| 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 a 3D batch normalisation layer | ||
| 6 | !!!############################################################################# | ||
| 7 | module batchnorm3d_layer | ||
| 8 | use constants, only: real12 | ||
| 9 | use base_layer, only: batch_layer_type, learnable_layer_type | ||
| 10 | use custom_types, only: initialiser_type | ||
| 11 | implicit none | ||
| 12 | |||
| 13 | |||
| 14 | type, extends(batch_layer_type) :: batchnorm3d_layer_type | ||
| 15 | real(real12), allocatable, dimension(:,:,:,:,:) :: output | ||
| 16 | real(real12), allocatable, dimension(:,:,:,:,:) :: di ! gradient of input (i.e. delta) | ||
| 17 | contains | ||
| 18 | procedure, pass(this) :: get_output => get_output_batchnorm3d | ||
| 19 | procedure, pass(this) :: init => init_batchnorm3d | ||
| 20 | procedure, pass(this) :: set_batch_size => set_batch_size_batchnorm3d | ||
| 21 | procedure, pass(this) :: print => print_batchnorm3d | ||
| 22 | |||
| 23 | procedure, pass(this) :: forward => forward_rank | ||
| 24 | procedure, pass(this) :: backward => backward_rank | ||
| 25 | procedure, private, pass(this) :: forward_5d | ||
| 26 | procedure, private, pass(this) :: backward_5d | ||
| 27 | |||
| 28 | procedure, pass(this) :: reduce => layer_reduction | ||
| 29 | procedure, pass(this) :: merge => layer_merge | ||
| 30 | procedure :: add_t_t => layer_add !t = type, r = real, i = int | ||
| 31 | generic :: operator(+) => add_t_t !, public | ||
| 32 | end type batchnorm3d_layer_type | ||
| 33 | |||
| 34 | |||
| 35 | interface batchnorm3d_layer_type | ||
| 36 | module function layer_setup( & | ||
| 37 | input_shape, batch_size, & | ||
| 38 | momentum, epsilon, & | ||
| 39 | gamma_init_mean, gamma_init_std, & | ||
| 40 | beta_init_mean, beta_init_std, & | ||
| 41 | kernel_initialiser, bias_initialiser, & | ||
| 42 | moving_mean_initialiser, moving_variance_initialiser & | ||
| 43 | ) result(layer) | ||
| 44 | integer, dimension(:), optional, intent(in) :: input_shape | ||
| 45 | integer, optional, intent(in) :: batch_size | ||
| 46 | real(real12), optional, intent(in) :: momentum, epsilon | ||
| 47 | real(real12), optional, intent(in) :: gamma_init_mean, gamma_init_std | ||
| 48 | real(real12), optional, intent(in) :: beta_init_mean, beta_init_std | ||
| 49 | character(*), optional, intent(in) :: & | ||
| 50 | kernel_initialiser, bias_initialiser, & | ||
| 51 | moving_mean_initialiser, moving_variance_initialiser | ||
| 52 | type(batchnorm3d_layer_type) :: layer | ||
| 53 | end function layer_setup | ||
| 54 | end interface batchnorm3d_layer_type | ||
| 55 | |||
| 56 | |||
| 57 | private | ||
| 58 | public :: batchnorm3d_layer_type | ||
| 59 | public :: read_batchnorm3d_layer | ||
| 60 | |||
| 61 | |||
| 62 | contains | ||
| 63 | |||
| 64 | !!!############################################################################# | ||
| 65 | !!! layer reduction | ||
| 66 | !!!############################################################################# | ||
| 67 | 1 | subroutine layer_reduction(this, rhs) | |
| 68 | implicit none | ||
| 69 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 70 | class(learnable_layer_type), intent(in) :: rhs | ||
| 71 | |||
| 72 | select type(rhs) | ||
| 73 | class is(batchnorm3d_layer_type) | ||
| 74 |
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2 | this%dg = this%dg + rhs%dg |
| 75 |
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3 | this%db = this%db + rhs%db |
| 76 | end select | ||
| 77 | |||
| 78 | 1 | end subroutine layer_reduction | |
| 79 | !!!############################################################################# | ||
| 80 | |||
| 81 | |||
| 82 | !!!############################################################################# | ||
| 83 | !!! layer addition | ||
| 84 | !!!############################################################################# | ||
| 85 | 1 | function layer_add(a, b) result(output) | |
| 86 | implicit none | ||
| 87 | class(batchnorm3d_layer_type), intent(in) :: a, b | ||
| 88 | type(batchnorm3d_layer_type) :: output | ||
| 89 | |||
| 90 |
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|
1 | output = a |
| 91 |
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2 | output%dg = output%dg + b%dg |
| 92 |
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2 | output%db = output%db + b%db |
| 93 | |||
| 94 |
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2 | end function layer_add |
| 95 | !!!############################################################################# | ||
| 96 | |||
| 97 | |||
| 98 | !!!############################################################################# | ||
| 99 | !!! layer merge | ||
| 100 | !!!############################################################################# | ||
| 101 | 1 | subroutine layer_merge(this, input) | |
| 102 | implicit none | ||
| 103 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 104 | class(learnable_layer_type), intent(in) :: input | ||
