package owl

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Parameter
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Class type
type arr = A.arr
type mat = M.mat
type elt = M.elt
type t = Owl_algodiff_generic.Make(M)(A).t =
  1. | F of float
  2. | Arr of arr
  3. | Mat of mat
  4. | DF of t * t * int
  5. | DR of t * t Pervasives.ref * trace_op * int Pervasives.ref * int
module Maths : sig ... end
module Mat : sig ... end
module Arr : sig ... end
val diff : (t -> t) -> t -> t
val diff' : (t -> t) -> t -> t * t
val grad : (t -> t) -> t -> t
val grad' : (t -> t) -> t -> t * t
val jacobian : (t -> t) -> t -> t
val jacobian' : (t -> t) -> t -> t * t
val jacobianv : (t -> t) -> t -> t -> t
val jacobianv' : (t -> t) -> t -> t -> t * t
val jacobianTv : (t -> t) -> t -> t -> t
val jacobianTv' : (t -> t) -> t -> t -> t * t
val hessian : (t -> t) -> t -> t
val hessian' : (t -> t) -> t -> t * t
val hessianv : (t -> t) -> t -> t -> t
val hessianv' : (t -> t) -> t -> t -> t * t
val laplacian : (t -> t) -> t -> t
val laplacian' : (t -> t) -> t -> t * t
val gradhessian : (t -> t) -> t -> t * t
val gradhessian' : (t -> t) -> t -> t * t * t
val gradhessianv : (t -> t) -> t -> t -> t * t
val gradhessianv' : (t -> t) -> t -> t -> t * t * t
val pack_flt : elt -> t
val unpack_flt : t -> elt
val pack_arr : arr -> t
val unpack_arr : t -> arr
val pack_mat : mat -> t
val unpack_mat : t -> mat
val tag : unit -> int
val primal : t -> t
val primal' : t -> t
val adjval : t -> t
val adjref : t -> t Pervasives.ref
val tangent : t -> t
val make_forward : t -> t -> int -> t
val make_reverse : t -> int -> t
val reverse_prop : t -> t -> unit
val type_info : t -> string
val shape : t -> int array
val clone_primal' : t -> t
val clip_by_l2norm : elt -> t -> t
val to_trace : t list -> string
val to_dot : t list -> string
module Init : sig ... end
module Input : sig ... end
module Activation : sig ... end
module Linear : sig ... end
module LinearNoBias : sig ... end
module Recurrent : sig ... end
module LSTM : sig ... end
module GRU : sig ... end
module Conv1D : sig ... end
module Conv2D : sig ... end
module Conv3D : sig ... end
module FullyConnected : sig ... end
module MaxPool1D : sig ... end
module MaxPool2D : sig ... end
module AvgPool1D : sig ... end
module AvgPool2D : sig ... end
module GlobalMaxPool1D : sig ... end
module GlobalMaxPool2D : sig ... end
module GlobalAvgPool1D : sig ... end
module GlobalAvgPool2D : sig ... end
module UpSampling1D : sig ... end
module UpSampling2D : sig ... end
module UpSampling3D : sig ... end
module Padding1D : sig ... end
module Padding2D : sig ... end
module Padding3D : sig ... end
module Lambda : sig ... end
module Dropout : sig ... end
module Reshape : sig ... end
module Flatten : sig ... end
module Add : sig ... end
module Mul : sig ... end
module Dot : sig ... end
module Max : sig ... end
module Average : sig ... end
module Concatenate : sig ... end
module Normalisation : sig ... end
module GaussianNoise : sig ... end
module GaussianDropout : sig ... end
module AlphaDropout : sig ... end
module Embedding : sig ... end
module Masking : sig ... end
type neuron = Owl_neural_neuron.Make(M)(A).neuron =
  1. | Input of Input.neuron_typ
  2. | Linear of Linear.neuron_typ
  3. | LinearNoBias of LinearNoBias.neuron_typ
  4. | Embedding of Embedding.neuron_typ
  5. | LSTM of LSTM.neuron_typ
  6. | GRU of GRU.neuron_typ
  7. | Recurrent of Recurrent.neuron_typ
  8. | Conv1D of Conv1D.neuron_typ
  9. | Conv2D of Conv2D.neuron_typ
  10. | Conv3D of Conv3D.neuron_typ
  11. | FullyConnected of FullyConnected.neuron_typ
  12. | MaxPool1D of MaxPool1D.neuron_typ
  13. | MaxPool2D of MaxPool2D.neuron_typ
  14. | AvgPool1D of AvgPool1D.neuron_typ
  15. | AvgPool2D of AvgPool2D.neuron_typ
  16. | GlobalMaxPool1D of GlobalMaxPool1D.neuron_typ
  17. | GlobalMaxPool2D of GlobalMaxPool2D.neuron_typ
  18. | GlobalAvgPool1D of GlobalAvgPool1D.neuron_typ
  19. | GlobalAvgPool2D of GlobalAvgPool2D.neuron_typ
  20. | Dropout of Dropout.neuron_typ
  21. | Reshape of Reshape.neuron_typ
  22. | Flatten of Flatten.neuron_typ
  23. | Lambda of Lambda.neuron_typ
  24. | Activation of Activation.neuron_typ
  25. | GaussianNoise of GaussianNoise.neuron_typ
  26. | GaussianDropout of GaussianDropout.neuron_typ
  27. | AlphaDropout of AlphaDropout.neuron_typ
  28. | Normalisation of Normalisation.neuron_typ
  29. | Add of Add.neuron_typ
  30. | Mul of Mul.neuron_typ
  31. | Dot of Dot.neuron_typ
  32. | Max of Max.neuron_typ
  33. | Average of Average.neuron_typ
  34. | Concatenate of Concatenate.neuron_typ
val get_in_out_shape : neuron -> int array * int array
val get_in_shape : neuron -> int array
val get_out_shape : neuron -> int array
val connect : int array array -> neuron -> unit
val init : neuron -> unit
val reset : neuron -> unit
val mktag : int -> neuron -> unit
val mkpar : neuron -> t array
val mkpri : neuron -> t array
val mkadj : neuron -> t array
val update : neuron -> t array -> unit
val copy : neuron -> neuron
val run : t array -> neuron -> t
val to_string : neuron -> string
val to_name : neuron -> string
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