Make HDF5 optional under CMake

.github/workflows/ci.yml

@@ -20,7 +20,7 @@ env:
 
 jobs:
 
-  build_and_test_debug_profile:
+  gnu-fpm-debug:
     name: Build and test in debug mode
     runs-on: ubuntu-latest
 
@@ -42,7 +42,7 @@ jobs:
     - name: Test
       run: fpm test --profile debug
 
-  build_and_test_release_profile:
+  gnu-fpm-release:
     name: Build and test in release mode
     runs-on: ubuntu-latest
 

CMakeLists.txt

@@ -17,9 +17,12 @@ include(FetchContent)
 include(cmake/options.cmake)
 include(cmake/compilers.cmake)
 
-include(cmake/functional.cmake)
-include(cmake/h5fortran.cmake)
-include(cmake/json.cmake)
+if(USE_KERAS_HDF5)
+  add_definitions(-DUSE_KERAS_HDF5)
+  include(cmake/functional.cmake)
+  include(cmake/h5fortran.cmake)
+  include(cmake/json.cmake)
+endif()
 
 # library to archive (libneural-fortran.a)
 add_library(neural-fortran
@@ -65,12 +68,14 @@ add_library(neural-fortran
   src/nf/io/nf_io_hdf5_submodule.f90
 )
 
-target_link_libraries(neural-fortran PRIVATE
-  functional::functional
-  h5fortran::h5fortran
-  HDF5::HDF5
-  jsonfortran::jsonfortran
-)
+if(USE_KERAS_HDF5)
+  target_link_libraries(neural-fortran PRIVATE
+    functional::functional
+    h5fortran::h5fortran
+    HDF5::HDF5
+    jsonfortran::jsonfortran
+  )
+endif()
 
 install(TARGETS neural-fortran)
 

README.md

@@ -21,8 +21,8 @@ Read the paper [here](https://arxiv.org/abs/1902.06714).
   RMSProp, Adagrad, Adam, AdamW
 * More than a dozen activation functions and their derivatives
 * Loss functions and metrics: Quadratic, Mean Squared Error, Pearson Correlation etc.
-* Loading dense and convolutional models from Keras HDF5 (.h5) files
 * Data-based parallelism
+* Loading dense and convolutional models from Keras HDF5 (.h5) files (optional)
 
 ### Available layers
 
@@ -51,24 +51,23 @@ cd neural-fortran
 Required dependencies are:
 
 * A Fortran compiler
-* [HDF5](https://www.hdfgroup.org/downloads/hdf5/)
-  (must be provided by the OS package manager or your own build from source)
-* [functional-fortran](https://github.com/wavebitscientific/functional-fortran),
-  [h5fortran](https://github.com/geospace-code/h5fortran),
-  [json-fortran](https://github.com/jacobwilliams/json-fortran)
-  (all handled by neural-fortran's build systems, no need for a manual install)
 * [fpm](https://github.com/fortran-lang/fpm) or
   [CMake](https://cmake.org) for building the code
 
 Optional dependencies are:
 
+* [HDF5](https://www.hdfgroup.org/downloads/hdf5/) for input of Keras models
+  saved as HDF5 files. You can use the HDF5 that ships from your system
+  package manager or build your own from source.
+  Note that HDF5 is still a required dependency if building with fpm instead
+  of CMake.
 * OpenCoarrays (for parallel execution with GFortran)
 * BLAS, MKL, or similar (for offloading `matmul` and `dot_product` calls)
-* curl (for downloading testing and example datasets)
+* curl (for downloading test and example datasets)
 
 Compilers tested include:
 