| 105 | |||
| 106 | select type(input) | ||
| 107 | class is(batchnorm3d_layer_type) | ||
| 108 |
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2 | this%dg = this%dg + input%dg |
| 109 |
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3 | this%db = this%db + input%db |
| 110 | end select | ||
| 111 | |||
| 112 | 1 | end subroutine layer_merge | |
| 113 | !!!############################################################################# | ||
| 114 | |||
| 115 | |||
| 116 | !!!##########################################################################!!! | ||
| 117 | !!! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * !!! | ||
| 118 | !!!##########################################################################!!! | ||
| 119 | |||
| 120 | |||
| 121 | !!!############################################################################# | ||
| 122 | !!! get layer outputs | ||
| 123 | !!!############################################################################# | ||
| 124 | 4 | pure subroutine get_output_batchnorm3d(this, output) | |
| 125 | implicit none | ||
| 126 | class(batchnorm3d_layer_type), intent(in) :: this | ||
| 127 | real(real12), allocatable, dimension(..), intent(out) :: output | ||
| 128 | |||
| 129 | select rank(output) | ||
| 130 | rank(1) | ||
| 131 |
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7 | output = reshape(this%output, [size(this%output)]) |
| 132 | rank(2) | ||
| 133 | output = & | ||
| 134 |
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7 | reshape(this%output, [product(this%output_shape),this%batch_size]) |
| 135 | rank(5) | ||
| 136 |
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|
3514 | output = this%output |
| 137 | end select | ||
| 138 | |||
| 139 | 4 | end subroutine get_output_batchnorm3d | |
| 140 | !!!############################################################################# | ||
| 141 | |||
| 142 | |||
| 143 | !!!##########################################################################!!! | ||
| 144 | !!! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * !!! | ||
| 145 | !!!##########################################################################!!! | ||
| 146 | |||
| 147 | |||
| 148 | |||
| 149 | !!!############################################################################# | ||
| 150 | !!! forward propagation assumed rank handler | ||
| 151 | !!!############################################################################# | ||
| 152 | 2 | pure subroutine forward_rank(this, input) | |
| 153 | implicit none | ||
| 154 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 155 | real(real12), dimension(..), intent(in) :: input | ||
| 156 | |||
| 157 | select rank(input); rank(5) | ||
| 158 | 2 | call forward_5d(this, input) | |
| 159 | end select | ||
| 160 | 2 | end subroutine forward_rank | |
| 161 | !!!############################################################################# | ||
| 162 | |||
| 163 | |||
| 164 | !!!############################################################################# | ||
| 165 | !!! backward propagation assumed rank handler | ||
| 166 | !!!############################################################################# | ||
| 167 | 1 | pure subroutine backward_rank(this, input, gradient) | |
| 168 | implicit none | ||
| 169 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 170 | real(real12), dimension(..), intent(in) :: input | ||
| 171 | real(real12), dimension(..), intent(in) :: gradient | ||
| 172 | |||
| 173 | select rank(input); rank(5) | ||
| 174 | 1 | select rank(gradient); rank(5) | |
| 175 | 1 | call backward_5d(this, input, gradient) | |
| 176 | end select | ||
| 177 | end select | ||
| 178 | 1 | end subroutine backward_rank | |
| 179 | !!!############################################################################# | ||
| 180 | |||
| 181 | |||
| 182 | !!!##########################################################################!!! | ||
| 183 | !!! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * !!! | ||
| 184 | !!!##########################################################################!!! | ||
| 185 | |||
| 186 | |||
| 187 | !!!############################################################################# | ||
| 188 | !!! set up layer | ||
| 189 | !!!############################################################################# | ||
| 190 | 3 | module function layer_setup( & | |
| 191 |
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3 | input_shape, batch_size, & |
| 192 | momentum, epsilon, & | ||
| 193 | gamma_init_mean, gamma_init_std, & | ||
| 194 | beta_init_mean, beta_init_std, & | ||
| 195 | kernel_initialiser, bias_initialiser, & | ||
| 196 | moving_mean_initialiser, moving_variance_initialiser & | ||
| 197 | ) result(layer) | ||
| 198 | use initialiser, only: get_default_initialiser | ||
| 199 | implicit none | ||
| 200 | integer, dimension(:), optional, intent(in) :: input_shape | ||
