resolve conflicts from master

Author: milancurcic

CMakeLists.txt

@@ -31,6 +31,13 @@ else()
   add_definitions(-DREAL32)
 endif()
 
+if(SERIAL)
+  message(STATUS "Configuring build for serial execution")
+else()
+  message(STATUS "Configuring build for parallel execution")
+  add_definitions(-DCAF)
+endif()
+
 # compiler flags for gfortran
 if(CMAKE_Fortran_COMPILER_ID MATCHES GNU)
 
@@ -52,9 +59,15 @@ endif()
 
 # compiler flags for ifort
 if(CMAKE_Fortran_COMPILER_ID MATCHES Intel)
-  set(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -coarray=shared -fpp -assume byterecl,realloc_lhs -heap-arrays")
+
+  set(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -fpp -assume byterecl,realloc_lhs -heap-arrays")
   set(CMAKE_Fortran_FLAGS_DEBUG "-O0 -g -C -traceback")
   set(CMAKE_Fortran_FLAGS_RELEASE "-O3")
+
+  if(NOT SERIAL)
+    set(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -coarray=shared")
+  endif()
+
 endif()
 
 # compiler flags for Cray ftn

CONTRIBUTORS.md

@@ -0,0 +1,7 @@
+# Contributors
+
+* @ivan-pi
+* @jvdp1
+* @milancurcic
+* @pirpyn
+* @scivision

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2018 Milan Curcic
+Copyright (c) 2018-2019 Milan Curcic and neural-fortran contributors
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

src/lib/mod_layer.f90

@@ -18,6 +18,7 @@ module mod_layer
     real(rk), allocatable :: z(:) ! arg. to activation function
     procedure(activation_function), pointer, nopass :: activation => null()
     procedure(activation_function), pointer, nopass :: activation_prime => null()
+    character(len=:), allocatable :: activation_str ! activation character string
   contains
     procedure, public, pass(self) :: set_activation
   end type layer_type
@@ -102,7 +103,9 @@ subroutine db_co_sum(db)
     type(array1d), allocatable, intent(in out) :: db(:)
     integer(ik) :: n
     do n = 2, size(db)
+#ifdef CAF
       call co_sum(db(n) % array)
+#endif
     end do
   end subroutine db_co_sum
 
@@ -111,11 +114,13 @@ subroutine dw_co_sum(dw)
     type(array2d), allocatable, intent(in out) :: dw(:)
     integer(ik) :: n
     do n = 1, size(dw) - 1
+#ifdef CAF
       call co_sum(dw(n) % array)
+#endif
     end do
   end subroutine dw_co_sum
 
-  pure subroutine set_activation(self, activation)
+  pure elemental subroutine set_activation(self, activation)
     ! Sets the activation function. Input string must match one of
     ! provided activation functions, otherwise it defaults to sigmoid.
     ! If activation not present, defaults to sigmoid.
@@ -125,21 +130,27 @@ pure subroutine set_activation(self, activation)
       case('gaussian')
         self % activation => gaussian
         self % activation_prime => gaussian_prime
+        self % activation_str = 'gaussian'
       case('relu')
         self % activation => relu
         self % activation_prime => relu_prime
+        self % activation_str = 'relu'
       case('sigmoid')
         self % activation => sigmoid
         self % activation_prime => sigmoid_prime
+        self % activation_str = 'sigmoid'
       case('step')
         self % activation => step
         self % activation_prime => step_prime
+        self % activation_str = 'step'
       case('tanh')
         self % activation => tanhf
         self % activation_prime => tanh_prime
+        self % activation_str = 'tanh'
       case default
         self % activation => sigmoid
         self % activation_prime => sigmoid_prime
+        self % activation_str = 'sigmoid'
     end select
   end subroutine set_activation
 

src/lib/mod_network.f90

@@ -26,14 +26,16 @@ module mod_network
     procedure, public, pass(self) :: output_batch
     procedure, public, pass(self) :: output_single
     procedure, public, pass(self) :: save
-    procedure, public, pass(self) :: set_activation
+    procedure, public, pass(self) :: set_activation_equal
+    procedure, public, pass(self) :: set_activation_layers
     procedure, public, pass(self) :: sync
     procedure, public, pass(self) :: train_batch
     procedure, public, pass(self) :: train_epochs
     procedure, public, pass(self) :: train_single
     procedure, public, pass(self) :: update
 