-* gfortran-9.4.0
+* gfortran-13.2.0
 * ifort-2021.4
 * ifx-2021.4
 
@@ -84,7 +83,8 @@ fpm build \
   --flag "-I$HDF5INC -L$HDF5LIB"
 ```
 
-HDF5 is now a required dependency, so you have to provide it to fpm.
+HDF5 is for now a required dependency when building with fpm, so you have to
+provide it to fpm.
 The above command assumes that the `HDF5INC` and `HDF5LIB` environment
 variables are set to the include and library paths, respectively, of your
 HDF5 install.
@@ -139,6 +139,15 @@ make
 
 Tests and examples will be built in the `bin/` directory.
 
+#### Building with Keras HDF5 input
+
+When building neural-fortran with CMake, Keras HDF5 input feature will not be
+built by default. To build it, use the `-DUSE_KERAS_HDF5=1` option.
+
+```
+cmake .. -DSERIAL=1 -DUSE_KERAS_HDF5=1
+```
+
 #### Building in parallel mode
 
 If you use GFortran and want to run neural-fortran in parallel,

cmake/compilers.cmake

@@ -14,8 +14,8 @@ if(CMAKE_Fortran_COMPILER_ID STREQUAL "GNU")
     message(STATUS "Configuring build to use BLAS from ${BLAS}")
   endif()
 
-  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-fcheck=bounds;-fbacktrace>")
-  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-Ofast;-fno-frontend-optimize;-fno-backtrace>")
+  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-cpp;-O0;-fcheck=bounds;-fbacktrace>")
+  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-cpp;-Ofast;-fno-backtrace>")
 
 elseif(CMAKE_Fortran_COMPILER_ID MATCHES "^Intel")
   # compiler flags for ifort
@@ -44,12 +44,12 @@ elseif(CMAKE_Fortran_COMPILER_ID MATCHES "^Intel")
   else()
     string(APPEND CMAKE_Fortran_FLAGS " -assume byterecl")
   endif()
-  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-check;-traceback>")
-  # add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-O3>")
+  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-fpp;-O0;-check;-traceback>")
+  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-fpp;-O3>")
 
 elseif(CMAKE_Fortran_COMPILER_ID STREQUAL "Cray")
   # compiler flags for Cray ftn
   string(APPEND CMAKE_Fortran_FLAGS " -h noomp")
-  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-O0;-g>")
-  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-O3>")
+  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Debug>>:-e Z;-O0;-g>")
+  add_compile_options("$<$<AND:$<COMPILE_LANGUAGE:Fortran>,$<CONFIG:Release>>:-e Z;-O3>")
 endif()

cmake/options.cmake

@@ -1,4 +1,5 @@
 option(SERIAL "Serial execution")
+option(USE_KERAS_HDF5 "Enable modules to load Keras HDF5 models")
 option(${PROJECT_NAME}_BUILD_TESTING "build ${PROJECT_NAME} tests" true)
 option(${PROJECT_NAME}_BUILD_EXAMPLES "build ${PROJECT_NAME} examples" true)
 
@@ -14,6 +15,12 @@ else()
   message(STATUS "Configuring build for parallel execution")
 endif()
 
+if(USE_KERAS_HDF5)
+  message(STATUS "Configuring build with Keras HDF5 support")
+else()
+  message(STATUS "Configuring build without Keras HDF5 support")
+endif()
+
 # --- Generally useful CMake project options
 
 # Rpath options necessary for shared library install to work correctly in user projects

example/CMakeLists.txt

@@ -10,10 +10,15 @@ foreach(execid
   quadratic
 )
   add_executable(${execid} ${execid}.f90)
-  target_link_libraries(${execid} PRIVATE
-    neural-fortran
-    h5fortran::h5fortran
-    jsonfortran::jsonfortran
-    ${LIBS}
-  )
+  if(USE_KERAS_HDF5)
+    target_compile_definitions(${execid} PRIVATE USE_KERAS_HDF5)
+    target_link_libraries(${execid} PRIVATE
+      neural-fortran
+      h5fortran::h5fortran
+      jsonfortran::jsonfortran
+      ${LIBS}
+    )
+  else()
+    target_link_libraries(${execid} PRIVATE neural-fortran ${LIBS})
+  endif()
 endforeach()

example/cnn_from_keras.f90

@@ -1,4 +1,5 @@
 program cnn_from_keras
+#ifdef USE_KERAS_HDF5
 
   ! This example demonstrates loading a convolutional model
   ! pre-trained on the MNIST dataset from a Keras HDF5
@@ -55,4 +56,5 @@ real function accuracy(net, x, y)
     accuracy = real(good) / size(x, dim=4)
   end function accuracy
 
-end program cnn_from_keras
+#endif
+end program cnn_from_keras

example/dense_from_keras.f90

@@ -1,4 +1,5 @@
 program dense_from_keras
+#ifdef USE_KERAS_HDF5
 
   ! This example demonstrates loading a dense model
   ! pre-trained on the MNIST dataset from a Keras HDF5
@@ -49,4 +50,5 @@ real function accuracy(net, x, y)
     accuracy = real(good) / size(x, dim=2)
   end function accuracy
 
-end program dense_from_keras
+#endif
+end program dense_from_keras

src/nf/io/nf_io_hdf5.f90

@@ -57,4 +57,4 @@ end subroutine get_hdf5_dataset_real32_4d
 
   end interface get_hdf5_dataset
 
-end module nf_io_hdf5
+end module nf_io_hdf5

src/nf/io/nf_io_hdf5_submodule.f90

@@ -1,3 +1,4 @@
+#ifdef USE_KERAS_HDF5
 submodule(nf_io_hdf5) nf_io_hdf5_submodule
 
