feat: more 1.12 support

src/TracedRArray.jl

@@ -1109,6 +1109,19 @@ function Base.accumulate_pairwise!(op, A::AnyTracedRVector, B::AnyTracedRVector)
     return accumulate!(op, A, B; dims=1)
 end
 
+if isdefined(Base, :_accumulate_promote_op)
+    function Base._accumulate_promote_op(op, A::AnyTracedRArray{T}; init=nothing) where {T}
+        if init !== nothing
+            init isa TracedRNumber && (init = zero(unwrapped_eltype(init)))
+        end
+        return TracedRNumber{
+            unwrapped_eltype(
+                Base._accumulate_promote_op(op, Array{T,ndims(A)}(undef, size(A)); init)
+            ),
+        }
+    end
+end
+
 function Base._accumulate!(
     op, output::AnyTracedRArray, input::AnyTracedRVector, ::Nothing, ::Nothing
 )

src/stdlibs/LinearAlgebra.jl

@@ -273,26 +273,56 @@ function overloaded_mul!(
     return C
 end
 
-function LinearAlgebra.triu!(@nospecialize(X::TracedRArray{T,2}), k::Integer) where {T}
+if isdefined(LinearAlgebra, :_triu)
+    function LinearAlgebra._triu(A::AnyTracedRArray{T,2}, ::Val{true}, k::Integer) where {T}
+        return overloaded_triu(materialize_traced_array(A), k)
+    end
+    function LinearAlgebra._triu(
+        A::AnyTracedRArray{T,2}, ::Val{false}, k::Integer
+    ) where {T}
+        return overloaded_triu(materialize_traced_array(A), k)
+    end
+end
+
+if isdefined(LinearAlgebra, :_tril)
+    function LinearAlgebra._tril(A::AnyTracedRArray{T,2}, ::Val{true}, k::Integer) where {T}
+        return overloaded_tril(materialize_traced_array(A), k)
+    end
+    function LinearAlgebra._tril(
+        A::AnyTracedRArray{T,2}, ::Val{false}, k::Integer
+    ) where {T}
+        return overloaded_tril(materialize_traced_array(A), k)
+    end
+end
+
+function LinearAlgebra.triu!(X::AnyTracedRArray{T,2}, k::Integer) where {T}
+    set_mlir_data!(X, get_mlir_data(overloaded_triu(materialize_traced_array(X), k)))
+    return X
+end
+
+function LinearAlgebra.tril!(X::AnyTracedRArray{T,2}, k::Integer) where {T}
+    set_mlir_data!(X, get_mlir_data(overloaded_tril(materialize_traced_array(X), k)))
+    return X
+end
+
+function overloaded_triu(X::TracedRArray{T,2}, k::Integer) where {T}
     iota_1 = @opcall iota(Int64, [size(X)...]; iota_dimension=1)
     iota_2 = @opcall subtract(
         @opcall(iota(Int64, [size(X)...]; iota_dimension=2)),
         Reactant.broadcast_to_size(k, size(X)),
     )
     idxs = @opcall compare(iota_1, iota_2; comparison_direction="LE")
-    X.mlir_data = @opcall(select(idxs, X, zero(X))).mlir_data
-    return X
+    return @opcall select(idxs, X, zero(X))
 end
 
-function LinearAlgebra.tril!(@nospecialize(X::TracedRArray{T,2}), k::Integer) where {T}
+function overloaded_tril(X::TracedRArray{T,2}, k::Integer) where {T}
     iota_1 = @opcall iota(Int64, [size(X)...]; iota_dimension=1)
     iota_2 = @opcall subtract(
         @opcall(iota(Int64, [size(X)...]; iota_dimension=2)),
         Reactant.broadcast_to_size(k, size(X)),
     )
     idxs = @opcall compare(iota_1, iota_2; comparison_direction="GE")
-    X.mlir_data = @opcall(select(idxs, X, zero(X))).mlir_data
-    return X
+    return @opcall select(idxs, X, zero(X))
 end
 
 # LinearAlgebra defines norm with some conditionals which cannot be traced directly

test/runtests.jl

@@ -53,12 +53,16 @@ const REACTANT_TEST_GROUP = lowercase(get(ENV, "REACTANT_TEST_GROUP", "all"))
         @safetestset "Python" include("integration/python.jl")
         @safetestset "Optimisers" include("integration/optimisers.jl")
         @safetestset "FillArrays" include("integration/fillarrays.jl")
-        @safetestset "Zygote" include("integration/zygote.jl")
         @safetestset "MPI" begin
             using MPI
             nranks = 2
             run(`$(mpiexec()) -n $nranks $(Base.julia_cmd()) integration/mpi.jl`)
         end
+
+        # Zygote is not supported on 1.12 https://github.com/FluxML/Zygote.jl/issues/1580
+        if VERSION < v"1.12-"
+            @safetestset "Zygote" include("integration/zygote.jl")
+        end
     end
 
     if REACTANT_TEST_GROUP == "all" || REACTANT_TEST_GROUP == "neural_networks"