From 084259d663e2913efadb75520dde9d2ed8c0c4b0 Mon Sep 17 00:00:00 2001
From: Kamal Saleh <kamal.saleh@web.de>
Date: Tue, 9 Jul 2024 14:15:51 +0200
Subject: [PATCH] bug fix in SigmoidBinaryCrossEntropyLoss

---
 PackageInfo.g                               |  2 +-
 gap/CategoryOfParametrisedMorphisms.gi      |  5 +++--
 gap/CategoryOfSkeletalSmoothMaps.gi         |  2 +-
 tst/categorical_vs_direct_constructions.tst | 25 +++++++++++++++++++++
 4 files changed, 30 insertions(+), 4 deletions(-)
 create mode 100644 tst/categorical_vs_direct_constructions.tst

diff --git a/PackageInfo.g b/PackageInfo.g
index c05bb33..dc44739 100644
--- a/PackageInfo.g
+++ b/PackageInfo.g
@@ -10,7 +10,7 @@ SetPackageInfo( rec(
 
 PackageName := "MachineLearningForCAP",
 Subtitle := "Exploring categorical machine learning in CAP",
-Version := "2024.07-04",
+Version := "2024.07-09",
 Date := (function ( ) if IsBound( GAPInfo.SystemEnvironment.GAP_PKG_RELEASE_DATE ) then return GAPInfo.SystemEnvironment.GAP_PKG_RELEASE_DATE; else return Concatenation( ~.Version{[ 1 .. 4 ]}, "-", ~.Version{[ 6, 7 ]}, "-01" ); fi; end)( ),
 License := "GPL-2.0-or-later",
 
diff --git a/gap/CategoryOfParametrisedMorphisms.gi b/gap/CategoryOfParametrisedMorphisms.gi
index 425aee3..f2f19de 100644
--- a/gap/CategoryOfParametrisedMorphisms.gi
+++ b/gap/CategoryOfParametrisedMorphisms.gi
@@ -446,7 +446,8 @@ InstallOtherMethod( \.,
         end;
         
     elif f in [ "Constant", "Zero", "IdFunc", "Sum", "Mean", "Mul", "Power", "PowerBase", "Relu", "Sigmoid_", "Sigmoid", "Softmax_", "Softmax",
-                "QuadraticLoss_", "QuadraticLoss", "CrossEntropyLoss_", "CrossEntropyLoss", "SoftmaxCrossEntropyLoss_", "SoftmaxCrossEntropyLoss" ] then
+                "QuadraticLoss_", "QuadraticLoss", "CrossEntropyLoss_", "CrossEntropyLoss", "SoftmaxCrossEntropyLoss_", "SoftmaxCrossEntropyLoss",
+                "SigmoidBinaryCrossEntropyLoss_", "SigmoidBinaryCrossEntropyLoss" ] then
       
       return
         function ( arg... )
@@ -455,7 +456,7 @@ InstallOtherMethod( \.,
           
         end;
         
-    elif f in [ "Sqrt", "Exp", "Log", "Sin", "Cos", "SigmoidBinaryCrossEntropyLoss_", "SigmoidBinaryCrossEntropyLoss" ] then
+    elif f in [ "Sqrt", "Exp", "Log", "Sin", "Cos" ] then
         
         return C.( f ) / Para;
         
diff --git a/gap/CategoryOfSkeletalSmoothMaps.gi b/gap/CategoryOfSkeletalSmoothMaps.gi
index 9f6499d..8787a9b 100644
--- a/gap/CategoryOfSkeletalSmoothMaps.gi
+++ b/gap/CategoryOfSkeletalSmoothMaps.gi
@@ -1408,7 +1408,7 @@ InstallOtherMethod( \.,
             
             return PreCompose( Smooth,
                       DirectProductFunctorial( Smooth, [ Smooth.Sigmoid_( 1 ), Smooth.IdFunc( 1 ) ] ),
-                      Smooth.BinaryCrossEntropyLoss_ );
+                      Smooth.BinaryCrossEntropyLoss_( n ) );
             
           end;
           
diff --git a/tst/categorical_vs_direct_constructions.tst b/tst/categorical_vs_direct_constructions.tst
new file mode 100644
index 0000000..b5e83d3
--- /dev/null
+++ b/tst/categorical_vs_direct_constructions.tst
@@ -0,0 +1,25 @@
+gap> Smooth := SkeletalSmoothMaps;;
+gap> Lenses := CategoryOfLenses( Smooth );;
+gap> Para := CategoryOfParametrisedMorphisms( Smooth );;
+gap> Assert( 0, Para.Softmax_( 3 ) = Para.Softmax( 3 ) );
+gap> Assert( 0, Para.Sigmoid_( 3 ) = Para.Sigmoid( 3 ) );
+gap> Assert( 0, Para.QuadraticLoss_( 3 ) = Para.QuadraticLoss( 3 ) );
+gap> Assert( 0, Para.CrossEntropyLoss_( 3 ) = Para.CrossEntropyLoss( 3 ) );
+gap> Assert( 0, Para.SoftmaxCrossEntropyLoss_( 3 ) = Para.SoftmaxCrossEntropyLoss( 3 ) );
+gap> Assert( 0, Para.QuadraticLoss_( 3 ) = Para.QuadraticLoss( 3 ) );
+gap> Assert( 0, Para.QuadraticLoss_( 3 ) = Para.QuadraticLoss( 3 ) );
+gap> Assert( 0, Para.SigmoidBinaryCrossEntropyLoss_( 1 ) = Para.SigmoidBinaryCrossEntropyLoss( 1 ) );
+gap> Assert( 0, Para.AffineTransformation_( 3, 4 ) = Para.AffineTransformation( 3, 4 ) );
+gap> Eval( Smooth.PolynomialTransformation( 2, 3, 4 ), [ 1 .. 47 ] );
+[ 122341573, 479204128, 836066683 ]
+gap> EvalJacobianMatrix( Smooth.PolynomialTransformation( 2, 3, 4 ), [ 1 .. 47 ] );
+[ [ 4477456, 4574792, 97336, 4674244, 99452, 2116, 4775858, 101614, 2162, 46, 4879681, 103823, 2209, 47, 1, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2585050, 7818740 ],
+  [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4477456, 4574792, 97336, 4674244, 99452, 2116, 4775858, 101614, 2162, 46,
+      4879681, 103823, 2209, 47, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17701630, 23262470 ],
+  [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4477456, 4574792, 97336,
+      4674244, 99452, 2116, 4775858, 101614, 2162, 46, 4879681, 103823, 2209, 47, 1, 32818210, 38706200 ] ]
+gap> Assert( 0, Lenses.GradientDescentOptimizer_( )( 3 ) = Lenses.GradientDescentOptimizer( )( 3 ) );
+gap> Assert( 0, Lenses.GradientDescentWithMomentumOptimizer_( )( 3 ) = Lenses.GradientDescentWithMomentumOptimizer( )( 3 ) );
+gap> Assert( 0, Lenses.AdagradOptimizer_( )( 3 ) = Lenses.AdagradOptimizer( )( 3 ) );
+gap> Assert( 0, Lenses.AdamOptimizer_( )( 3 ) = Lenses.AdamOptimizer( )( 3 ) );