Use new DI patch

Author: penelopeysm

test/Project.toml

@@ -33,6 +33,7 @@ AdvancedHMC = "0.6, 0.7, 0.8"
 ChainRulesTestUtils = "0.7, 1"
 ChangesOfVariables = "0.1"
 Combinatorics = "1.0.2"
+DifferentiationInterface = "0.7.7"
 DistributionsAD = "0.6.3"
 Documenter = "1"
 Enzyme = "0.13.12"

test/ad/corr.jl

@@ -34,20 +34,11 @@ end
         cholesky_to_triangular =
             uplo == 'U' ? Bijectors.cholesky_upper : Bijectors.cholesky_lower
 
-        if adtype isa AutoEnzyme{<:ForwardMode} && d == 1
-            # For d == 1, y has length 0, and DI doesn't handle this well
-            # https://github.com/JuliaDiff/DifferentiationInterface.jl/issues/802
-            @test_throws DivideError test_ad(y -> sum(transform(b, binv(y))), adtype, y)
-            @test_throws DivideError test_ad(
-                y -> sum(cholesky_to_triangular(transform(binv, y))), adtype, y
-            )
-        else
-            # roundtrip
-            test_ad(y -> sum(transform(b, binv(y))), adtype, y)
-            # inverse (we need to tack on `cholesky_upper`/`cholesky_lower`,
-            # because directly calling `sum` on a LinearAlgebra.Cholesky doesn't
-            # give a scalar)
-            test_ad(y -> sum(cholesky_to_triangular(transform(binv, y))), adtype, y)
-        end
+        # roundtrip
+        test_ad(y -> sum(transform(b, binv(y))), adtype, y)
+        # inverse (we need to tack on `cholesky_upper`/`cholesky_lower`,
+        # because directly calling `sum` on a LinearAlgebra.Cholesky doesn't
+        # give a scalar)
+        test_ad(y -> sum(cholesky_to_triangular(transform(binv, y))), adtype, y)
     end
 end