WIP

src/nf/nf_layer.f90

@@ -30,9 +30,9 @@ module nf_layer
     procedure :: get_params
     procedure :: get_gradients
     procedure :: set_params
+    procedure :: set_state
     procedure :: init
     procedure :: print_info
-    procedure :: reset
 
     ! Specific subroutines for different array ranks
     procedure, private :: backward_1d
@@ -154,9 +154,10 @@ module subroutine set_params(self, params)
         !! Parameters of this layer
     end subroutine set_params
 
-    module subroutine reset(self)
-      class(layer), intent(in out) :: self
-    end subroutine reset
+    module subroutine set_state(self, state)
+      class(layer), intent(inout) :: self
+      real, intent(in), optional :: state(:)
+    end subroutine set_state
 
   end interface
 

src/nf/nf_layer_constructors_submodule.f90

@@ -81,7 +81,6 @@ pure module function input1d(layer_size) result(res)
     res % initialized = .true.
   end function input1d
 
-
   pure module function input3d(layer_shape) result(res)
     integer, intent(in) :: layer_shape(3)
     type(layer) :: res

src/nf/nf_layer_submodule.f90

@@ -442,14 +442,18 @@ module subroutine set_params(self, params)
 
   end subroutine set_params
 
-  module subroutine reset(self)
-    class(layer), intent(in out) :: self
+  subroutine set_state(self, state)
+    class(layer), intent(inout) :: self
+    real, intent(in), optional :: state(:)
 
     select type (this_layer => self % p)
       type is (rnn_layer)
-        call this_layer % reset()
-    end select
-
-  end subroutine reset
+        if (present(state)) then
+          this_layer % state = state
+        else
+          this_layer % state = 0
+        end if
+      end select
+  end subroutine set_state
 
 end submodule nf_layer_submodule

src/nf/nf_network.f90

@@ -23,7 +23,6 @@ module nf_network
     procedure :: get_params
     procedure :: print_info
     procedure :: set_params
-    procedure :: reset
     procedure :: train
     procedure :: update
 
@@ -224,13 +223,6 @@ module subroutine update(self, optimizer, batch_size)
         !! Set to `size(input_data, dim=2)` for a batch gradient descent.
     end subroutine update
 
-    module subroutine reset(self)
-      !! Reset network state
-      !!
-      !! Currently only affect RNN layer type
-      class(network), intent(in out) :: self
-    end subroutine reset
-
   end interface
 
 end module nf_network

src/nf/nf_network_submodule.f90

@@ -676,23 +676,12 @@ module subroutine update(self, optimizer, batch_size)
         type is(conv2d_layer)
           this_layer % dw = 0
           this_layer % db = 0
-      end select
-    end do
-
-  end subroutine update
-
-  module subroutine reset(self)
-    class(network), intent(in out) :: self
-    integer :: n, num_layers
-
-    num_layers = size(self % layers)
-    do n = 2, num_layers
-      select type(this_layer => self % layers(n) % p)
         type is(rnn_layer)
-          call self % layers(n) % reset()
+          this_layer % dw = 0
+          this_layer % db = 0
       end select
     end do
 
-  end subroutine reset
+  end subroutine update
 
 end submodule nf_network_submodule

src/nf/nf_rnn_layer.f90

@@ -14,7 +14,7 @@ module nf_rnn_layer
 
   type, extends(base_layer) :: rnn_layer
 
-    !! Concrete implementation of a dense (fully-connected) layer type
+    !! Concrete implementation of an RNN (fully-connected) layer type
 
     integer :: input_size
     integer :: output_size
@@ -40,7 +40,7 @@ module nf_rnn_layer
     procedure :: get_params
     procedure :: init
     procedure :: set_params
-    procedure :: reset
+    procedure :: set_state
 
   end type rnn_layer
 
@@ -94,7 +94,7 @@ pure module function get_params(self) result(params)
       !! Return the parameters (weights and biases) of this layer.
       !! The parameters are ordered as weights first, biases second.
       class(rnn_layer), intent(in) :: self
-        !! Dense layer instance
+        !! RNN layer instance
       real, allocatable :: params(:)
         !! Parameters of this layer
     end function get_params
@@ -137,4 +137,14 @@ end subroutine reset
 
   end interface
 
+  subroutine set_state(self, state)
+    type(rnn_layer), intent(inout) :: self
+    real, intent(in), optional :: state(:)
+    if (present(state)) then
+      self % state = state
+    else
+      self % state = 0
+    end if
+  end subroutine set_state
+
 end module nf_rnn_layer