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milancurcicmilancurcic
authoredSep 3, 2024··
Standard conformance fixes (#190)
* Make various functions impure to allow returning polymorphic allocatables * Update tested compilers * More on tested compilers * Update CMake definitions to make serial default and add PARALLEL macro
1 parent 3872202 commit 9a40117

16 files changed

+84
-73
lines changed
 

‎README.md

Lines changed: 8 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -63,9 +63,10 @@ Optional dependencies are:
6363

6464
Compilers tested include:
6565

66-
* gfortran-9.4.0
67-
* ifort-2021.4
68-
* ifx-2021.4
66+
* flang-new 20.0.0
67+
* gfortran 13.2.0, 14.0.1
68+
* ifort 2021.13.1
69+
* ifx 2024.2.1
6970

7071
### Building with fpm
7172

@@ -85,7 +86,7 @@ Once installed, use the compiler wrappers `caf` and `cafrun` to build and execut
8586
in parallel, respectively:
8687

8788
```
88-
fpm build --compiler caf --profile release
89+
fpm build --compiler caf --profile release --flag "-cpp -DPARALLEL"
8990
```
9091

9192
#### Testing with fpm
@@ -107,7 +108,7 @@ See the [Fortran Package Manager](https://github.com/fortran-lang/fpm) for more
107108
```
108109
mkdir build
109110
cd build
110-
cmake .. -DSERIAL=1
111+
cmake ..
111112
make
112113
```
113114

@@ -122,7 +123,7 @@ in parallel, respectively:
122123

123124

124125
```
125-
FC=caf cmake ..
126+
FC=caf cmake .. -DPARALLEL
126127
make
127128
cafrun -n 4 bin/mnist # run MNIST example on 4 cores
128129
```
@@ -139,7 +140,7 @@ FC=ifort cmake ..
139140
for a parallel build of neural-fortran, or
140141

141142
```
142-
FC=ifort cmake .. -DSERIAL=1
143+
FC=ifort cmake ..
143144
```
144145

145146
for a serial build.

‎cmake/compilers.cmake

Lines changed: 20 additions & 18 deletions
Original file line numberDiff line numberDiff line change
@@ -1,11 +1,12 @@
11
# compiler flags for gfortran
22
if(CMAKE_Fortran_COMPILER_ID STREQUAL "GNU")
33

4-
if(SERIAL)
5-
message(STATUS "Configuring to build with -fcoarray=single")
6-
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:-fcoarray=single>")
4+
if(PARALLEL)
5+
message(STATUS "Configuring to build with -fcoarray=shared")
6+
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:-fcoarray=shared>")
7+
add_compile_definitions(PARALLEL)
78
else()
8-
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:-fcoarray=lib>")
9+
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:-fcoarray=single>")
910
endif()
1011

1112
if(BLAS)
@@ -14,21 +15,22 @@ if(CMAKE_Fortran_COMPILER_ID STREQUAL "GNU")
1415
message(STATUS "Configuring build to use BLAS from ${BLAS}")
1516
endif()
1617

17-
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-fcheck=bounds;-fbacktrace>")
18-
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-Ofast;-fno-frontend-optimize;-fno-backtrace>")
18+
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-cpp;-fcheck=bounds;-fbacktrace>")
19+
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-cpp;-Ofast;-fno-frontend-optimize;-fno-backtrace>")
1920

2021
elseif(CMAKE_Fortran_COMPILER_ID MATCHES "^Intel")
2122
# compiler flags for ifort
2223

23-
if(SERIAL)
24-
message(STATUS "Configuring to build with -coarray=single")
24+
if(PARALLEL)
25+
message(STATUS "Configuring to build with -coarray=shared")
2526
if(WIN32)
26-
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:/Qcoarray:single>")
27-
add_link_options("$<$<COMPILE_LANGUAGE:Fortran>:/Qcoarray:single>")
27+
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:/Qcoarray:shared>")
28+
add_link_options("$<$<COMPILE_LANGUAGE:Fortran>:/Qcoarray:shared>")
2829
else()
29-
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:-coarray=single>")
30-
add_link_options("$<$<COMPILE_LANGUAGE:Fortran>:-coarray=single>")
30+
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:-coarray=shared>")
31+
add_link_options("$<$<COMPILE_LANGUAGE:Fortran>:-coarray=shared>")
3132
endif()
33+
add_compile_definitions(PARALLEL)
3234
else()
3335
if(WIN32)
3436
add_compile_options("$<$<COMPILE_LANGUAGE:Fortran>:/Qcoarray:shared>")
@@ -40,16 +42,16 @@ elseif(CMAKE_Fortran_COMPILER_ID MATCHES "^Intel")
4042
endif()
4143

