Replace Agnostic with Adaptive

Author: BatyLeo

test/argmax.jl

@@ -116,7 +116,8 @@ end
             one_hot_argmax;
             Ω=half_square_norm,
             Ω_grad=identity_kw,
-            frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+            # frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+            frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
         ),
         loss=mse_kw,
         error_function=hamming_distance,
@@ -198,7 +199,8 @@ end
                 one_hot_argmax;
                 Ω=half_square_norm,
                 Ω_grad=identity_kw,
-                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
+                # frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
             ),
         ),
         error_function=hamming_distance,

test/paths.jl

@@ -101,7 +101,7 @@ end
             shortest_path_maximizer;
             Ω=half_square_norm,
             Ω_grad=identity_kw,
-            frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+            frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
         ),
         loss=mse_kw,
         error_function=mse_kw,
@@ -177,7 +177,7 @@ end
                 shortest_path_maximizer;
                 Ω=half_square_norm,
                 Ω_grad=identity_kw,
-                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
             ),
         ),
         error_function=mse_kw,
@@ -247,7 +247,7 @@ end
                 shortest_path_maximizer;
                 Ω=half_square_norm,
                 Ω_grad=identity_kw,
-                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
             ),
             cost,
         ),

test/ranking.jl

@@ -101,7 +101,7 @@ end
             ranking;
             Ω=half_square_norm,
             Ω_grad=identity_kw,
-            frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+            frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
         ),
         loss=mse_kw,
         error_function=hamming_distance,
@@ -170,7 +170,7 @@ end
                 ranking;
                 Ω=half_square_norm,
                 Ω_grad=identity_kw,
-                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
             ),
         ),
         error_function=hamming_distance,
@@ -303,7 +303,7 @@ end
                 ranking;
                 Ω=half_square_norm,
                 Ω_grad=identity_kw,
-                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Agnostic()),
+                frank_wolfe_kwargs=(; max_iteration=10, line_search=FrankWolfe.Adaptive()),
             ),
             cost,
         ),