package owl-base

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Legend:
Library
Module
Module type
Parameter
Class
Class type
Init neuron
module Init : sig ... end
Input neuron
module Input : sig ... end
Activation neuron
module Activation : sig ... end
Linear neuron
module Linear : sig ... end
LinearNoBias neuron
module LinearNoBias : sig ... end
Recurrent neuron
module Recurrent : sig ... end
LSTM neuron
module LSTM : sig ... end
GRU neuron
module GRU : sig ... end
Conv1D neuron
module Conv1D : sig ... end
Conv2D neuron
module Conv2D : sig ... end
Conv3D neuron
module Conv3D : sig ... end
DilatedConv1D neuron
module DilatedConv1D : sig ... end
DilatedConv2D neuron
module DilatedConv2D : sig ... end
DilatedConv3D neuron
module DilatedConv3D : sig ... end
TransposeConv1D neuron
module TransposeConv1D : sig ... end
TransposeConv2D neuron
module TransposeConv2D : sig ... end
TransposeConv3D neuron
module TransposeConv3D : sig ... end
FullyConnected neuron
module FullyConnected : sig ... end
MaxPool1D neuron
module MaxPool1D : sig ... end
MaxPool2D neuron
module MaxPool2D : sig ... end
AvgPool1D neuron
module AvgPool1D : sig ... end
AvgPool2D neuron
module AvgPool2D : sig ... end
GlobalMaxPool1D neuron
module GlobalMaxPool1D : sig ... end
GlobalMaxPool2D neuron
module GlobalMaxPool2D : sig ... end
GlobalAvgPool1D neuron
module GlobalAvgPool1D : sig ... end
GlobalAvgPool2D neuron
module GlobalAvgPool2D : sig ... end
UpSampling1D neuron
module UpSampling1D : sig ... end
UpSampling2D neuron
module UpSampling2D : sig ... end
UpSampling3D neuron
module UpSampling3D : sig ... end
Padding1D neuron
module Padding1D : sig ... end
Padding2D neuron
module Padding2D : sig ... end
Padding3D neuron
module Padding3D : sig ... end
Lambda neuron
module Lambda : sig ... end
LambdaArray neuron
module LambdaArray : sig ... end
Dropout neuron
module Dropout : sig ... end
Reshape neuron
module Reshape : sig ... end
Flatten neuron
module Flatten : sig ... end
Slice neuron
module Slice : sig ... end
Add neuron
module Add : sig ... end
Mul neuron
module Mul : sig ... end
Dot neuron
module Dot : sig ... end
Max neuron
module Max : sig ... end
Average neuron
module Average : sig ... end
Concatenate neuron
module Concatenate : sig ... end
Normalisation neuron
module Normalisation : sig ... end
GaussianNoise neuron
module GaussianNoise : sig ... end
GaussianDropout neuron
module GaussianDropout : sig ... end
AlphaDropout neuron
module AlphaDropout : sig ... end
Embedding neuron
module Embedding : sig ... end
Masking neuron
module Masking : sig ... end
Core functions
type 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. | Slice of Slice.neuron_typ
  32. | Lambda of Lambda.neuron_typ
  33. | LambdaArray of LambdaArray.neuron_typ
  34. | Activation of Activation.neuron_typ
  35. | GaussianNoise of GaussianNoise.neuron_typ
  36. | GaussianDropout of GaussianDropout.neuron_typ
  37. | AlphaDropout of AlphaDropout.neuron_typ
  38. | Normalisation of Normalisation.neuron_typ
  39. | Add of Add.neuron_typ
  40. | Mul of Mul.neuron_typ
  41. | Dot of Dot.neuron_typ
  42. | Max of Max.neuron_typ
  43. | Average of Average.neuron_typ
  44. | Concatenate of Concatenate.neuron_typ
    (*

    Types of neuron.

    *)
val get_in_out_shape : neuron -> int array * int array

Get both input and output shapes of a neuron.

val get_in_shape : neuron -> int array

Get the input shape of a neuron.

val get_out_shape : neuron -> int array

Get the output shape of a neuron.

val connect : int array array -> neuron -> unit

Connect this neuron to others in a neural network.

val init : neuron -> unit

Initialise the neuron and its parameters.

val reset : neuron -> unit

Reset the parameters in a neuron.

val mktag : int -> neuron -> unit

Tag the neuron, used by ``Algodiff`` module.

val mkpar : neuron -> Optimise.Algodiff.t array

Assemble all the trainable parameters in an array, used by ``Optimise`` module.

val mkpri : neuron -> Optimise.Algodiff.t array

Assemble all the primal values in an array, used by ``Optimise`` module.

val mkadj : neuron -> Optimise.Algodiff.t array

Assemble all the adjacent values in an array, used by ``Optimise`` module.

val update : neuron -> Optimise.Algodiff.t array -> unit

Update trainable parameters in a neuron, used by ``Optimise`` module.

val load_weights : neuron -> Optimise.Algodiff.t array -> unit

Load both trainable and non-trainable parameters into the neuron.

val save_weights : neuron -> Optimise.Algodiff.t array

Assemble both trainable and non-trainable parameters of the neuron.

val copy : neuron -> neuron

Make a deep copy of the neuron and its parameters.

Execute the computation in this neuron.

val to_string : neuron -> string

Convert the neuron to its string representation. The string is often a summary of the parameters defined in the neuron.

val to_name : neuron -> string

Return the name of the neuron.

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