Merge branch 'fix-tests-manopt-update' into add-MvNormalMeanScalePrec…

…ision
ReactiveBayes · Oct 23, 2024 · 82161b1 · 82161b1
2 parents 7760a14 + b5f3b70
commit 82161b1
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Showing 4 changed files with 10 additions and 10 deletions.
diff --git a/test/manopt_setuptests.jl b/test/manopt_setuptests.jl
@@ -16,7 +16,7 @@ function (sc::StopWhenGradientNormLessNonAllocating)(mp, s, i)
     return false
 end
 
-# Non allocating version of the same `ConstantStepsize` from `Manopt.jl`
+# Non allocating version of the same `ConstantLength` from `Manopt.jl`
 struct ConstantStepsizeNonAllocating{T} <: Stepsize
     stepsize::T
 end

diff --git a/test/shifted_negative_numbers_tests.jl b/test/shifted_negative_numbers_tests.jl
@@ -159,7 +159,7 @@ end
         b in (10.0, 5.0),
         c in (1.0, 10.0, -1.0),
         eps in (1e-4, 1e-5, 1e-8, 1e-10),
-        stepsize in (ConstantStepsize(0.1), ConstantStepsize(0.01), ConstantStepsize(0.001))
+        stepsize in (ConstantLength(0.1), ConstantLength(0.01), ConstantLength(0.001))
 
         expected_q = -b / 2a
         expected_minimum = c - b^2 / (4a)
@@ -232,11 +232,11 @@ end
         obj = ManifoldGradientObjective(missing, grad_f!; evaluation=InplaceEvaluation())
         dmp = DefaultManoptProblem(M, obj)
         s = GradientDescentState(
-            M,
-            q;
+            M;
+            p = q,
             stopping_criterion=StopWhenGradientNormLessNonAllocating(1e-8),
             stepsize=ConstantStepsizeNonAllocating(0.1),
-            direction=IdentityUpdateRule(),
+            direction=Manopt.IdentityUpdateRule(),
             retraction_method=default_retraction_method(M, typeof(q)),
             X=zero_vector(M, q),
         )

diff --git a/test/shifted_positive_numbers_tests.jl b/test/shifted_positive_numbers_tests.jl
@@ -159,7 +159,7 @@ end
         b in (-10.0, -5.0),
         c in (1.0, 10.0, -1.0),
         eps in (1e-4, 1e-5, 1e-8, 1e-10),
-        stepsize in (ConstantStepsize(0.1), ConstantStepsize(0.01), ConstantStepsize(0.001))
+        stepsize in (ConstantLength(0.1), ConstantLength(0.01), ConstantLength(0.001))
 
         expected_q = -b / 2a
         expected_minimum = c - b^2 / (4a)
@@ -231,11 +231,11 @@ end
         obj = ManifoldGradientObjective(missing, grad_f!; evaluation=InplaceEvaluation())
         dmp = DefaultManoptProblem(M, obj)
         s = GradientDescentState(
-            M,
-            q;
+            M;
+            p = q,
             stopping_criterion=StopWhenGradientNormLessNonAllocating(1e-8),
             stepsize=ConstantStepsizeNonAllocating(0.1),
-            direction=IdentityUpdateRule(),
+            direction=Manopt.IdentityUpdateRule(),
             retraction_method=default_retraction_method(M, typeof(q)),
             X=zero_vector(M, q),
         )

diff --git a/test/single_point_manifold_tests.jl b/test/single_point_manifold_tests.jl
@@ -82,7 +82,7 @@ end
         b in (10.0, 5.0),
         c in (1.0, 10.0, -1.0),
         eps in (1e-4, 1e-5, 1e-8, 1e-10),
-        stepsize in (ConstantStepsize(0.1), ConstantStepsize(0.01), ConstantStepsize(0.001))
+        stepsize in (ConstantLength(0.1), ConstantLength(0.01), ConstantLength(0.001))
 
         f(M, x) = (a .* x .^ 2 .+ b .* x .+ c)[1]
         grad_f(M, x) = 2 .* a .* x .+ b