     generic, public :: output => output_batch, output_single
+    generic, public :: set_activation => set_activation_equal, set_activation_layers
     generic, public :: train => train_batch, train_epochs, train_single
 
   end type network_type
@@ -139,13 +141,18 @@ subroutine load(self, filename)
     ! Loads the network from file.
     class(network_type), intent(in out) :: self
     character(len=*), intent(in) :: filename
-    integer(ik) :: fileunit, n, num_layers
+    integer(ik) :: fileunit, n, num_layers, layer_idx
     integer(ik), allocatable :: dims(:)
+    character(len=100) :: buffer ! activation string
     open(newunit=fileunit, file=filename, status='old', action='read')
     read(fileunit, fmt=*) num_layers
     allocate(dims(num_layers))
     read(fileunit, fmt=*) dims
     call self % init(dims)
+    do n = 1, num_layers
+      read(fileunit, fmt=*) layer_idx, buffer
+      call self % layers(layer_idx) % set_activation(trim(buffer))
+    end do
     do n = 2, size(self % dims)
       read(fileunit, fmt=*) self % layers(n) % b
     end do
@@ -198,6 +205,9 @@ subroutine save(self, filename)
     open(newunit=fileunit, file=filename)
     write(fileunit, fmt=*) size(self % dims)
     write(fileunit, fmt=*) self % dims
+    do n = 1, size(self % dims)
+      write(fileunit, fmt=*) n, self % layers(n) % activation_str
+    end do
     do n = 2, size(self % dims)
       write(fileunit, fmt=*) self % layers(n) % b
     end do
@@ -207,17 +217,23 @@ subroutine save(self, filename)
     close(fileunit)
   end subroutine save
 
-  pure subroutine set_activation(self, activation)
+  pure subroutine set_activation_equal(self, activation)
     ! A thin wrapper around layer % set_activation().
     ! This method can be used to set an activation function
     ! for all layers at once. 
     class(network_type), intent(in out) :: self
     character(len=*), intent(in) :: activation
-    integer :: n
-    do concurrent(n = 1:size(self % layers))
-      call self % layers(n) % set_activation(activation)
-    end do
-  end subroutine set_activation
+    call self % layers(:) % set_activation(activation)
+  end subroutine set_activation_equal
+
+  pure subroutine set_activation_layers(self, activation)
+    ! A thin wrapper around layer % set_activation().
+    ! This method can be used to set different activation functions
+    ! for each layer separately. 
+    class(network_type), intent(in out) :: self
+    character(len=*), intent(in) :: activation(size(self % layers))
+    call self % layers(:) % set_activation(activation)
+  end subroutine set_activation_layers
 
   subroutine sync(self, image)
     ! Broadcasts network weights and biases from
@@ -227,8 +243,10 @@ subroutine sync(self, image)
     integer(ik) :: n
     if (num_images() == 1) return
     layers: do n = 1, size(self % dims)
+#ifdef CAF
       call co_broadcast(self % layers(n) % b, image)
       call co_broadcast(self % layers(n) % w, image)
+#endif
     end do layers
   end subroutine sync
 

src/tests/test_network_save.f90

@@ -6,6 +6,7 @@ program test_network_save
   print *, 'Initializing 2 networks with random weights and biases'
   net1 = network_type([768, 30, 10])
   net2 = network_type([768, 30, 10])
+
   print *, 'Save network 1 into file'
   call net1 % save('test_network.dat')
   call net2 % load('test_network.dat')
@@ -15,4 +16,17 @@ program test_network_save
       all(net1 % layers(n) % w == net2 % layers(n) % w),&
       ', biases equal:', all(net1 % layers(n) % b == net2 % layers(n) % b)
   end do
+  print *, ''
+
+  print *, 'Setting different activation functions for each layer of network 1'
+  call net1 % set_activation([character(len=10) :: 'sigmoid', 'tanh', 'gaussian'])
+  print *, 'Save network 1 into file'
+  call net1 % save('test_network.dat')
+  call net2 % load('test_network.dat')
+  print *, 'Load network 2 from file'
+  do n = 1, size(net1 % layers)
+    print *, 'Layer ', n, ', activation functions equal:',&
+     associated(net1 % layers(n) % activation, net2 % layers(n) % activation),&
+     '(network 1: ', net1 % layers(n) % activation_str, ', network 2: ', net2 % layers(n) % activation_str,')'
+  end do  
 end program test_network_save