| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | !!!############################################################################# | ||
| 2 | !!! Code written by Ned Thaddeus Taylor | ||
| 3 | !!! Code part of the ATHENA library - a feedforward neural network library | ||
| 4 | !!!############################################################################# | ||
| 5 | !!! module contains implementation of the ReLU activation function | ||
| 6 | !!!############################################################################# | ||
| 7 | module activation_relu | ||
| 8 | use constants, only: real12 | ||
| 9 | use custom_types, only: activation_type | ||
| 10 | implicit none | ||
| 11 | |||
| 12 | type, extends(activation_type) :: relu_type | ||
| 13 | contains | ||
| 14 | procedure, pass(this) :: activate_1d => relu_activate_1d | ||
| 15 | procedure, pass(this) :: activate_2d => relu_activate_2d | ||
| 16 | procedure, pass(this) :: activate_3d => relu_activate_3d | ||
| 17 | procedure, pass(this) :: activate_4d => relu_activate_4d | ||
| 18 | procedure, pass(this) :: activate_5d => relu_activate_5d | ||
| 19 | procedure, pass(this) :: differentiate_1d => relu_differentiate_1d | ||
| 20 | procedure, pass(this) :: differentiate_2d => relu_differentiate_2d | ||
| 21 | procedure, pass(this) :: differentiate_3d => relu_differentiate_3d | ||
| 22 | procedure, pass(this) :: differentiate_4d => relu_differentiate_4d | ||
| 23 | procedure, pass(this) :: differentiate_5d => relu_differentiate_5d | ||
| 24 | end type relu_type | ||
| 25 | |||
| 26 | interface relu_setup | ||
| 27 | procedure initialise | ||
| 28 | end interface relu_setup | ||
| 29 | |||
| 30 | |||
| 31 | private | ||
| 32 | |||
| 33 | public :: relu_setup | ||
| 34 | |||
| 35 | |||
| 36 | contains | ||
| 37 | |||
| 38 | !!!############################################################################# | ||
| 39 | !!! initialisation | ||
| 40 | !!!############################################################################# | ||
| 41 | 4 | pure function initialise(scale) | |
| 42 | implicit none | ||
| 43 | type(relu_type) :: initialise | ||
| 44 | real(real12), optional, intent(in) :: scale | ||
| 45 | |||
| 46 | 4 | initialise%name = "relu" | |
| 47 | |||
| 48 |
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4 | if(present(scale))then |
| 49 | 4 | initialise%scale = scale | |
| 50 | else | ||
| 51 | ✗ | initialise%scale = 1._real12 | |
| 52 | end if | ||
| 53 | 4 | initialise%threshold = 0._real12 | |
| 54 | |||
| 55 | 4 | end function initialise | |
| 56 | !!!############################################################################# | ||
| 57 | |||
| 58 | |||
| 59 | !!!############################################################################# | ||
| 60 | !!! RELU transfer function | ||
| 61 | !!! f = max(0, x) | ||
| 62 | !!!############################################################################# | ||
| 63 |
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1 | pure function relu_activate_1d(this, val) result(output) |
| 64 | implicit none | ||
| 65 | class(relu_type), intent(in) :: this | ||
| 66 | real(real12), dimension(:), intent(in) :: val | ||
| 67 |
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1 | real(real12), dimension(size(val,dim=1)) :: output |
| 68 | |||
| 69 |
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2 | output = max(this%threshold, val) * this%scale |
| 70 |
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1 | end function relu_activate_1d |
| 71 | !!!----------------------------------------------------------------------------- | ||
| 72 | !!!----------------------------------------------------------------------------- | ||
| 73 |
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1 | pure function relu_activate_2d(this, val) result(output) |
| 74 | implicit none | ||
| 75 | class(relu_type), intent(in) :: this | ||
| 76 | real(real12), dimension(:,:), intent(in) :: val | ||
| 77 |
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2 | real(real12), dimension(size(val,1),size(val,2)) :: output |
| 78 | |||
| 79 |
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3 | output = max(this%threshold, val) * this%scale |
| 80 |
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2 | end function relu_activate_2d |
| 81 | !!!----------------------------------------------------------------------------- | ||
| 82 | !!!----------------------------------------------------------------------------- | ||
| 83 |
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1 | pure function relu_activate_3d(this, val) result(output) |
| 84 | implicit none | ||
| 85 | class(relu_type), intent(in) :: this | ||
| 86 | real(real12), dimension(:,:,:), intent(in) :: val | ||
| 87 |
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3 | real(real12), dimension(size(val,1),size(val,2),size(val,3)) :: output |
| 88 | |||
| 89 |
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4 | output = max(this%threshold, val) * this%scale |
| 90 |
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3 | end function relu_activate_3d |
| 91 | !!!----------------------------------------------------------------------------- | ||
| 92 | !!!----------------------------------------------------------------------------- | ||
| 93 |
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1 | pure function relu_activate_4d(this, val) result(output) |
| 94 | implicit none | ||
| 95 | class(relu_type), intent(in) :: this | ||
| 96 | real(real12), dimension(:,:,:,:), intent(in) :: val | ||
| 97 | real(real12), dimension(& | ||
| 98 |
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4 | size(val,1),size(val,2),size(val,3),size(val,4)) :: output |
| 99 | |||
| 100 |
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5 | output = max(this%threshold, val) * this%scale |
| 101 |
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4 | end function relu_activate_4d |
| 102 | !!!----------------------------------------------------------------------------- | ||
| 103 | !!!----------------------------------------------------------------------------- | ||
| 104 |
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1 | pure function relu_activate_5d(this, val) result(output) |
