t -> t -> t * t * t
module Builder : sig ... end
module Maths : sig ... end
module Linalg : sig ... end
module NN : sig ... end
module Mat : sig ... end
module Arr : sig ... end
val to_trace : t list -> string
val to_dot : t list -> string
val pp_num : Stdlib.Format.formatter -> t -> unit