| 201 | integer, optional, intent(in) :: batch_size | ||
| 202 | real(real12), optional, intent(in) :: momentum, epsilon | ||
| 203 | real(real12), optional, intent(in) :: gamma_init_mean, gamma_init_std | ||
| 204 | real(real12), optional, intent(in) :: beta_init_mean, beta_init_std | ||
| 205 | character(*), optional, intent(in) :: & | ||
| 206 | kernel_initialiser, bias_initialiser, & | ||
| 207 | moving_mean_initialiser, moving_variance_initialiser | ||
| 208 | |||
| 209 | type(batchnorm3d_layer_type) :: layer | ||
| 210 | |||
| 211 | |||
| 212 |
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3 | layer%name = "batchnorm3d" |
| 213 | 3 | layer%input_rank = 4 | |
| 214 | !!-------------------------------------------------------------------------- | ||
| 215 | !! initialise batch size | ||
| 216 | !!-------------------------------------------------------------------------- | ||
| 217 |
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3 | if(present(batch_size)) layer%batch_size = batch_size |
| 218 | |||
| 219 | |||
| 220 | !!-------------------------------------------------------------------------- | ||
| 221 | !! set up momentum and epsilon | ||
| 222 | !!-------------------------------------------------------------------------- | ||
| 223 |
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3 | if(present(momentum))then |
| 224 | 1 | layer%momentum = momentum | |
| 225 | else | ||
| 226 | 2 | layer%momentum = 0._real12 | |
| 227 | end if | ||
| 228 |
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3 | if(present(epsilon))then |
| 229 | 1 | layer%epsilon = epsilon | |
| 230 | else | ||
| 231 | 2 | layer%epsilon = 1.E-5_real12 | |
| 232 | end if | ||
| 233 | |||
| 234 | |||
| 235 | !!-------------------------------------------------------------------------- | ||
| 236 | !! set up initialiser mean and standard deviations | ||
| 237 | !!-------------------------------------------------------------------------- | ||
| 238 |
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3 | if(present(gamma_init_mean)) layer%gamma_init_mean = gamma_init_mean |
| 239 |
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3 | if(present(gamma_init_std)) layer%gamma_init_std = gamma_init_std |
| 240 |
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3 | if(present(beta_init_mean)) layer%beta_init_mean = beta_init_mean |
| 241 |
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3 | if(present(beta_init_std)) layer%beta_init_std = beta_init_std |
| 242 | |||
| 243 | |||
| 244 | !!-------------------------------------------------------------------------- | ||
| 245 | !! define gamma and beta initialisers | ||
| 246 | !!-------------------------------------------------------------------------- | ||
| 247 |
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3 | if(present(kernel_initialiser)) layer%kernel_initialiser = kernel_initialiser |
| 248 |
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3 | if(trim(layer%kernel_initialiser).eq.'') & |
| 249 | 2 | layer%kernel_initialiser = 'ones' | |
| 250 | !get_default_initialiser("batch") | ||
| 251 | write(*,'("BATCHNORM3D kernel (gamma) initialiser: ",A)') & | ||
| 252 |
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3 | trim(layer%kernel_initialiser) |
| 253 |
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3 | if(present(bias_initialiser)) layer%bias_initialiser = bias_initialiser |
| 254 |
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3 | if(trim(layer%bias_initialiser).eq.'') & |
| 255 | 2 | layer%bias_initialiser = 'zeros' | |
| 256 | !get_default_initialiser("batch") | ||
| 257 | write(*,'("BATCHNORM3D bias (beta) initialiser: ",A)') & | ||
| 258 |
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3 | trim(layer%bias_initialiser) |
| 259 | |||
| 260 |
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3 | if(present(moving_mean_initialiser)) & |
| 261 |
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1 | layer%moving_mean_initialiser = moving_mean_initialiser |
| 262 |
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3 | if(trim(layer%moving_mean_initialiser).eq.'') & |
| 263 | 2 | layer%moving_mean_initialiser = 'zeros' | |
| 264 | !get_default_initialiser("batch") | ||
| 265 | write(*,'("BATCHNORM3D moving mean initialiser: ",A)') & | ||
| 266 |
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3 | trim(layer%moving_mean_initialiser) |
| 267 |
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3 | if(present(moving_variance_initialiser)) & |
| 268 |
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1 | layer%moving_variance_initialiser = moving_variance_initialiser |
| 269 |
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3 | if(trim(layer%moving_variance_initialiser).eq.'') & |
| 270 | 2 | layer%moving_variance_initialiser = 'ones' | |
| 271 | !get_default_initialiser("batch") | ||
| 272 | write(*,'("BATCHNORM3D moving variance initialiser: ",A)') & | ||
| 273 |