   use iso_fortran_env, only: int64, real32, stderr => error_unit
@@ -109,3 +110,4 @@ module subroutine get_hdf5_dataset_real32_4d(filename, object_name, values)
   end subroutine get_hdf5_dataset_real32_4d
 
 end submodule nf_io_hdf5_submodule
+#endif

src/nf/nf_keras_submodule.f90

@@ -1,3 +1,4 @@
+#ifdef USE_KERAS_HDF5
 submodule(nf_keras) nf_keras_submodule
 
   use functional, only: reverse
@@ -102,3 +103,4 @@ module function get_keras_h5_layers(filename) result(res)
   end function get_keras_h5_layers
 
 end submodule nf_keras_submodule
+#endif

src/nf/nf_network_submodule.f90

@@ -95,6 +95,7 @@ module function network_from_layers(layers) result(res)
   end function network_from_layers
 
 
+#ifdef USE_KERAS_HDF5
   module function network_from_keras(filename) result(res)
     character(*), intent(in) :: filename
     type(network) :: res
@@ -222,9 +223,10 @@ module function network_from_keras(filename) result(res)
 
       end select
 
-  end do
+    end do
 
   end function network_from_keras
+#endif
 
 
   pure function get_activation_by_name(activation_name) result(res)

test/CMakeLists.txt

@@ -20,7 +20,13 @@ foreach(execid
   metrics
   )
   add_executable(test_${execid} test_${execid}.f90)
-  target_link_libraries(test_${execid} PRIVATE neural-fortran h5fortran::h5fortran jsonfortran::jsonfortran ${LIBS})
+
+  if (USE_KERAS_HDF5)
+    target_compile_definitions(test_${execid} PRIVATE USE_KERAS_HDF5)
+    target_link_libraries(test_${execid} PRIVATE neural-fortran h5fortran::h5fortran jsonfortran::jsonfortran ${LIBS})
+  else()
+    target_link_libraries(test_${execid} PRIVATE neural-fortran ${LIBS})
+  endif()
 
   add_test(NAME test_${execid} COMMAND test_${execid})
 endforeach()

test/test_cnn_from_keras.f90

@@ -1,4 +1,5 @@
 program test_cnn_from_keras
+#ifdef USE_KERAS_HDF5
 
   use iso_fortran_env, only: stderr => error_unit
   use nf, only: network
@@ -66,4 +67,5 @@ real function accuracy(net, x, y)
     accuracy = real(good) / size(x, dim=4)
   end function accuracy
 
+#endif
 end program test_cnn_from_keras

test/test_conv2d_network.f90

@@ -39,7 +39,7 @@ program test_conv2d_network
 
     type(network) :: cnn
     real :: y(1)
-    real :: tolerance = 1e-5
+    real :: tolerance = 1e-4
     integer :: n
     integer, parameter :: num_iterations = 1000
 
@@ -76,7 +76,7 @@ program test_conv2d_network
     type(network) :: cnn
     real :: x(1, 8, 8)
     real :: y(1)
-    real :: tolerance = 1e-5
+    real :: tolerance = 1e-4
     integer :: n
     integer, parameter :: num_iterations = 1000
 
@@ -111,7 +111,7 @@ program test_conv2d_network
     type(network) :: cnn
     real :: x(1, 12, 12)
     real :: y(9)
-    real :: tolerance = 1e-5
+    real :: tolerance = 1e-4
     integer :: n
     integer, parameter :: num_iterations = 5000
 

test/test_dense_network_from_keras.f90

@@ -1,4 +1,5 @@
 program test_dense_network_from_keras
+#ifdef USE_KERAS_HDF5
 
   use iso_fortran_env, only: stderr => error_unit
   use nf, only: network
@@ -97,4 +98,5 @@ real function accuracy(net, x, y)
     accuracy = real(good) / size(x, dim=2)
   end function accuracy
 
+#endif
 end program test_dense_network_from_keras

test/test_io_hdf5.f90

@@ -1,4 +1,5 @@
 program test_io_hdf5
+#ifdef USE_KERAS_HDF5
 
   use iso_fortran_env, only: stderr => error_unit
   use nf_datasets, only: download_and_unpack, keras_dense_mnist_url
@@ -54,4 +55,5 @@ program test_io_hdf5
     stop 1
   end if
 
-end program test_io_hdf5
+#endif
+end program test_io_hdf5

test/test_keras_read_model.f90

@@ -1,4 +1,5 @@
 program test_keras_read_model
+#ifdef USE_KERAS_HDF5
 
   use iso_fortran_env, only: stderr => error_unit
   use nf_datasets, only: download_and_unpack, keras_dense_mnist_url, &
@@ -105,4 +106,5 @@ program test_keras_read_model
     stop 1
   end if
 
-end program test_keras_read_model
+#endif
+end program test_keras_read_model

test/test_reshape_layer.f90

@@ -2,7 +2,10 @@ program test_reshape_layer
 
   use iso_fortran_env, only: stderr => error_unit
   use nf, only: input, network, reshape_layer => reshape
-  use nf_datasets, only: download_and_unpack, keras_reshape_url
+  use nf_datasets, only: download_and_unpack
+#ifdef USE_KERAS_HDF5
+  use nf_datasets, only: keras_reshape_url
+#endif
 
   implicit none
 
@@ -43,6 +46,7 @@ program test_reshape_layer
     ok = .false.
   end if
 
+#ifdef USE_KERAS_HDF5
   ! Now test reading the reshape layer from a Keras h5 model.
   inquire(file=keras_reshape_path, exist=file_exists)
   if (.not. file_exists) call download_and_unpack(keras_reshape_url)
@@ -67,6 +71,7 @@ program test_reshape_layer
     write(stderr, '(a)') 'the target shape of the reshape layer is correct.. failed'
     ok = .false.
   end if
+#endif
 
   if (ok) then
     print '(a)', 'test_reshape_layer: All tests passed.'