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package owl-base
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Module Owl_neural_graph.MakeSource

Parameters

Signature

Sourcemodule Neuron : sig ... end
Sourcemodule Optimise : sig ... end
Sourcetype node = {
  1. mutable name : string;
  2. mutable prev : node array;
  3. mutable next : node array;
  4. mutable neuron : Neuron.neuron;
  5. mutable output : Neuron.t option;
  6. mutable network : network;
  7. mutable train : bool;
}
Sourceand network = {
  1. mutable nnid : string;
  2. mutable size : int;
  3. mutable root : node option;
  4. mutable topo : node array;
}
Sourceval make_network : ?nnid:string -> int -> node option -> node array -> network
Sourceval make_node : ?name:string -> ?train:bool -> node array -> node array -> Neuron.neuron -> Neuron.t option -> network -> node
Sourceval get_root : network -> node
Sourceval get_node : network -> string -> node
Sourceval get_network : node -> network
Sourceval collect_output : node array -> Neuron.t array
Sourceval connect_pair : node -> node -> unit
Sourceval connect_to_parents : node array -> node -> unit
Sourceval add_node : ?act_typ:Neuron.Activation.typ -> network -> node array -> node -> node
Sourceval init : network -> unit
Sourceval reset : network -> unit
Sourceval mktag : int -> network -> unit
Sourceval mkpar : network -> Neuron.t array array
Sourceval mkpri : network -> Neuron.t array array
Sourceval mkadj : network -> Neuron.t array array
Sourceval update : network -> Neuron.t array array -> unit
Sourceval forward : network -> Neuron.t -> Neuron.t * Neuron.t array array
Sourceval backward : network -> Neuron.t -> Neuron.t array array * Neuron.t array array
Sourceval copy : network -> network
Sourceval _remove_training_nodes : network -> unit
Sourceval input : ?name:string -> int array -> node
Sourceval activation : ?name:string -> Neuron.Activation.typ -> node -> node
Sourceval linear : ?name:string -> ?init_typ:Neuron.Init.typ -> ?act_typ:Neuron.Activation.typ -> int -> node -> node
Sourceval linear_nobias : ?name:string -> ?init_typ:Neuron.Init.typ -> ?act_typ:Neuron.Activation.typ -> int -> node -> node
Sourceval embedding : ?name:string -> ?init_typ:Neuron.Init.typ -> ?act_typ:Neuron.Activation.typ -> int -> int -> node -> node
Sourceval recurrent : ?name:string -> ?init_typ:Neuron.Init.typ -> act_typ:Neuron.Activation.typ -> int -> int -> node -> node
Sourceval lstm : ?name:string -> ?init_typ:Neuron.Init.typ -> int -> node -> node
Sourceval gru : ?name:string -> ?init_typ:Neuron.Init.typ -> int -> node -> node
Sourceval conv1d : ?name:string -> ?padding:Owl_types.padding -> ?init_typ:Neuron.Init.typ -> ?act_typ:Neuron.Activation.typ -> int array -> int array -> node -> node
Sourceval conv2d : ?name:string -> ?padding:Owl_types.padding -> ?init_typ:Neuron.Init.typ -> ?act_typ:Neuron.Activation.typ -> int array -> int array -> node -> node
Sourceval conv3d : ?name:string -> ?padding:Owl_types.padding -> ?init_typ:Neuron.Init.typ -> ?act_typ:Neuron.Activation.typ -> int array -> int array -> node -> node
Sourceval fully_connected : ?name:string -> ?init_typ:Neuron.Init.typ -> ?act_typ:Neuron.Activation.typ -> int -> node -> node
Sourceval max_pool1d : ?name:string -> ?padding:Owl_types.padding -> ?act_typ:Neuron.Activation.typ -> int array -> int array -> node -> node
Sourceval max_pool2d : ?name:string -> ?padding:Owl_types.padding -> ?act_typ:Neuron.Activation.typ -> int array -> int array -> node -> node
Sourceval avg_pool1d : ?name:string -> ?padding:Owl_types.padding -> ?act_typ:Neuron.Activation.typ -> int array -> int array -> node -> node
Sourceval avg_pool2d : ?name:string -> ?padding:Owl_types.padding -> ?act_typ:Neuron.Activation.typ -> int array -> int array -> node -> node
Sourceval global_max_pool1d : ?name:string -> ?act_typ:Neuron.Activation.typ -> node -> node
Sourceval global_max_pool2d : ?name:string -> ?act_typ:Neuron.Activation.typ -> node -> node
Sourceval global_avg_pool1d : ?name:string -> ?act_typ:Neuron.Activation.typ -> node -> node
Sourceval global_avg_pool2d : ?name:string -> ?act_typ:Neuron.Activation.typ -> node -> node
Sourceval dropout : ?name:string -> float -> node -> node
Sourceval gaussian_noise : ?name:string -> float -> node -> node
Sourceval gaussian_dropout : ?name:string -> float -> node -> node
Sourceval alpha_dropout : ?name:string -> float -> node -> node
Sourceval normalisation : ?name:string -> ?axis:int -> ?training:bool -> ?decay:float -> ?mu:Neuron.arr -> ?var:Neuron.arr -> node -> node
Sourceval reshape : ?name:string -> int array -> node -> node
Sourceval flatten : ?name:string -> node -> node
Sourceval lambda : ?name:string -> ?act_typ:Neuron.Activation.typ -> (Neuron.t -> Neuron.t) -> node -> node
Sourceval add : ?name:string -> ?act_typ:Neuron.Activation.typ -> node array -> node
Sourceval mul : ?name:string -> ?act_typ:Neuron.Activation.typ -> node array -> node
Sourceval dot : ?name:string -> ?act_typ:Neuron.Activation.typ -> node array -> node
Sourceval max : ?name:string -> ?act_typ:Neuron.Activation.typ -> node array -> node
Sourceval average : ?name:string -> ?act_typ:Neuron.Activation.typ -> node array -> node
Sourceval concatenate : ?name:string -> ?act_typ:Neuron.Activation.typ -> int -> node array -> node
Sourceval to_string : network -> string
Sourceval pp_network : Format.formatter -> network -> unit
Sourceval print : network -> unit
Sourceval save : network -> string -> unit
Sourceval load : string -> network
Sourceval save_weights : network -> string -> unit
Sourceval load_weights : network -> string -> unit
Sourceval train_generic : ?state:Optimise.Checkpoint.state -> ?params:Optimise.Params.typ -> ?init_model:bool -> network -> Optimise.t -> Optimise.t -> Optimise.Checkpoint.state