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3 | trim(layer%moving_variance_initialiser) |
| 274 | |||
| 275 | |||
| 276 | !!-------------------------------------------------------------------------- | ||
| 277 | !! initialise layer shape | ||
| 278 | !!-------------------------------------------------------------------------- | ||
| 279 |
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3 | if(present(input_shape)) call layer%init(input_shape=input_shape) |
| 280 | |||
| 281 |
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6 | end function layer_setup |
| 282 | !!!############################################################################# | ||
| 283 | |||
| 284 | |||
| 285 | !!!############################################################################# | ||
| 286 | !!! initialise layer | ||
| 287 | !!!############################################################################# | ||
| 288 |
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3 | subroutine init_batchnorm3d(this, input_shape, batch_size, verbose) |
| 289 | use initialiser, only: initialiser_setup | ||
| 290 | implicit none | ||
| 291 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 292 | integer, dimension(:), intent(in) :: input_shape | ||
| 293 | integer, optional, intent(in) :: batch_size | ||
| 294 | integer, optional, intent(in) :: verbose | ||
| 295 | |||
| 296 | integer :: verbose_ = 0 | ||
| 297 | 6 | class(initialiser_type), allocatable :: t_initialiser | |
| 298 | |||
| 299 | |||
| 300 | !!-------------------------------------------------------------------------- | ||
| 301 | !! initialise optional arguments | ||
| 302 | !!-------------------------------------------------------------------------- | ||
| 303 |
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3 | if(present(verbose)) verbose_ = verbose |
| 304 |
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3 | if(present(batch_size)) this%batch_size = batch_size |
| 305 | |||
| 306 | |||
| 307 | !!-------------------------------------------------------------------------- | ||
| 308 | !! initialise input shape | ||
| 309 | !!-------------------------------------------------------------------------- | ||
| 310 |
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3 | if(.not.allocated(this%input_shape)) call this%set_shape(input_shape) |
| 311 | |||
| 312 | |||
| 313 | !!----------------------------------------------------------------------- | ||
| 314 | !! set up number of channels, width, height | ||
| 315 | !!----------------------------------------------------------------------- | ||
| 316 |
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15 | this%output_shape = this%input_shape |
| 317 |
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3 | this%num_channels = this%input_shape(this%input_rank) |
| 318 | |||
| 319 | |||
| 320 | !!----------------------------------------------------------------------- | ||
| 321 | !! allocate mean, variance, gamma, beta, dg, db | ||
| 322 | !!----------------------------------------------------------------------- | ||
| 323 |
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8 | allocate(this%mean(this%num_channels), source=0._real12) |
| 324 |
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8 | allocate(this%variance, source=this%mean) |
| 325 |
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8 | allocate(this%gamma, source=this%mean) |
| 326 |
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8 | allocate(this%beta, source=this%mean) |
| 327 |
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8 | allocate(this%dg, source=this%mean) |
| 328 |
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8 | allocate(this%db, source=this%mean) |
| 329 | |||
| 330 | |||
| 331 | !!----------------------------------------------------------------------- | ||
| 332 | !! initialise gamma | ||
| 333 | !!----------------------------------------------------------------------- | ||
| 334 |
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6 | allocate(t_initialiser, source=initialiser_setup(this%kernel_initialiser)) |
| 335 | 3 | t_initialiser%mean = this%gamma_init_mean | |
| 336 | 3 | t_initialiser%std = this%gamma_init_std | |
| 337 | 12 | call t_initialiser%initialise(this%gamma, & | |
| 338 | fan_in =this%num_channels, & | ||
| 339 |
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3 | fan_out=this%num_channels) |
| 340 |
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3 | deallocate(t_initialiser) |
| 341 | |||
| 342 | !! initialise beta | ||
| 343 | !!----------------------------------------------------------------------- | ||
| 344 |
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6 | allocate(t_initialiser, source=initialiser_setup(this%bias_initialiser)) |
| 345 | 3 | t_initialiser%mean = this%beta_init_mean | |
| 346 | 3 | t_initialiser%std = this%beta_init_std | |
| 347 | 12 | call t_initialiser%initialise(this%beta, & | |
