Module Make.Normalisation

type neuron_typ = {
  1. mutable axis : int;
  2. mutable beta : Optimise.Algodiff.t;
  3. mutable gamma : Optimise.Algodiff.t;
  4. mutable mu : Optimise.Algodiff.t;
  5. mutable var : Optimise.Algodiff.t;
  6. mutable decay : Optimise.Algodiff.t;
  7. mutable training : bool;
  8. mutable in_shape : int array;
  9. mutable out_shape : int array;
}
val create : ?training:bool -> ?decay:float -> ?mu:Optimise.Algodiff.A.arr -> ?var:Optimise.Algodiff.A.arr -> int -> neuron_typ
val connect : int array -> neuron_typ -> unit
val init : neuron_typ -> unit
val reset : neuron_typ -> unit
val mktag : int -> neuron_typ -> unit
val mkpar : neuron_typ -> Optimise.Algodiff.t array
val mkpri : neuron_typ -> Optimise.Algodiff.t array
val mkadj : neuron_typ -> Optimise.Algodiff.t array
val update : neuron_typ -> Optimise.Algodiff.t array -> unit
val load_weights : neuron_typ -> Optimise.Algodiff.t array -> unit
val save_weights : neuron_typ -> Optimise.Algodiff.t array
val copy : neuron_typ -> neuron_typ
val to_string : neuron_typ -> string
val to_name : unit -> string