Fix CI AD tests

ext/IntegralsMooncakeExt.jl

@@ -3,7 +3,7 @@ using Mooncake
 using LinearAlgebra: dot
 using Integrals, SciMLBase, QuadGK
 using Mooncake: @from_chainrules, @is_primitive, increment!!, MinimalCtx, rrule!!, NoFData,
-    NoRData, CoDual, primal, NoRData, zero_fcodual
+    CoDual, primal, NoRData, zero_fcodual
 import Mooncake: increment_and_get_rdata!, @zero_derivative
 using Integrals: AbstractIntegralMetaAlgorithm, IntegralProblem
 import ChainRulesCore
@@ -116,7 +116,7 @@ end
 # Allows clear translation from ChainRules -> Mooncake's tangent.
 function Mooncake.increment_and_get_rdata!(
         f::NoFData, r::Tuple{T, T},
-        t::Union{Tangent{Tuple{T, T}, Tuple{T, T}}, Tangent{Any, Tuple{Float64, Float64}}}
+        t::Union{Tangent{Tuple{T, T}, Tuple{T, T}}, Tangent{Any, Tuple{T, T}}}
     ) where {T <: Base.IEEEFloat}
     return r .+ t.backing
 end
@@ -234,13 +234,22 @@ function Mooncake.increment_and_get_rdata!(
     return t.prob.domain
 end
 
-# cannot mutate NoRData() in place, therefore return as is.
 function Mooncake.increment!!(
         ::Mooncake.NoRData,
         y::Tangent{Any, Y}
     ) where {
         T <: Base.IEEEFloat, Y <: Union{Tuple{T, T}, Tuple{Vector{T}, Vector{T}}},
     }
-    return Mooncake.NoRData()
+    return NoRData()
+end
+
+function Mooncake.increment!!(
+        x::Tangent{Any, Y},
+        ::Mooncake.NoRData
+    ) where {
+        T <: Base.IEEEFloat, Y <: Union{Tuple{T, T}, Tuple{Vector{T}, Vector{T}}},
+    }
+    return x
 end
+
 end

test/derivative_tests.jl

@@ -182,7 +182,6 @@ do_tests_mooncake = function (; f, scalarize, lb, ub, p, alg, abstol, reltol)
     end
     sol_fp = testf(lb, ub, p)
 
-    # sensealg when non zygoet?
     cache = Mooncake.prepare_gradient_cache(
         testf, lb, ub, p isa Number && f isa BatchIntegralFunction ? Scalar(p) : p
     )