Module Owl_neural_feedforward

module Owl_neural_feedforward: sig .. end

type network = {

val create : unit -> network

val layer_num : network -> int

val get_layer : network -> int -> Owl_neural_neuron.neuron

val connect_layer : Owl_neural_neuron.neuron -> Owl_neural_neuron.neuron -> unit

val add_layer : ?act_typ:Owl_neural_neuron.Activation.typ ->
       network -> Owl_neural_neuron.neuron -> unit

val init : network -> unit

val reset : network -> unit

val mktag : int -> network -> unit

val mkpar : network -> Owl_neural_neuron.t array array

val mkpri : network -> Owl_algodiff.S.t array array

val mkadj : network -> Owl_algodiff.S.t array array

val update : network -> Owl_algodiff.S.t array array -> unit

val run : Owl_algodiff.S.t -> network -> Owl_algodiff.S.t

val forward : network ->
       Owl_algodiff.S.t -> Owl_algodiff.S.t * Owl_neural_neuron.t array array

val backward : network ->
       Owl_algodiff.S.t ->
       Owl_algodiff.S.t array array * Owl_algodiff.S.t array array

val input_layer : int array -> Owl_neural_neuron.neuron

val activation_layer : Owl_neural_neuron.Activation.typ -> Owl_neural_neuron.neuron

val linear_layer : ?init_typ:Owl_neural_neuron.Init.typ ->
       ?inputs:int -> int -> Owl_neural_neuron.neuron

val linear_nobias_layer : ?init_typ:Owl_neural_neuron.Init.typ ->
       ?inputs:int -> int -> Owl_neural_neuron.neuron

val recurrent_layer : ?init_typ:Owl_neural_neuron.Init.typ ->
       act_typ:Owl_neural_neuron.Activation.typ ->
       ?inputs:int -> int -> int -> Owl_neural_neuron.neuron

val lstm_layer : ?inputs:int -> int -> Owl_neural_neuron.neuron

val gru_layer : ?inputs:int -> int -> Owl_neural_neuron.neuron

val conv2d_layer : ?padding:Owl_algodiff.S.padding ->
       ?inputs:int array -> int array -> int array -> Owl_neural_neuron.neuron

val conv3d_layer : ?padding:Owl_algodiff.S.padding ->
       ?inputs:int array -> 'a -> int array -> int array -> Owl_neural_neuron.neuron

val fully_connected_layer : ?init_typ:Owl_neural_neuron.Init.typ ->
       ?inputs:int -> int -> Owl_neural_neuron.neuron

val max_pool2d_layer : ?padding:Owl_algodiff.S.padding ->
       int array -> int array -> Owl_neural_neuron.neuron

val avg_pool2d_layer : ?padding:Owl_algodiff.S.padding ->
       int array -> int array -> Owl_neural_neuron.neuron

val dropout_layer : float -> Owl_neural_neuron.neuron

val reshape_layer : ?convert:bool -> ?inputs:int array -> int array -> Owl_neural_neuron.neuron

val flatten_layer : ?convert:bool -> unit -> Owl_neural_neuron.neuron

val lambda_layer : (Owl_neural_neuron.t -> Owl_neural_neuron.t) -> Owl_neural_neuron.neuron

val input : int array -> network

val activation : Owl_neural_neuron.Activation.typ ->
       network -> network

val linear : ?init_typ:Owl_neural_neuron.Init.typ ->
       ?act_typ:Owl_neural_neuron.Activation.typ ->
       int -> network -> network

val linear_nobias : ?init_typ:Owl_neural_neuron.Init.typ ->
       ?act_typ:Owl_neural_neuron.Activation.typ ->
       int -> network -> network

val recurrent : ?init_typ:Owl_neural_neuron.Init.typ ->
       act_typ:Owl_neural_neuron.Activation.typ ->
       int ->
       int -> network -> network

val lstm : int -> network -> network

val gru : int -> network -> network

val conv2d : ?padding:Owl_algodiff.S.padding ->
       ?act_typ:Owl_neural_neuron.Activation.typ ->
       int array ->
       int array -> network -> network

val conv3d : ?padding:Owl_algodiff.S.padding ->
       ?act_typ:Owl_neural_neuron.Activation.typ ->
       'a ->
       int array ->
       int array -> network -> network

val fully_connected : ?init_typ:Owl_neural_neuron.Init.typ ->
       ?act_typ:Owl_neural_neuron.Activation.typ ->
       int -> network -> network

val max_pool2d : ?padding:Owl_algodiff.S.padding ->
       ?act_typ:Owl_neural_neuron.Activation.typ ->
       int array ->
       int array -> network -> network

val avg_pool2d : ?padding:Owl_algodiff.S.padding ->
       ?act_typ:Owl_neural_neuron.Activation.typ ->
       int array ->
       int array -> network -> network

val dropout : float -> network -> network

val reshape : ?convert:bool ->
       int array -> network -> network

val flatten : ?convert:bool ->
       network -> network

val lambda : ?act_typ:Owl_neural_neuron.Activation.typ ->
       (Owl_neural_neuron.t -> Owl_neural_neuron.t) ->
       network -> network

val to_string : network -> string

val print : network -> unit

val save : 'a -> string -> unit

val load : string -> network

val train_generic : ?params:Owl_neural_optimise.Params.typ ->
       ?init_model:bool ->
       network ->
       Owl_algodiff.S.t -> Owl_algodiff.S.t -> Owl_algodiff.S.elt array

val train : ?params:Owl_neural_optimise.Params.typ ->
       ?init_model:bool ->
       network ->
       Owl_algodiff.S.mat -> Owl_algodiff.S.mat -> Owl_algodiff.S.elt array

val train_cnn : ?params:Owl_neural_optimise.Params.typ ->
       ?init_model:bool ->
       network ->
       Owl_algodiff.S.arr -> Owl_algodiff.S.mat -> Owl_algodiff.S.elt array

val test_model : network ->
       Owl_algodiff.S.mat -> Owl_algodiff.S.mat -> unit