tensorflow 0.0.10 · OCaml Package

type _1d

type _2d

type _3d

module Shape : sig ... end

module Id : sig ... end

module Input_id : sig ... end

type 'a t

type init = [

| `const of Base.float
| `normal of Base.float
| `truncated_normal of Base.float

]

val shape : 'a t -> 'a Shape.t

val id : _ t -> Id.t

val input : shape:'a Shape.t -> 'a t * Input_id.t

val const : Base.float -> shape:'a Shape.t -> 'a t

val sigmoid : 'a t -> 'a t

val tanh : 'a t -> 'a t

val relu : 'a t -> 'a t

val softmax : 'a t -> 'a t

val reduce_sum : 'a t -> 'a t

val square : 'a t -> 'a t

val neg : 'a t -> 'a t

val (+) : 'a t -> 'a t -> 'a t

val (-) : 'a t -> 'a t -> 'a t

val (*) : 'a t -> 'a t -> 'a t

val dense : 
  ?w_init:init ->
  ?b_init:init ->
  ?name:Base.string ->
  Base.int ->
  _1d t ->
  _1d t

val conv2d : 
  ?w_init:init ->
  ?b_init:init ->
  ?name:Base.string ->
  filter:(Base.int * Base.int) ->
  out_channels:Base.int ->
  strides:(Base.int * Base.int) ->
  padding:[ `same | `valid ] ->
  Base.unit ->
  _3d t ->
  _3d t

val dense' : 
  ?w_init:init ->
  ?b_init:init ->
  ?name:Base.string ->
  Base.int ->
  (_1d t -> _1d t) Base.Staged.t

val conv2d' : 
  ?w_init:init ->
  ?b_init:init ->
  ?name:Base.string ->
  filter:(Base.int * Base.int) ->
  out_channels:Base.int ->
  strides:(Base.int * Base.int) ->
  padding:[ `same | `valid ] ->
  Base.unit ->
  (_3d t -> _3d t) Base.Staged.t

val avg_pool : 
  _3d t ->
  filter:(Base.int * Base.int) ->
  strides:(Base.int * Base.int) ->
  padding:[ `same | `valid ] ->
  _3d t

val max_pool : 
  _3d t ->
  filter:(Base.int * Base.int) ->
  strides:(Base.int * Base.int) ->
  padding:[ `same | `valid ] ->
  _3d t

val reshape : _ t -> shape:'a Shape.t -> 'a t

val flatten : _ t -> _1d t

val split : _2d t -> _1d t Base.list

val concat : _1d t Base.list -> _2d t

val var : 'a t -> 'a t

module Optimizer : sig ... end

module Loss : sig ... end

module Model : sig ... end

package tensorflow