package owl

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package owl
Legend:
Library
Module
Module type
Parameter
Class
Class type
Utils module
module Utils : sig ... end
Learning_Rate module
module Learning_Rate : sig ... end
Batch module
module Batch : sig ... end
Loss module
module Loss : sig ... end
Gradient module
module Gradient : sig ... end
Momentum module
module Momentum : sig ... end
Regularisation module
module Regularisation : sig ... end
Clipping module
module Clipping : sig ... end
Stopping module
module Stopping : sig ... end
Checkpoint module
module Checkpoint : sig ... end
Params module
module Params : sig ... end
Core functions

This function minimises the weight ``w`` of passed-in function ``f``.

* ``f`` is a function ``f : w -> x -> y``. * ``w`` is a row vector but ``y`` can have any shape.

val minimise_network : ?state:Checkpoint.state -> Params.typ -> (Algodiff.t -> Algodiff.t * Algodiff.t array array) -> (Algodiff.t -> Algodiff.t array array * Algodiff.t array array) -> (Algodiff.t array array -> unit) -> (string -> unit) -> Algodiff.t -> Algodiff.t -> Checkpoint.state

This function is specifically designed for minimising the weights in a neural network of graph structure. In Owl's earlier versions, the functions in the regression module were actually implemented using this function.

This function minimises ``f : x -> y`` w.r.t ``x``.

``x`` is an ndarray; and ``y`` is an scalar value.

val minimise_compiled_network : ?state:Checkpoint.state -> Params.typ -> (Algodiff.t -> Algodiff.t -> Algodiff.t) -> (unit -> unit) -> (string -> unit) -> Algodiff.t -> Algodiff.t -> Checkpoint.state

TODO