4244
if(WIN32)
43-
string(APPEND CMAKE_Fortran_FLAGS " /assume:byterecl")
45+
string(APPEND CMAKE_Fortran_FLAGS " /assume:byterecl /fpp")
4446
else()
45-
string(APPEND CMAKE_Fortran_FLAGS " -assume byterecl")
47+
string(APPEND CMAKE_Fortran_FLAGS " -assume byterecl -fpp")
4648
endif()
47-
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-check;-traceback>")
48-
# add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-O3>")
49+
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-fpp;-check;-traceback>")
50+
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-fpp;-O3>")
4951

5052
elseif(CMAKE_Fortran_COMPILER_ID STREQUAL "Cray")
5153
# compiler flags for Cray ftn
5254
string(APPEND CMAKE_Fortran_FLAGS " -h noomp")
53-
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-O0;-g>")
54-
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-O3>")
55+
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-e Z;-O0;-g>")
56+
add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-e Z;-O3>")
5557
endif()

‎cmake/options.cmake

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
1-
option(SERIAL "Serial execution")
1+
option(PARALLEL "Parallel execution")
22
option(${PROJECT_NAME}_BUILD_TESTING "build ${PROJECT_NAME} tests" true)
33
option(${PROJECT_NAME}_BUILD_EXAMPLES "build ${PROJECT_NAME} examples" true)
44

@@ -8,10 +8,10 @@ set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
88
set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
99
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
1010

11-
if(SERIAL)
12-
message(STATUS "Configuring build for serial execution")
13-
else()
11+
if(PARALLEL)
1412
message(STATUS "Configuring build for parallel execution")
13+
else()
14+
message(STATUS "Configuring build for serial execution; configure with -DPARALLEL=1 for a parallel build")
1515
endif()
1616

1717
# --- Generally useful CMake project options

‎example/cnn_mnist.f90

Lines changed: 2 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -40,9 +40,8 @@ program cnn_mnist
4040
optimizer=sgd(learning_rate=3.) &
4141
)
4242

43-
if (this_image() == 1) &
44-
print '(a,i2,a,f5.2,a)', 'Epoch ', n, ' done, Accuracy: ', accuracy( &
45-
net, validation_images, label_digits(validation_labels)) * 100, ' %'
43+
print '(a,i2,a,f5.2,a)', 'Epoch ', n, ' done, Accuracy: ', accuracy( &
44+
net, validation_images, label_digits(validation_labels)) * 100, ' %'
4645

4746
end do epochs
4847

‎example/dense_mnist.f90

Lines changed: 5 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -24,9 +24,8 @@ program dense_mnist
2424

2525
call net % print_info()
2626

27-
if (this_image() == 1) &
28-
print '(a,f5.2,a)', 'Initial accuracy: ', accuracy( &
29-
net, validation_images, label_digits(validation_labels)) * 100, ' %'
27+
print '(a,f5.2,a)', 'Initial accuracy: ', accuracy( &
28+
net, validation_images, label_digits(validation_labels)) * 100, ' %'
3029

3130
epochs: do n = 1, num_epochs
3231

@@ -44,10 +43,9 @@ program dense_mnist
4443
! 2 metrics; 1st is default loss function (quadratic), other is Pearson corr.
4544
output_metrics = net % evaluate(validation_images, label_digits(validation_labels), metric=corr())
4645
mean_metrics = sum(output_metrics, 1) / size(output_metrics, 1)
47-
if (this_image() == 1) &
48-
print '(a,i2,3(a,f6.3))', 'Epoch ', n, ' done, Accuracy: ', &
49-
accuracy(net, validation_images, label_digits(validation_labels)) * 100, &
50-
'%, Loss: ', mean_metrics(1), ', Pearson correlation: ', mean_metrics(2)
46+
print '(a,i2,3(a,f6.3))', 'Epoch ', n, ' done, Accuracy: ', &
47+
accuracy(net, validation_images, label_digits(validation_labels)) * 100, &
48+
'%, Loss: ', mean_metrics(1), ', Pearson correlation: ', mean_metrics(2)
5149
end block
5250

5351
end do epochs

‎src/nf/nf_activation.f90

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -557,7 +557,7 @@ pure function eval_3d_celu_prime(self, x) result(res)
557557
end where
558558
end function
559559

560-
pure function get_activation_by_name(activation_name) result(res)
560+
function get_activation_by_name(activation_name) result(res)
561561
! Workaround to get activation_function with some
562562
! hardcoded default parameters by its name.
563563
! Need this function since we get only activation name

