package owl

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Module Graph.Neuron

type t = Owl_algodiff_generic.Make(Owl_dense_ndarray.D).t =
  1. | F of float
  2. | Arr of arr
  3. | DF of t * t * int
  4. | DR of t * t ref * trace_op * int ref * int
and trace_op = Owl_algodiff_generic.Make(Owl_dense_ndarray.D).trace_op =
  1. | Noop
  2. | Add_D_D of t * t
  3. | Add_D_C of t * t
  4. | Add_C_D of t * t
  5. | Sub_D_D of t * t
  6. | Sub_D_C of t * t
  7. | Sub_C_D of t * t
  8. | Mul_D_D of t * t
  9. | Mul_D_C of t * t
  10. | Mul_C_D of t * t
  11. | Div_D_D of t * t
  12. | Div_D_C of t * t
  13. | Div_C_D of t * t
  14. | Pow_D_D of t * t
  15. | Pow_D_C of t * t
  16. | Pow_C_D of t * t
  17. | Atan2_D_D of t * t
  18. | Atan2_D_C of t * t
  19. | Atan2_C_D of t * t
  20. | Neg_D of t
  21. | Abs_D of t
  22. | Signum_D of t
  23. | Floor_D of t
  24. | Ceil_D of t
  25. | Round_D of t
  26. | Sqr_D of t
  27. | Sqrt_D of t
  28. | Log_D of t
  29. | Log2_D of t
  30. | Log10_D of t
  31. | Exp_D of t
  32. | Sin_D of t
  33. | Cos_D of t
  34. | Tan_D of t
  35. | Sinh_D of t
  36. | Cosh_D of t
  37. | Tanh_D of t
  38. | Asin_D of t
  39. | Acos_D of t
  40. | Atan_D of t
  41. | Asinh_D of t
  42. | Acosh_D of t
  43. | Atanh_D of t
  44. | Get_Item of t * int * int
  45. | SetI_D_D of t * int * int * t
  46. | SetI_D_C of t * int * int * t
  47. | SetI_C_D of t * int * int * t
  48. | AddI_D_D of t * int * int * t
  49. | AddI_D_C of t * int * int * t
  50. | AddI_C_D of t * int * int * t
  51. | Get_Slice_D of t * int list list
  52. | Set_Slice_D_D of t * t * int list list
  53. | Set_Slice_D_C of t * t * int list list
  54. | Set_Slice_C_D of t * t * int list list
  55. | Sum_D of t
  56. | Sum__D of t * int
  57. | Dot_D_D of t * t
  58. | Dot_D_C of t * t
  59. | Dot_C_D of t * t
  60. | Trans_D of t
  61. | L1Norm_D of t
  62. | L2Norm_D of t
  63. | L2NormS_D of t
  64. | Sigmoid_D of t
  65. | Relu_D of t
  66. | Inv_D of t
  67. | Add_Row_D_D of t * t * int
  68. | Add_Row_D_C of t * t * int
  69. | Add_Row_C_D of t * t * int
  70. | Get_Row_D of t * int
  71. | Of_Rows_D of t array
  72. | Concat_D_D of t * t * int
  73. | Concat_D_C of t * t * int
  74. | Concat_C_D of t * t * int
  75. | Conv1D_D_D of t * t * int array
  76. | Conv1D_D_C of t * t * int array
  77. | Conv1D_C_D of t * t * int array
  78. | Conv2D_D_D of t * t * int array
  79. | Conv2D_D_C of t * t * int array
  80. | Conv2D_C_D of t * t * int array
  81. | Conv3D_D_D of t * t * int array
  82. | Conv3D_D_C of t * t * int array
  83. | Conv3D_C_D of t * t * int array
  84. | Reshape_D of t
  85. | Maxpool1D_D of t * Owl_types.padding * int array * int array
  86. | Maxpool2D_D of t * Owl_types.padding * int array * int array
  87. | Maxpool3D_D of t * Owl_types.padding * int array * int array
  88. | Avgpool1D_D of t * Owl_types.padding * int array * int array
  89. | Avgpool2D_D of t * Owl_types.padding * int array * int array
  90. | Avgpool3D_D of t * Owl_types.padding * int array * int array
val _global_tag : int ref
val tag : unit -> int
val cmp_tag : 'a -> 'a -> int
val reset_zero : t -> t
val primal : t -> t
val primal' : t -> t
val zero : t -> t
val tangent : t -> t
val adjref : t -> t ref
val adjval : t -> t
val shape : t -> int array
val row_num : t -> int
val col_num : t -> int
val numel : t -> int
val clip_by_value : amin:Owl_dense_ndarray.D.elt -> amax:Owl_dense_ndarray.D.elt -> t -> t
val clip_by_l2norm : Owl_dense_ndarray.D.elt -> t -> t
val copy_primal' : t -> t
val tile : t -> int array -> t
val repeat : ?axis:int -> t -> int -> t
val pack_arr : arr -> t
val unpack_arr : t -> arr
val pack_flt : float -> t
val unpack_flt : t -> float
val deep_info : t -> string
val type_info : t -> string
val error_binop : string -> t -> t -> 'a
val error_uniop : string -> t -> 'a
module Maths : sig ... end
val reverse_reset : t -> unit
val reverse_push : t -> t -> unit
val reverse_prop : t -> t -> unit
val make_forward : t -> t -> int -> t
val make_reverse : t -> int -> t
val diff' : (t -> t) -> t -> t * t
val diff : (t -> t) -> t -> t
val grad' : (t -> t) -> t -> t * t
val grad : (t -> t) -> t -> t
val jacobianv' : (t -> t) -> t -> t -> t * t
val jacobianv : (t -> t) -> t -> t -> t
val jacobianTv' : (t -> t) -> t -> t -> t * t
val jacobianTv : (t -> t) -> t -> t -> t
val jacobian' : (t -> t) -> t -> t * t
val jacobian : (t -> t) -> t -> t
val gradhessian : (t -> t) -> t -> t * t
val gradhessian' : (t -> t) -> t -> t * t * t
val hessian : (t -> t) -> t -> t
val hessian' : (t -> t) -> t -> t * t
val gradhessianv' : (t -> t) -> t -> t -> t * t * t
val gradhessianv : (t -> t) -> t -> t -> t * t
val hessianv' : (t -> t) -> t -> t -> t * t
val hessianv : (t -> t) -> t -> t -> t
val laplacian : (t -> t) -> t -> t
val laplacian' : (t -> t) -> t -> t * t
module Mat : sig ... end
module Arr : sig ... end
val _traverse_trace : t list -> (t, int * string * t list) Hashtbl.t
val _convert_terminal_output : (t, int * string * t list) Hashtbl.t -> string
val _convert_dot_output : (t, int * string * t list) Hashtbl.t -> string
val to_trace : t list -> string
val to_dot : t list -> string
val pp_num : Format.formatter -> t -> unit
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(Owl_dense_ndarray.D).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