package owl-base

  1. Overview
  2. Docs
On This Page
  1. Init neuron
  2. Input neuron
  3. Activation neuron
  4. Linear neuron
  5. LinearNoBias neuron
  6. Recurrent neuron
  7. LSTM neuron
  8. GRU neuron
  9. Conv1D neuron
  10. Conv2D neuron
  11. Conv3D neuron
  12. DilatedConv1D neuron
  13. DilatedConv2D neuron
  14. DilatedConv3D neuron
  15. TransposeConv1D neuron
  16. TransposeConv2D neuron
  17. TransposeConv3D neuron
  18. FullyConnected neuron
  19. MaxPool1D neuron
  20. MaxPool2D neuron
  21. AvgPool1D neuron
  22. AvgPool2D neuron
  23. GlobalMaxPool1D neuron
  24. GlobalMaxPool2D neuron
  25. GlobalAvgPool1D neuron
  26. GlobalAvgPool2D neuron
  27. UpSampling1D neuron
  28. UpSampling2D neuron
  29. UpSampling3D neuron
  30. Padding1D neuron
  31. Padding2D neuron
  32. Padding3D neuron
  33. Lambda neuron
  34. LambdaArray neuron
  35. Dropout neuron
  36. Reshape neuron
  37. Flatten neuron
  38. Slice neuron
  39. Add neuron
  40. Mul neuron
  41. Dot neuron
  42. Max neuron
  43. Average neuron
  44. Concatenate neuron
  45. Normalisation neuron
  46. GaussianNoise neuron
  47. GaussianDropout neuron
  48. AlphaDropout neuron
  49. Embedding neuron
  50. Masking neuron
  51. Core functions
package owl-base
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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