package owl

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Library
Module
Module type
Parameter
Class
Class type
module Optimise : sig ... end
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 DilatedConv1D : sig ... end
module DilatedConv2D : sig ... end
module DilatedConv3D : sig ... end
module TransposeConv1D : sig ... end
module TransposeConv2D : sig ... end
module TransposeConv3D : 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 LambdaArray : 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_generic.Make_Embedded(Owl_algodiff_primal_ops.D).Neuron.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. | DilatedConv1D of DilatedConv1D.neuron_typ
  12. | DilatedConv2D of DilatedConv2D.neuron_typ
  13. | DilatedConv3D of DilatedConv3D.neuron_typ
  14. | TransposeConv1D of TransposeConv1D.neuron_typ
  15. | TransposeConv2D of TransposeConv2D.neuron_typ
  16. | TransposeConv3D of TransposeConv3D.neuron_typ
  17. | FullyConnected of FullyConnected.neuron_typ
  18. | MaxPool1D of MaxPool1D.neuron_typ
  19. | MaxPool2D of MaxPool2D.neuron_typ
  20. | AvgPool1D of AvgPool1D.neuron_typ
  21. | AvgPool2D of AvgPool2D.neuron_typ
  22. | GlobalMaxPool1D of GlobalMaxPool1D.neuron_typ
  23. | GlobalMaxPool2D of GlobalMaxPool2D.neuron_typ
  24. | GlobalAvgPool1D of GlobalAvgPool1D.neuron_typ
  25. | GlobalAvgPool2D of GlobalAvgPool2D.neuron_typ
  26. | UpSampling2D of UpSampling2D.neuron_typ
  27. | Padding2D of Padding2D.neuron_typ
  28. | Dropout of Dropout.neuron_typ
  29. | Reshape of Reshape.neuron_typ
  30. | Flatten of Flatten.neuron_typ
  31. | Lambda of Lambda.neuron_typ
  32. | LambdaArray of LambdaArray.neuron_typ
  33. | Activation of Activation.neuron_typ
  34. | GaussianNoise of GaussianNoise.neuron_typ
  35. | GaussianDropout of GaussianDropout.neuron_typ
  36. | AlphaDropout of AlphaDropout.neuron_typ
  37. | Normalisation of Normalisation.neuron_typ
  38. | Add of Add.neuron_typ
  39. | Mul of Mul.neuron_typ
  40. | Dot of Dot.neuron_typ
  41. | Max of Max.neuron_typ
  42. | Average of Average.neuron_typ
  43. | 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 -> Optimise.Algodiff.t array
val mkpri : neuron -> Optimise.Algodiff.t array
val mkadj : neuron -> Optimise.Algodiff.t array
val update : neuron -> Optimise.Algodiff.t array -> unit
val load_weights : neuron -> Optimise.Algodiff.t array -> unit
val save_weights : neuron -> Optimise.Algodiff.t array
val copy : neuron -> neuron
val to_string : neuron -> string
val to_name : neuron -> string
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