| 348 | fan_in =this%num_channels, & | ||
| 349 |
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3 | fan_out=this%num_channels) |
| 350 |
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3 | deallocate(t_initialiser) |
| 351 | |||
| 352 | |||
| 353 | !!----------------------------------------------------------------------- | ||
| 354 | !! initialise moving mean | ||
| 355 | !!----------------------------------------------------------------------- | ||
| 356 | ✗ | allocate(t_initialiser, & | |
| 357 |
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6 | source=initialiser_setup(this%moving_mean_initialiser)) |
| 358 | 12 | call t_initialiser%initialise(this%mean, & | |
| 359 | fan_in =this%num_channels, & | ||
| 360 |
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3 | fan_out=this%num_channels) |
| 361 |
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3 | deallocate(t_initialiser) |
| 362 | |||
| 363 | !! initialise moving variance | ||
| 364 | !!----------------------------------------------------------------------- | ||
| 365 | ✗ | allocate(t_initialiser, & | |
| 366 |
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6 | source=initialiser_setup(this%moving_variance_initialiser)) |
| 367 | 12 | call t_initialiser%initialise(this%variance, & | |
| 368 | fan_in =this%num_channels, & | ||
| 369 |
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3 | fan_out=this%num_channels) |
| 370 |
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3 | deallocate(t_initialiser) |
| 371 | |||
| 372 | |||
| 373 | !!-------------------------------------------------------------------------- | ||
| 374 | !! initialise batch size-dependent arrays | ||
| 375 | !!-------------------------------------------------------------------------- | ||
| 376 |
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3 | if(this%batch_size.gt.0) call this%set_batch_size(this%batch_size) |
| 377 | |||
| 378 |
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15 | end subroutine init_batchnorm3d |
| 379 | !!!############################################################################# | ||
| 380 | |||
| 381 | |||
| 382 | !!!############################################################################# | ||
| 383 | !!! set batch size | ||
| 384 | !!!############################################################################# | ||
| 385 | 3 | subroutine set_batch_size_batchnorm3d(this, batch_size, verbose) | |
| 386 | implicit none | ||
| 387 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 388 | integer, intent(in) :: batch_size | ||
| 389 | integer, optional, intent(in) :: verbose | ||
| 390 | |||
| 391 | integer :: verbose_ = 0 | ||
| 392 | |||
| 393 | |||
| 394 | !!-------------------------------------------------------------------------- | ||
| 395 | !! initialise optional arguments | ||
| 396 | !!-------------------------------------------------------------------------- | ||
| 397 |
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3 | if(present(verbose)) verbose_ = verbose |
| 398 | 3 | this%batch_size = batch_size | |
| 399 | |||
| 400 | |||
| 401 | !!-------------------------------------------------------------------------- | ||
| 402 | !! set norm | ||
| 403 | !!-------------------------------------------------------------------------- | ||
| 404 | this%norm = real( & | ||
| 405 | this%batch_size * & | ||
| 406 |
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12 | product(this%input_shape(1:this%input_rank-1) ),real12) |
| 407 | |||
| 408 | |||
| 409 | !!-------------------------------------------------------------------------- | ||
| 410 | !! allocate arrays | ||
| 411 | !!-------------------------------------------------------------------------- | ||
| 412 |
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3 | if(allocated(this%input_shape))then |
| 413 |
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3 | if(allocated(this%output)) deallocate(this%output) |
| 414 | ✗ | allocate(this%output( & | |
| 415 | 6 | this%output_shape(1), & | |
| 416 | 6 | this%output_shape(2), & | |
| 417 | 6 | this%output_shape(3), this%num_channels, & | |
| 418 | this%batch_size), & | ||
| 419 |
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|
1791 | source=0._real12) |
| 420 |
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3 | if(allocated(this%di)) deallocate(this%di) |
| 421 |
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|
1791 | allocate(this%di, source=this%output) |
| 422 | end if | ||
| 423 | |||
| 424 | 3 | end subroutine set_batch_size_batchnorm3d | |
| 425 | !!!############################################################################# | ||
| 426 | |||
| 427 | |||
| 428 | !!!##########################################################################!!! | ||
| 429 | !!! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * !!! | ||
| 430 | !!!##########################################################################!!! | ||
| 431 | |||
| 432 | |||