‎src/nf/nf_conv2d_layer.f90

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -41,7 +41,7 @@ module nf_conv2d_layer
4141
end type conv2d_layer
4242

4343
interface conv2d_layer
44-
pure module function conv2d_layer_cons(filters, kernel_size, activation) &
44+
module function conv2d_layer_cons(filters, kernel_size, activation) &
4545
result(res)
4646
!! `conv2d_layer` constructor function
4747
integer, intent(in) :: filters

‎src/nf/nf_conv2d_layer_submodule.f90

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -7,7 +7,7 @@
77

88
contains
99

10-
pure module function conv2d_layer_cons(filters, kernel_size, activation) result(res)
10+
module function conv2d_layer_cons(filters, kernel_size, activation) result(res)
1111
implicit none
1212
integer, intent(in) :: filters
1313
integer, intent(in) :: kernel_size

‎src/nf/nf_dense_layer.f90

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -42,7 +42,7 @@ module nf_dense_layer
4242
end type dense_layer
4343

4444
interface dense_layer
45-
elemental module function dense_layer_cons(output_size, activation) &
45+
module function dense_layer_cons(output_size, activation) &
4646
result(res)
4747
!! This function returns the `dense_layer` instance.
4848
integer, intent(in) :: output_size

‎src/nf/nf_dense_layer_submodule.f90

Lines changed: 3 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -8,7 +8,7 @@
88

99
contains
1010

11-
elemental module function dense_layer_cons(output_size, activation) &
11+
module function dense_layer_cons(output_size, activation) &
1212
result(res)
1313
integer, intent(in) :: output_size
1414
class(activation_function), intent(in) :: activation
@@ -129,7 +129,9 @@ module subroutine init(self, input_shape)
129129
self % weights = self % weights / self % input_size
130130

131131
! Broadcast weights to all other images, if any.
132+
#ifdef PARALLEL
132133
call co_broadcast(self % weights, 1)
134+
#endif
133135

134136
allocate(self % biases(self % output_size))
135137
self % biases = 0

‎src/nf/nf_layer_constructors.f90

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -12,7 +12,7 @@ module nf_layer_constructors
1212

1313
interface input
1414

15-
pure module function input1d(layer_size) result(res)
15+
module function input1d(layer_size) result(res)
1616
!! 1-d input layer constructor.
1717
!!
1818
!! This layer is for inputting 1-d data to the network.
@@ -35,7 +35,7 @@ pure module function input1d(layer_size) result(res)
3535
!! Resulting layer instance
3636
end function input1d
3737

38-
pure module function input3d(layer_shape) result(res)
38+
module function input3d(layer_shape) result(res)
3939
!! 3-d input layer constructor.
4040
!!
4141
!! This layer is for inputting 3-d data to the network.
@@ -62,7 +62,7 @@ end function input3d
6262

6363
interface
6464

65-
pure module function dense(layer_size, activation) result(res)
65+
module function dense(layer_size, activation) result(res)
6666
!! Dense (fully-connected) layer constructor.
6767
!!
6868
!! This layer is a building block for dense, fully-connected networks,
@@ -85,7 +85,7 @@ pure module function dense(layer_size, activation) result(res)
8585
!! Resulting layer instance
8686
end function dense
8787

88-
pure module function flatten() result(res)
88+
module function flatten() result(res)
8989
!! Flatten (3-d -> 1-d) layer constructor.
9090
!!
9191
!! Use this layer to chain layers with 3-d outputs to layers with 1-d
@@ -106,7 +106,7 @@ pure module function flatten() result(res)
106106
!! Resulting layer instance
107107
end function flatten
108108

109-
pure module function conv2d(filters, kernel_size, activation) result(res)
109+
module function conv2d(filters, kernel_size, activation) result(res)
110110
!! 2-d convolutional layer constructor.
111111
!!
112112
!! This layer is for building 2-d convolutional network.
@@ -133,7 +133,7 @@ pure module function conv2d(filters, kernel_size, activation) result(res)
133133
!! Resulting layer instance
134134
end function conv2d
135135

136-
pure module function maxpool2d(pool_size, stride) result(res)
136+
module function maxpool2d(pool_size, stride) result(res)
137137
!! 2-d maxpooling layer constructor.
138138
!!
139139
!! This layer is for downscaling other layers, typically `conv2d`.
@@ -155,7 +155,7 @@ pure module function maxpool2d(pool_size, stride) result(res)
155155
!! Resulting layer instance
156156
end function maxpool2d
157157

158-
pure module function reshape(output_shape) result(res)
158+
module function reshape(output_shape) result(res)
159159
!! Rank-1 to rank-any reshape layer constructor.
160160
!! Currently implemented is only rank-3 for the output of the reshape.
161161
!!

