mapreduce: don't inbounds unknown functions (JuliaLang#55329)

More finely scope the `@inbounds` annotations to ensure neither `f` nor
`op` are erroneously `@inbounds`ed.

Author: mbauman

base/reduce.jl

@@ -638,11 +638,11 @@ function mapreduce_impl(f, op::Union{typeof(max), typeof(min)},
     start = first + 1
     simdstop  = start + chunk_len - 4
     while simdstop <= last - 3
-        @inbounds for i in start:4:simdstop
-            v1 = _fast(op, v1, f(A[i+0]))
-            v2 = _fast(op, v2, f(A[i+1]))
-            v3 = _fast(op, v3, f(A[i+2]))
-            v4 = _fast(op, v4, f(A[i+3]))
+        for i in start:4:simdstop
+            v1 = _fast(op, v1, f(@inbounds(A[i+0])))
+            v2 = _fast(op, v2, f(@inbounds(A[i+1])))
+            v3 = _fast(op, v3, f(@inbounds(A[i+2])))
+            v4 = _fast(op, v4, f(@inbounds(A[i+3])))
         end
         checkbounds(A, simdstop+3)
         start += chunk_len

base/reducedim.jl

@@ -269,19 +269,20 @@ function _mapreducedim!(f, op, R::AbstractArray, A::AbstractArrayOrBroadcasted)
     if reducedim1(R, A)
         # keep the accumulator as a local variable when reducing along the first dimension
         i1 = first(axes1(R))
-        @inbounds for IA in CartesianIndices(indsAt)
+        for IA in CartesianIndices(indsAt)
             IR = Broadcast.newindex(IA, keep, Idefault)
-            r = R[i1,IR]
+            @inbounds r = R[i1,IR]
             @simd for i in axes(A, 1)
-                r = op(r, f(A[i, IA]))
+                r = op(r, f(@inbounds(A[i, IA])))
             end
-            R[i1,IR] = r
+            @inbounds R[i1,IR] = r
         end
     else
-        @inbounds for IA in CartesianIndices(indsAt)
+        for IA in CartesianIndices(indsAt)
             IR = Broadcast.newindex(IA, keep, Idefault)
             @simd for i in axes(A, 1)
-                R[i,IR] = op(R[i,IR], f(A[i,IA]))
+                v = op(@inbounds(R[i,IR]), f(@inbounds(A[i,IA])))
+                @inbounds R[i,IR] = v
             end
         end
     end
@@ -1025,33 +1026,33 @@ function findminmax!(f, op, Rval, Rind, A::AbstractArray{T,N}) where {T,N}
     zi = zero(eltype(ks))
     if reducedim1(Rval, A)
         i1 = first(axes1(Rval))
-        @inbounds for IA in CartesianIndices(indsAt)
+        for IA in CartesianIndices(indsAt)
             IR = Broadcast.newindex(IA, keep, Idefault)
-            tmpRv = Rval[i1,IR]
-            tmpRi = Rind[i1,IR]
+            @inbounds tmpRv = Rval[i1,IR]
+            @inbounds tmpRi = Rind[i1,IR]
             for i in axes(A,1)
                 k, kss = y::Tuple
-                tmpAv = f(A[i,IA])
+                tmpAv = f(@inbounds(A[i,IA]))
                 if tmpRi == zi || op(tmpRv, tmpAv)
                     tmpRv = tmpAv
                     tmpRi = k
                 end
                 y = iterate(ks, kss)
             end
-            Rval[i1,IR] = tmpRv
-            Rind[i1,IR] = tmpRi
+            @inbounds Rval[i1,IR] = tmpRv
+            @inbounds Rind[i1,IR] = tmpRi
         end
     else
-        @inbounds for IA in CartesianIndices(indsAt)
+        for IA in CartesianIndices(indsAt)
             IR = Broadcast.newindex(IA, keep, Idefault)
             for i in axes(A, 1)
                 k, kss = y::Tuple
-                tmpAv = f(A[i,IA])
-                tmpRv = Rval[i,IR]
-                tmpRi = Rind[i,IR]
+                tmpAv = f(@inbounds(A[i,IA]))
+                @inbounds tmpRv = Rval[i,IR]
+                @inbounds tmpRi = Rind[i,IR]
                 if tmpRi == zi || op(tmpRv, tmpAv)
-                    Rval[i,IR] = tmpAv
-                    Rind[i,IR] = k
+                    @inbounds Rval[i,IR] = tmpAv
+                    @inbounds Rind[i,IR] = k
                 end
                 y = iterate(ks, kss)
             end

test/reducedim.jl

@@ -587,6 +587,30 @@ end
     @test B[argmin(B, dims=[2, 3])] == @inferred(minimum(B, dims=[2, 3]))
 end
 
+@testset "careful with @inbounds" begin
+    Base.@propagate_inbounds f(x) = x == 2 ? x[-10000] : x
+    Base.@propagate_inbounds op(x,y) = x[-10000] + y[-10000]
+    for (arr, dims) in (([1,1,2], 1), ([1 1 2], 2), ([ones(Int,256);2], 1))
+        @test_throws BoundsError mapreduce(f, +, arr)
+        @test_throws BoundsError mapreduce(f, +, arr; dims)
+        @test_throws BoundsError mapreduce(f, +, arr; dims, init=0)
+        @test_throws BoundsError mapreduce(identity, op, arr)
+        try
+            #=@test_throws BoundsError=# mapreduce(identity, op, arr; dims)
+        catch ex
+            @test_broken ex isa BoundsError
+        end
+        @test_throws BoundsError mapreduce(identity, op, arr; dims, init=0)
+
+        @test_throws BoundsError findmin(f, arr)
+        @test_throws BoundsError findmin(f, arr; dims)
+
+        @test_throws BoundsError mapreduce(f, max, arr)
+        @test_throws BoundsError mapreduce(f, max, arr; dims)
+        @test_throws BoundsError mapreduce(f, max, arr; dims, init=0)
+    end
+end
+
 @testset "in-place reductions with mismatched dimensionalities" begin
     B = reshape(1:24, 4, 3, 2)
     for R in (fill(0, 4), fill(0, 4, 1), fill(0, 4, 1, 1))