| 105 | implicit none | ||
| 106 | class(relu_type), intent(in) :: this | ||
| 107 | real(real12), dimension(:,:,:,:,:), intent(in) :: val | ||
| 108 | real(real12), dimension(& | ||
| 109 |
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|
5 | size(val,1),size(val,2),size(val,3),size(val,4),size(val,5)) :: output |
| 110 | |||
| 111 |
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|
6 | output = max(this%threshold, val) * this%scale |
| 112 |
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5 | end function relu_activate_5d |
| 113 | !!!############################################################################# | ||
| 114 | |||
| 115 | |||
| 116 | !!!############################################################################# | ||
| 117 | !!! derivative of RELU transfer function | ||
| 118 | !!! e.g. df/dx (1*x) = 1 | ||
| 119 | !!! we are performing the derivative to identify what weight ... | ||
| 120 | !!! ... results in the minimum error | ||
| 121 | !!!############################################################################# | ||
| 122 |
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1 | pure function relu_differentiate_1d(this, val) result(output) |
| 123 | implicit none | ||
| 124 | class(relu_type), intent(in) :: this | ||
| 125 | real(real12), dimension(:), intent(in) :: val | ||
| 126 |
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1 | real(real12), dimension(size(val,dim=1)) :: output |
| 127 | |||
| 128 |
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2 | where(val.ge.this%threshold) |
| 129 |
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1 | output = this%scale |
| 130 | elsewhere | ||
| 131 |
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1 | output = this%threshold |
| 132 | end where | ||
| 133 |
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1 | end function relu_differentiate_1d |
| 134 | !!!----------------------------------------------------------------------------- | ||
| 135 | !!!----------------------------------------------------------------------------- | ||
| 136 |
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1 | pure function relu_differentiate_2d(this, val) result(output) |
| 137 | implicit none | ||
| 138 | class(relu_type), intent(in) :: this | ||
| 139 | real(real12), dimension(:,:), intent(in) :: val | ||
| 140 |
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2 | real(real12), dimension(size(val,1),size(val,2)) :: output |
| 141 | |||
| 142 |
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3 | where(val.ge.this%threshold) |
| 143 |
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1 | output = this%scale |
| 144 | elsewhere | ||
| 145 |
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1 | output = this%threshold |
| 146 | end where | ||
| 147 |
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2 | end function relu_differentiate_2d |
| 148 | !!!----------------------------------------------------------------------------- | ||
| 149 | !!!----------------------------------------------------------------------------- | ||
| 150 |
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1 | pure function relu_differentiate_3d(this, val) result(output) |
| 151 | implicit none | ||
| 152 | class(relu_type), intent(in) :: this | ||
| 153 | real(real12), dimension(:,:,:), intent(in) :: val | ||
| 154 |
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3 | real(real12), dimension(size(val,1),size(val,2),size(val,3)) :: output |
| 155 | |||
| 156 |
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4 | where(val.ge.this%threshold) |
| 157 |
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1 | output = this%scale |
| 158 | elsewhere | ||
| 159 |
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1 | output = this%threshold |
| 160 | end where | ||
| 161 |
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3 | end function relu_differentiate_3d |
| 162 | !!!----------------------------------------------------------------------------- | ||
| 163 | !!!----------------------------------------------------------------------------- | ||
| 164 |
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1 | pure function relu_differentiate_4d(this, val) result(output) |
| 165 | implicit none | ||
| 166 | class(relu_type), intent(in) :: this | ||
| 167 | real(real12), dimension(:,:,:,:), intent(in) :: val | ||
| 168 | real(real12), dimension(& | ||
| 169 |
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4 | size(val,1),size(val,2),size(val,3),size(val,4)) :: output |
| 170 | |||
| 171 |
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5 | where(val.ge.this%threshold) |
| 172 |
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1 | output = this%scale |
| 173 | elsewhere | ||
| 174 |
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1 | output = this%threshold |
| 175 | end where | ||
| 176 |
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4 | end function relu_differentiate_4d |
| 177 | !!!----------------------------------------------------------------------------- | ||
| 178 | !!!----------------------------------------------------------------------------- | ||
| 179 |
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1 | pure function relu_differentiate_5d(this, val) result(output) |
| 180 | implicit none | ||
| 181 | class(relu_type), intent(in) :: this | ||
| 182 | real(real12), dimension(:,:,:,:,:), intent(in) :: val | ||
| 183 | real(real12), dimension(& | ||
| 184 |
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|
5 | size(val,1),size(val,2),size(val,3),size(val,4),size(val,5)) :: output |
| 185 | |||
| 186 |
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6 | where(val.ge.this%threshold) |
| 187 |
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1 | output = this%scale |
| 188 | elsewhere | ||
| 189 |
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1 | output = this%threshold |
| 190 | end where | ||
| 191 |
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5 | end function relu_differentiate_5d |
| 192 | !!!############################################################################# | ||
| 193 | |||
| 194 | 11 | end module activation_relu | |
| 195 |