‎src/nf/nf_layer_constructors_submodule.f90

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -14,7 +14,7 @@
1414

1515
contains
1616

17-
pure module function conv2d(filters, kernel_size, activation) result(res)
17+
module function conv2d(filters, kernel_size, activation) result(res)
1818
integer, intent(in) :: filters
1919
integer, intent(in) :: kernel_size
2020
class(activation_function), intent(in), optional :: activation
@@ -40,7 +40,7 @@ pure module function conv2d(filters, kernel_size, activation) result(res)
4040
end function conv2d
4141

4242

43-
pure module function dense(layer_size, activation) result(res)
43+
module function dense(layer_size, activation) result(res)
4444
integer, intent(in) :: layer_size
4545
class(activation_function), intent(in), optional :: activation
4646
type(layer) :: res
@@ -63,14 +63,14 @@ pure module function dense(layer_size, activation) result(res)
6363
end function dense
6464

6565

66-
pure module function flatten() result(res)
66+
module function flatten() result(res)
6767
type(layer) :: res
6868
res % name = 'flatten'
6969
allocate(res % p, source=flatten_layer())
7070
end function flatten
7171

7272

73-
pure module function input1d(layer_size) result(res)
73+
module function input1d(layer_size) result(res)
7474
integer, intent(in) :: layer_size
7575
type(layer) :: res
7676
res % name = 'input'
@@ -81,7 +81,7 @@ pure module function input1d(layer_size) result(res)
8181
end function input1d
8282

8383

84-
pure module function input3d(layer_shape) result(res)
84+
module function input3d(layer_shape) result(res)
8585
integer, intent(in) :: layer_shape(3)
8686
type(layer) :: res
8787
res % name = 'input'
@@ -91,7 +91,7 @@ pure module function input3d(layer_shape) result(res)
9191
res % initialized = .true.
9292
end function input3d
9393

94-
pure module function maxpool2d(pool_size, stride) result(res)
94+
module function maxpool2d(pool_size, stride) result(res)
9595
integer, intent(in) :: pool_size
9696
integer, intent(in), optional :: stride
9797
integer :: stride_
@@ -119,7 +119,7 @@ pure module function maxpool2d(pool_size, stride) result(res)
119119

120120
end function maxpool2d
121121

122-
pure module function reshape(output_shape) result(res)
122+
module function reshape(output_shape) result(res)
123123
integer, intent(in) :: output_shape(:)
124124
type(layer) :: res
125125

‎src/nf/nf_metrics.f90

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -36,7 +36,7 @@ end function metric_interface
3636

3737
contains
3838

39-
pure module function corr_eval(true, predicted) result(res)
39+
pure function corr_eval(true, predicted) result(res)
4040
!! Pearson correlation function:
4141
!!
4242
real, intent(in) :: true(:)

‎src/nf/nf_network.f90

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -77,7 +77,7 @@ end function evaluate_batch_1d
7777

7878
interface forward
7979

80-
pure module subroutine forward_1d(self, input)
80+
module subroutine forward_1d(self, input)
8181
!! Apply a forward pass through the network.
8282
!!
8383
!! This changes the state of layers on the network.
@@ -91,7 +91,7 @@ pure module subroutine forward_1d(self, input)
9191
!! 1-d input data
9292
end subroutine forward_1d
9393

94-
pure module subroutine forward_3d(self, input)
94+
module subroutine forward_3d(self, input)
9595
!! Apply a forward pass through the network.
9696
!!
9797
!! This changes the state of layers on the network.
@@ -153,7 +153,7 @@ end function predict_batch_3d
153153

154154
interface
155155

156-
pure module subroutine backward(self, output, loss)
156+
module subroutine backward(self, output, loss)
157157
!! Apply one backward pass through the network.
158158
!! This changes the state of layers on the network.
159159
!! Typically used only internally from the `train` method,
@@ -166,7 +166,7 @@ pure module subroutine backward(self, output, loss)
166166
!! Loss instance to use. If not provided, the default is quadratic().
167167
end subroutine backward
168168

169-
pure module integer function get_num_params(self)
169+
module integer function get_num_params(self)
170170
!! Get the number of parameters in the network.
171171
class(network), intent(in) :: self
172172
!! Network instance

‎src/nf/nf_network_submodule.f90

Lines changed: 14 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -93,7 +93,7 @@ module function network_from_layers(layers) result(res)
9393
end function network_from_layers
9494