| 433 | !!!############################################################################# | ||
| 434 | !!! print layer to file | ||
| 435 | !!!############################################################################# | ||
| 436 | ✗ | subroutine print_batchnorm3d(this, file) | |
| 437 | implicit none | ||
| 438 | class(batchnorm3d_layer_type), intent(in) :: this | ||
| 439 | character(*), intent(in) :: file | ||
| 440 | |||
| 441 | integer :: unit | ||
| 442 | integer :: m | ||
| 443 | |||
| 444 | !! open file with new unit | ||
| 445 | !!-------------------------------------------------------------------------- | ||
| 446 | ✗ | open(newunit=unit, file=trim(file), access='append') | |
| 447 | |||
| 448 | !! write convolution initial parameters | ||
| 449 | !!-------------------------------------------------------------------------- | ||
| 450 | ✗ | write(unit,'("BATCHNORM3D")') | |
| 451 | ✗ | write(unit,'(3X,"INPUT_SHAPE = ",3(1X,I0))') this%input_shape | |
| 452 | ✗ | write(unit,'(3X,"MOMENTUM = ",F0.9)') this%momentum | |
| 453 | ✗ | write(unit,'(3X,"EPSILON = ",F0.9)') this%epsilon | |
| 454 | ✗ | write(unit,'(3X,"NUM_CHANNELS = ",I0)') this%num_channels | |
| 455 | ✗ | write(unit,'("GAMMA")') | |
| 456 | ✗ | do m=1,this%num_channels | |
| 457 | ✗ | write(unit,'(5(E16.8E2))') this%gamma(m) | |
| 458 | end do | ||
| 459 | ✗ | write(unit,'("END GAMMA")') | |
| 460 | ✗ | write(unit,'("BETA")') | |
| 461 | ✗ | do m=1,this%num_channels | |
| 462 | ✗ | write(unit,'(5(E16.8E2))') this%beta(m) | |
| 463 | end do | ||
| 464 | ✗ | write(unit,'("END BETA")') | |
| 465 | ✗ | write(unit,'("END BATCHNORM3D")') | |
| 466 | |||
| 467 | !! close unit | ||
| 468 | !!-------------------------------------------------------------------------- | ||
| 469 | ✗ | close(unit) | |
| 470 | |||
| 471 | ✗ | end subroutine print_batchnorm3d | |
| 472 | !!!############################################################################# | ||
| 473 | |||
| 474 | |||
| 475 | !!!############################################################################# | ||
| 476 | !!! read layer from file | ||
| 477 | !!!############################################################################# | ||
| 478 | ✗ | function read_batchnorm3d_layer(unit, verbose) result(layer) | |
| 479 | use infile_tools, only: assign_val, assign_vec | ||
| 480 | use misc, only: to_lower, icount | ||
| 481 | implicit none | ||
| 482 | integer, intent(in) :: unit | ||
| 483 | integer, optional, intent(in) :: verbose | ||
| 484 | |||
| 485 | class(batchnorm3d_layer_type), allocatable :: layer | ||
| 486 | |||
| 487 | integer :: stat, verbose_ = 0 | ||
| 488 | integer :: itmp1, c, i, j, k | ||
| 489 | integer :: num_channels | ||
| 490 | real(real12) :: momentum = 0._real12, epsilon = 1.E-5_real12 | ||
| 491 | logical :: found_gamma=.false., found_beta=.false. | ||
| 492 | character(14) :: kernel_initialiser='', bias_initialiser='' | ||
| 493 | character(256) :: buffer, tag | ||
| 494 | |||
| 495 | integer, dimension(3) :: input_shape | ||
| 496 | ✗ | real(real12), allocatable, dimension(:) :: data_list | |
| 497 | |||
| 498 | |||
| 499 | !!-------------------------------------------------------------------------- | ||
| 500 | !! initialise optional arguments | ||
| 501 | !!-------------------------------------------------------------------------- | ||
| 502 | ✗ | if(present(verbose)) verbose_ = verbose | |
| 503 | |||
| 504 | |||
| 505 | !!-------------------------------------------------------------------------- | ||
| 506 | !! loop over tags in layer card | ||
| 507 | !!-------------------------------------------------------------------------- | ||
| 508 | ✗ | tag_loop: do | |
| 509 | |||
| 510 | !! check for end of file | ||
| 511 | ✗ | read(unit,'(A)',iostat=stat) buffer | |
| 512 | ✗ | if(stat.ne.0)then | |
| 513 | ✗ | write(0,*) "ERROR: file encountered error (EoF?) before END BATCHNORM3D" | |
| 514 | ✗ | stop "Exiting..." | |
| 515 | end if | ||
| 516 | ✗ | if(trim(adjustl(buffer)).eq."") cycle tag_loop | |
| 517 | |||
| 518 | !! check for end of convolution card | ||
| 519 | ✗ | if(trim(adjustl(buffer)).eq."END BATCHNORM3D")then | |
| 520 | ✗ | backspace(unit) | |
| 521 | ✗ | exit tag_loop | |
| 522 | end if | ||
| 523 | |||
| 524 | ✗ | tag=trim(adjustl(buffer)) | |
| 525 | ✗ | if(scan(buffer,"=").ne.0) tag=trim(tag(:scan(tag,"=")-1)) | |
| 526 | |||
| 527 | !! read parameters from save file | ||
| 528 | ✗ | select case(trim(tag)) | |
| 529 | case("INPUT_SHAPE") | ||
| 530 | ✗ | call assign_vec(buffer, input_shape, itmp1) | |
| 531 | case("MOMENTUM") | ||
| 532 | ✗ | call assign_val(buffer, momentum, itmp1) | |
| 533 | case("EPSILON") | ||
| 534 | ✗ | call assign_val(buffer, epsilon, itmp1) | |
| 535 | case("KERNEL_INITIALISER") | ||
| 536 | ✗ | call assign_val(buffer, kernel_initialiser, itmp1) | |
| 537 | case("BIAS_INITIALISER") | ||
| 538 | ✗ | call assign_val(buffer, bias_initialiser, itmp1) | |
| 539 | case("GAMMA") | ||
