| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | module athena__activation_gaussian | ||
| 2 | !! Module containing implementation of the Gaussian activation function | ||
| 3 | !! | ||
| 4 | !! This module implements the Gaussian (bell curve) activation, | ||
| 5 | !! which produces maximum activation at the origin. | ||
| 6 | !! | ||
| 7 | !! Mathematical operation: | ||
| 8 | !! \[ f(x) = \frac{1}{\sqrt{2\pi\sigma^2}} \exp\left(-\frac{(x-\mu)^2}{2\sigma^2}\right) \] | ||
| 9 | !! | ||
| 10 | !! Derivative: | ||
| 11 | !! \[ f'(x) = -\frac{x-\mu}{\sigma^3\sqrt{2\pi}} \exp\left(-\frac{(x-\mu)^2}{2\sigma^2}\right) \] | ||
| 12 | !! | ||
| 13 | !! Properties: Smooth, symmetric, max at \(x=\mu\) | ||
| 14 | !! Used in Radial Basis Function (RBF) networks | ||
| 15 | !! Responds strongly to inputs near \(\mu\) | ||
| 16 | use coreutils, only: real32, print_warning | ||
| 17 | use diffstruc, only: array_type, gaussian, operator(*) | ||
| 18 | use athena__misc_types, only: base_actv_type | ||
| 19 | use athena__misc_types, only: onnx_attribute_type | ||
| 20 | implicit none | ||
| 21 | |||
| 22 | |||
| 23 | private | ||
| 24 | |||
| 25 | public :: gaussian_actv_type, create_from_onnx_gaussian_activation | ||
| 26 | |||
| 27 | |||
| 28 | type, extends(base_actv_type) :: gaussian_actv_type | ||
| 29 | !! Type for Gaussian activation function with overloaded procedures | ||
| 30 | real(real32) :: sigma | ||
| 31 | !! Standard deviation parameter for Gaussian function | ||
| 32 | real(real32) :: mu | ||
| 33 | !! Mean parameter for Gaussian function | ||
| 34 | contains | ||
| 35 | procedure, pass(this) :: apply => apply_gaussian | ||
| 36 | procedure, pass(this) :: reset => reset_gaussian | ||
| 37 | procedure, pass(this) :: apply_attributes => apply_attributes_gaussian | ||
| 38 | procedure, pass(this) :: export_attributes => export_attributes_gaussian | ||
| 39 | end type gaussian_actv_type | ||
| 40 | |||
| 41 | interface gaussian_actv_type | ||
| 42 | procedure initialise | ||
| 43 | end interface gaussian_actv_type | ||
| 44 | |||
| 45 | |||
| 46 | |||
| 47 | contains | ||
| 48 | |||
| 49 | !############################################################################### | ||
| 50 | − | function initialise(scale, sigma, mu, attributes) result(activation) | |
| 51 | !! Initialise a Gaussian activation function | ||
| 52 | implicit none | ||
| 53 | |||
| 54 | ! Arguments | ||
| 55 | real(real32), intent(in), optional :: scale | ||
| 56 | !! Optional scale factor for activation output | ||
| 57 | real(real32), intent(in), optional :: sigma | ||
| 58 | !! Optional standard deviation parameter | ||
| 59 | real(real32), intent(in), optional :: mu | ||
| 60 | !! Optional mean parameter | ||
| 61 | type(onnx_attribute_type), dimension(:), intent(in), optional :: attributes | ||
| 62 | !! Optional array of ONNX attributes | ||
| 63 | type(gaussian_actv_type) :: activation | ||
| 64 | !! Gaussian activation type | ||
| 65 | |||
| 66 | |||
| 67 | − | call activation%reset() | |
| 68 | |||
| 69 | − | if(present(scale)) activation%scale = scale | |
| 70 | − | if(abs(activation%scale-1._real32) .gt. 1.e-6_real32)then | |
| 71 | − | activation%apply_scaling = .true. | |
| 72 | end if | ||
| 73 | |||
| 74 | − | if(present(sigma)) activation%sigma = sigma | |
| 75 | − | if(present(mu)) activation%mu = mu | |
| 76 | |||
| 77 | − | if(present(attributes)) then | |
| 78 | − | call activation%apply_attributes(attributes) | |
| 79 | end if | ||
| 80 | |||
| 81 | − | end function initialise | |
| 82 | !------------------------------------------------------------------------------- | ||
| 83 | − | pure subroutine reset_gaussian(this) | |
| 84 | !! Reset Gaussian activation function attributes and variables | ||
| 85 | implicit none | ||
| 86 | |||
| 87 | ! Arguments | ||
| 88 | class(gaussian_actv_type), intent(inout) :: this | ||
| 89 | !! Gaussian activation type | ||
| 90 | |||
| 91 | − | this%name = "gaussian" | |
| 92 | − | this%scale = 1._real32 | |
| 93 | − | this%threshold = 0._real32 | |
| 94 | − | this%apply_scaling = .false. | |
| 95 | − | this%sigma = 1.5_real32 | |
| 96 | − | this%mu = 0._real32 | |
| 97 | |||
| 98 | − | end subroutine reset_gaussian | |
| 99 | !------------------------------------------------------------------------------- | ||
| 100 | − | function create_from_onnx_gaussian_activation(attributes) result(activation) | |
| 101 | !! Create Gaussian activation function from ONNX attributes | ||
| 102 | implicit none | ||
| 103 | |||
| 104 | ! Arguments | ||
| 105 | type(onnx_attribute_type), dimension(:), intent(in) :: attributes | ||
| 106 | !! Array of ONNX attributes | ||
| 107 | |||
| 108 | class(base_actv_type), allocatable :: activation | ||
| 109 | !! Instance of activation type | ||
| 110 | |||
| 111 | − | allocate(activation, source = gaussian_actv_type(attributes = attributes)) | |
| 112 | |||