9595

96-
pure module subroutine backward(self, output, loss)
96+
module subroutine backward(self, output, loss)
9797
class(network), intent(in out) :: self
9898
real, intent(in) :: output(:)
9999
class(loss_type), intent(in), optional :: loss
@@ -167,20 +167,20 @@ module function evaluate_batch_1d(self, input_data, output_data, metric) result(
167167

168168
allocate(res(size(output, dim=1), n))
169169

170-
do concurrent (i = 1:size(output, dim=1))
170+
do i = 1, size(output, dim=1)
171171
res(i,1) = self % loss % eval(output_data(i,:), output(i,:))
172172
end do
173173

174174
if (.not. present(metric)) return
175175

176-
do concurrent (i = 1:size(output, dim=1))
176+
do i = 1, size(output, dim=1)
177177
res(i,2) = metric % eval(output_data(i,:), output(i,:))
178178
end do
179179

180180
end function evaluate_batch_1d
181181

182182

183-
pure module subroutine forward_1d(self, input)
183+
module subroutine forward_1d(self, input)
184184
class(network), intent(in out) :: self
185185
real, intent(in) :: input(:)
186186
integer :: n
@@ -197,7 +197,7 @@ pure module subroutine forward_1d(self, input)
197197
end subroutine forward_1d
198198

199199

200-
pure module subroutine forward_3d(self, input)
200+
module subroutine forward_3d(self, input)
201201
class(network), intent(in out) :: self
202202
real, intent(in) :: input(:,:,:)
203203
integer :: n
@@ -273,7 +273,7 @@ module function predict_batch_1d(self, input) result(res)
273273

274274
allocate(res(output_size, batch_size))
275275

276-
batch: do concurrent(i = 1:size(res, dim=2))
276+
batch: do i = 1, size(res, dim=2)
277277

278278
call self % forward(input(:,i))
279279

@@ -303,7 +303,7 @@ module function predict_batch_3d(self, input) result(res)
303303

304304
allocate(res(output_size, batch_size))
305305

306-
batch: do concurrent(i = 1:batch_size)
306+
batch: do i = 1, batch_size
307307

308308
call self % forward(input(:,:,:,i))
309309

@@ -330,7 +330,7 @@ module subroutine print_info(self)
330330
end subroutine print_info
331331

332332

333-
pure module function get_num_params(self)
333+
module function get_num_params(self)
334334
class(network), intent(in) :: self
335335
integer :: get_num_params
336336

@@ -443,15 +443,17 @@ module subroutine train(self, input_data, output_data, batch_size, &
443443
call random_number(pos)
444444
batch_start = int(pos * (dataset_size - batch_size + 1)) + 1
445445

446+
#ifdef PARALLEL
446447
! FIXME shuffle in a way that doesn't require co_broadcast
447448
call co_broadcast(batch_start, 1)
449+
#endif
448450

449451
! Distribute the batch in nearly equal pieces to all images
450452
indices = tile_indices(batch_size)
451453
istart = indices(1) + batch_start - 1
452454
iend = indices(2) + batch_start - 1
453455

454-
do concurrent(j = istart:iend)
456+
do j = istart, iend
455457
call self % forward(input_data(:,j))
456458
call self % backward(output_data(:,j))
457459
end do
@@ -494,6 +496,7 @@ module subroutine update(self, optimizer, batch_size)
494496
batch_size_ = 1
495497
end if
496498

499+
#ifdef PARALLEL
497500
! Sum weight and bias gradients across images, if any
498501
do n = 2, size(self % layers)
499502
select type(this_layer => self % layers(n) % p)
@@ -505,13 +508,14 @@ module subroutine update(self, optimizer, batch_size)
505508
call co_sum(this_layer % db)
506509
end select
507510
end do
511+
#endif
508512

509513
params = self % get_params()
510514
call self % optimizer % minimize(params, self % get_gradients() / batch_size_)
511515
call self % set_params(params)
512516

513517
! Flush network gradients to zero.
514-
do concurrent(n = 2:size(self % layers))
518+
do n = 2, size(self % layers)
515519
select type(this_layer => self % layers(n) % p)
516520
type is(dense_layer)
517521
this_layer % dw = 0

‎src/nf/nf_parallel_submodule.f90

Lines changed: 5 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,3 +1,8 @@
1+
#ifndef PARALLEL
2+
#define num_images() 1
3+
#define this_image() 1
4+
#endif
5+
16
submodule(nf_parallel) nf_parallel_submodule
27
implicit none
38
contains

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