| 540 | ✗ | found_gamma = .true. | |
| 541 | ✗ | kernel_initialiser = 'zeros' | |
| 542 | ✗ | bias_initialiser = 'zeros' | |
| 543 | ✗ | exit tag_loop | |
| 544 | case("beta") | ||
| 545 | ✗ | found_beta = .true. | |
| 546 | ✗ | kernel_initialiser = 'zeros' | |
| 547 | ✗ | bias_initialiser = 'zeros' | |
| 548 | ✗ | exit tag_loop | |
| 549 | case default | ||
| 550 | !! don't look for "e" due to scientific notation of numbers | ||
| 551 | !! ... i.e. exponent (E+00) | ||
| 552 | ✗ | if(scan(to_lower(trim(adjustl(buffer))),& | |
| 553 | 'abcdfghijklmnopqrstuvwxyz').eq.0)then | ||
| 554 | ✗ | cycle tag_loop | |
| 555 | ✗ | elseif(tag(:3).eq.'END')then | |
| 556 | ✗ | cycle tag_loop | |
| 557 | end if | ||
| 558 | ✗ | stop "Unrecognised line in input file: "//trim(adjustl(buffer)) | |
| 559 | end select | ||
| 560 | end do tag_loop | ||
| 561 | |||
| 562 | |||
| 563 | !!-------------------------------------------------------------------------- | ||
| 564 | !! set transfer activation function | ||
| 565 | !!-------------------------------------------------------------------------- | ||
| 566 | ✗ | num_channels = input_shape(size(input_shape,1)) | |
| 567 | layer = batchnorm3d_layer_type( input_shape=input_shape, & | ||
| 568 | momentum = momentum, epsilon = epsilon & | ||
| 569 | ✗ | ) | |
| 570 | |||
| 571 | |||
| 572 | !!-------------------------------------------------------------------------- | ||
| 573 | !! check if WEIGHTS card was found | ||
| 574 | !!-------------------------------------------------------------------------- | ||
| 575 | ✗ | allocate(data_list(num_channels), source=0._real12) | |
| 576 | ✗ | do i=1,2 | |
| 577 | ✗ | if(found_gamma.or.found_beta)then | |
| 578 | ✗ | c = 1 | |
| 579 | ✗ | k = 1 | |
| 580 | ✗ | data_list = 0._real12 | |
| 581 | ✗ | data_concat_loop: do while(c.le.num_channels) | |
| 582 | ✗ | read(unit,'(A)',iostat=stat) buffer | |
| 583 | ✗ | if(stat.ne.0) exit data_concat_loop | |
| 584 | ✗ | k = icount(buffer) | |
| 585 | ✗ | read(buffer,*,iostat=stat) (data_list(j),j=c,c+k-1) | |
| 586 | ✗ | c = c + k | |
| 587 | end do data_concat_loop | ||
| 588 | ✗ | if(found_gamma)then | |
| 589 | ✗ | layer%gamma = data_list | |
| 590 | ✗ | found_gamma = .false. | |
| 591 | ✗ | elseif(found_beta)then | |
| 592 | ✗ | layer%beta = data_list | |
| 593 | ✗ | found_beta = .false. | |
| 594 | end if | ||
| 595 | ✗ | read(unit,'(A)',iostat=stat) buffer | |
| 596 | ✗ | if(index(trim(adjustl(buffer)),"GAMMA").eq.1) found_gamma = .true. | |
| 597 | ✗ | if(index(trim(adjustl(buffer)),"BETA").eq.1) found_beta = .true. | |
| 598 | end if | ||
| 599 | end do | ||
| 600 | ✗ | deallocate(data_list) | |
| 601 | |||
| 602 | |||
| 603 | !! check for end of layer card | ||
| 604 | !!----------------------------------------------------------------------- | ||
| 605 | ✗ | read(unit,'(A)') buffer | |
| 606 | ✗ | if(trim(adjustl(buffer)).ne."END BATCHNORM3D")then | |
| 607 | ✗ | write(*,*) trim(adjustl(buffer)) | |
| 608 | ✗ | stop "ERROR: END BATCHNORM3D not where expected" | |
| 609 | end if | ||
| 610 | |||
| 611 | ✗ | end function read_batchnorm3d_layer | |
| 612 | !!!############################################################################# | ||
| 613 | |||
| 614 | |||
| 615 | !!!##########################################################################!!! | ||
| 616 | !!! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * !!! | ||
| 617 | !!!##########################################################################!!! | ||
| 618 | |||
| 619 | |||
| 620 | !!!############################################################################# | ||
| 621 | !!! forward propagation | ||
| 622 | !!!############################################################################# | ||
| 623 | 14 | pure subroutine forward_5d(this, input) | |
| 624 | implicit none | ||
| 625 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 626 |
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2 | real(real12), dimension( & |
| 627 |
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2 | this%input_shape(1), & |
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2 | this%input_shape(2), & |
| 629 | this%input_shape(3), & | ||
| 630 | this%num_channels,this%batch_size), & | ||
| 631 | intent(in) :: input | ||
| 632 | |||
| 633 | integer :: m | ||
| 634 | 4 | real(real12), dimension(this%num_channels) :: t_mean, t_variance | |
| 635 | |||
| 636 | |||
| 637 | 2 | select case(this%inference) | |
| 638 | case(.true.) | ||
| 639 | ✗ | do concurrent(m=1:this%num_channels) | |
| 640 | !! normalize each feature | ||
| 641 | ✗ | this%output(:,:,:,m,:) = this%gamma(m) * (input(:,:,:,m,:) - & | |
| 642 | ✗ | this%mean(m)) / & | |
| 643 | sqrt( & | ||
| 644 | ✗ | this%batch_size / (this%batch_size - 1) * this%variance(m) + & | |
| 645 | this%epsilon) + & | ||
| 646 | ✗ | this%beta(m) | |
| 647 | end do | ||
| 648 | case default | ||
| 649 |
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2 | do concurrent(m=1:this%num_channels) |