| 113 | − | end function create_from_onnx_gaussian_activation | |
| 114 | !############################################################################### | ||
| 115 | |||
| 116 | |||
| 117 | !############################################################################### | ||
| 118 | − | subroutine apply_attributes_gaussian(this, attributes) | |
| 119 | !! Load ONNX attributes into Gaussian activation function | ||
| 120 | implicit none | ||
| 121 | |||
| 122 | ! Arguments | ||
| 123 | class(gaussian_actv_type), intent(inout) :: this | ||
| 124 | !! Gaussian activation type | ||
| 125 | type(onnx_attribute_type), dimension(:), intent(in) :: attributes | ||
| 126 | !! Array of ONNX attributes | ||
| 127 | |||
| 128 | ! Local variables | ||
| 129 | integer :: i | ||
| 130 | !! Loop variable | ||
| 131 | |||
| 132 | ! Load provided attributes | ||
| 133 | − | do i=1, size(attributes,dim=1) | |
| 134 | − | select case(trim(attributes(i)%name)) | |
| 135 | case("scale") | ||
| 136 | − | read(attributes(i)%val,*) this%scale | |
| 137 | − | if(abs(this%scale-1._real32) .gt. 1.e-6_real32)then | |
| 138 | − | this%apply_scaling = .true. | |
| 139 | else | ||
| 140 | − | this%apply_scaling = .false. | |
| 141 | end if | ||
| 142 | case("sigma") | ||
| 143 | − | read(attributes(i)%val,*) this%sigma | |
| 144 | case("mu") | ||
| 145 | − | read(attributes(i)%val,*) this%mu | |
| 146 | case("name") | ||
| 147 | − | if(trim(attributes(i)%val) .ne. trim(this%name)) then | |
| 148 | call print_warning( & | ||
| 149 | 'Gaussian activation: name attribute "' // & | ||
| 150 | − | trim(attributes(i)%val) // & | |
| 151 | '"" does not match expected "' // trim(this%name)//'"' & | ||
| 152 | − | ) | |
| 153 | |||
| 154 | end if | ||
| 155 | case default | ||
| 156 | call print_warning( & | ||
| 157 | 'Gaussian activation: unknown attribute '// & | ||
| 158 | − | trim(attributes(i)%name) & | |
| 159 | − | ) | |
| 160 | end select | ||
| 161 | end do | ||
| 162 | |||
| 163 | − | end subroutine apply_attributes_gaussian | |
| 164 | !############################################################################### | ||
| 165 | |||
| 166 | |||
| 167 | !############################################################################### | ||
| 168 | − | pure function export_attributes_gaussian(this) result(attributes) | |
| 169 | !! Export Gaussian activation function attributes as ONNX attributes | ||
| 170 | implicit none | ||
| 171 | |||
| 172 | ! Arguments | ||
| 173 | class(gaussian_actv_type), intent(in) :: this | ||
| 174 | !! Gaussian activation type | ||
| 175 | type(onnx_attribute_type), allocatable, dimension(:) :: attributes | ||
| 176 | !! Array of ONNX attributes | ||
| 177 | |||
| 178 | ! Local variables | ||
| 179 | character(50) :: buffer | ||
| 180 | !! Temporary string buffer | ||
| 181 | |||
| 182 | − | allocate(attributes(4)) | |
| 183 | |||
| 184 | − | write(buffer, '(A)') this%name | |
| 185 | − | attributes(1) = onnx_attribute_type( & | |
| 186 | − | "name", "string", trim(adjustl(buffer)) ) | |
| 187 | |||
| 188 | − | write(buffer, '(F10.6)') this%scale | |
| 189 | − | attributes(2) = onnx_attribute_type( & | |
| 190 | − | "scale", "float", trim(adjustl(buffer)) ) | |
| 191 | |||
| 192 | − | write(buffer, '(F10.6)') this%sigma | |
| 193 | − | attributes(3) = onnx_attribute_type( & | |
| 194 | − | "sigma", "float", trim(adjustl(buffer)) ) | |
| 195 | |||
| 196 | − | write(buffer, '(F10.6)') this%mu | |
| 197 | − | attributes(4) = onnx_attribute_type( & | |
| 198 | − | "mu", "float", trim(adjustl(buffer)) ) | |
| 199 | |||
| 200 | − | end function export_attributes_gaussian | |
| 201 | !############################################################################### | ||
| 202 | |||
| 203 | |||
| 204 | !############################################################################### | ||
| 205 | − | function apply_gaussian(this, val) result(output) | |
| 206 | !! Apply Gaussian activation to array | ||
| 207 | !! | ||
| 208 | !! Applies the Gaussian function element-wise to input array: | ||
| 209 | !! f = exp(-x^2/(2σ^2))/(σ√(2π)) | ||
| 210 | implicit none | ||
| 211 | |||
| 212 | ! Arguments | ||
| 213 | class(gaussian_actv_type), intent(in) :: this | ||
| 214 | !! Gaussian activation type containing sigma parameter | ||
| 215 | type(array_type), intent(in) :: val | ||
| 216 | !! Input values | ||
| 217 | type(array_type), pointer :: output | ||
| 218 | !! Gaussian activated output values | ||
| 219 | |||
| 220 | − | if(this%apply_scaling)then | |
| 221 | − | output => gaussian(val, this%mu, this%sigma) * this%scale | |
| 222 | else | ||
| 223 | − | output => gaussian(val, this%mu, this%sigma) | |
| 224 | end if | ||
| 225 | |||
| 226 | − | end function apply_gaussian | |
| 227 | !############################################################################### | ||
| 228 | |||
| 229 | − | end module athena__activation_gaussian | |
| 230 |