| 650 | !! calculate current mean and variance | ||
| 651 |
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3516 | t_mean(m) = sum(input(:,:,:,m,:)) / this%norm |
| 652 |
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|
3516 | t_variance(m) = sum((input(:,:,:,m,:) - t_mean(m))**2._real12) / this%norm |
| 653 | |||
| 654 | !! CONVERT TO USING inverse square root of variance (i.e. inverse std) | ||
| 655 | !! would also need to include epsilon in the sqrt denominator | ||
| 656 | |||
| 657 | !! update running averages | ||
| 658 |
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6 | if(this%momentum.ne.0._real12)then |
| 659 | ✗ | this%mean(m) = this%momentum * this%mean(m) + & | |
| 660 | ✗ | (1._real12 - this%momentum) * t_mean(m) | |
| 661 | ✗ | this%variance(m) = this%momentum * this%variance(m) + & | |
| 662 | ✗ | (1._real12 - this%momentum) * t_variance(m) | |
| 663 | else | ||
| 664 |
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6 | this%mean(m) = t_mean(m) |
| 665 |
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6 | this%variance(m) = t_variance(m) |
| 666 | end if | ||
| 667 | |||
| 668 | !! normalize each feature | ||
| 669 |
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6 | this%output(:,:,:,m,:) = this%gamma(m) * (input(:,:,:,m,:) - & |
| 670 | 12 | this%mean(m)) / & | |
| 671 |
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|
3524 | sqrt(this%variance(m) + this%epsilon) + this%beta(m) |
| 672 | end do | ||
| 673 | end select | ||
| 674 | |||
| 675 | 2 | end subroutine forward_5d | |
| 676 | !!!############################################################################# | ||
| 677 | |||
| 678 | |||
| 679 | !!!############################################################################# | ||
| 680 | !!! backward propagation | ||
| 681 | !!!############################################################################# | ||
| 682 | 13 | pure subroutine backward_5d(this, input, gradient) | |
| 683 | implicit none | ||
| 684 | class(batchnorm3d_layer_type), intent(inout) :: this | ||
| 685 |
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1 | real(real12), dimension( & |
| 686 |
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1 | this%input_shape(1), & |
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1 | this%input_shape(2), & |
| 688 | this%input_shape(3), & | ||
| 689 | this%num_channels,this%batch_size), & | ||
| 690 | intent(in) :: input | ||
| 691 |
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1 | real(real12), dimension( & |
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1 | this%output_shape(1), & |
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1 | this%output_shape(2), & |
| 694 | this%output_shape(3), & | ||
| 695 | this%num_channels,this%batch_size), & | ||
| 696 | intent(in) :: gradient | ||
| 697 | |||
| 698 | integer :: m | ||
| 699 | 4 | real(real12), dimension( & | |
| 700 | 4 | this%input_shape(1), & | |
| 701 | 4 | this%input_shape(2), & | |
| 702 | this%input_shape(3), & | ||
| 703 |
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|
1 | this%num_channels,this%batch_size) :: x_hat, dx_hat |
| 704 | |||
| 705 | |||
| 706 | 1 | do concurrent(m=1:this%num_channels) | |
| 707 | !! recalculate x_hat (i.e. normalised input) | ||
| 708 |
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|
6 | x_hat(:,:,:,m,:) = (input(:,:,:,m,:) - this%mean(m)) / & |
| 709 |
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|
1764 | sqrt(this%variance(m) + this%epsilon) |
| 710 | |||
| 711 | !! calculate gradient of normalised input | ||
| 712 |
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|
1758 | dx_hat(:,:,:,m,:) = gradient(:,:,:,m,:) * this%gamma(m) |
| 713 | |||
| 714 | !! calculate gradient of inputs | ||
| 715 | 66 | this%di(:,:,:,m,:) = & | |
| 716 | 6 | 1._real12 / (this%norm * sqrt(this%variance(m) + this%epsilon)) * & | |
| 717 |
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3 | ( this%norm * dx_hat(:,:,:,m,:) - & |
| 718 |
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6 | sum(dx_hat(:,:,:,m,:)) - x_hat(:,:,:,m,:) * & |
| 719 |
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|
5277 | sum(dx_hat(:,:,:,m,:) * x_hat(:,:,:,m,:))) |
| 720 | |||
| 721 | !! calculate gradient of gamma and beta | ||
| 722 |
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|
1758 | this%dg(m) = sum(gradient(:,:,:,m,:) * x_hat(:,:,:,m,:)) |
| 723 |
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|
1759 | this%db(m) = sum(gradient(:,:,:,m,:)) |
| 724 | end do | ||
| 725 | |||
| 726 | 1 | end subroutine backward_5d | |
| 727 | !!!############################################################################# | ||
| 728 | |||
| 729 |
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|
22 | end module batchnorm3d_layer |
| 730 | !!!############################################################################# | ||
| 731 |