feat: inherit scalar indexing functionality from GPUArraysCore (#268)

* feat: inherit scalar indexing functionality from GPUArraysCore

* chore: run formatter

* fix: always warn inside tracing unless opt-out

* chore: reexport @allowscalar

* feat: add isapprox for array types

* fix: test fixes for scalar indexing

* fix: allow scalar indexing in gather

Project.toml

@@ -8,6 +8,7 @@ Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 CEnum = "fa961155-64e5-5f13-b03f-caf6b980ea82"
 Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
 Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
+GPUArraysCore = "46192b85-c4d5-4398-a991-12ede77f4527"
 Libdl = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
@@ -35,6 +36,7 @@ ArrayInterface = "7.10"
 CEnum = "0.4, 0.5"
 Downloads = "1.6"
 Enzyme = "0.13"
+GPUArraysCore = "0.1, 0.2"
 LinearAlgebra = "1.10"
 NNlib = "0.9"
 OrderedCollections = "1"

ext/ReactantNNlibExt.jl

@@ -1,6 +1,7 @@
 module ReactantNNlibExt
 
 using NNlib
+using GPUArraysCore: @allowscalar
 using Reactant:
     Reactant, TracedRArray, AnyTracedRArray, materialize_traced_array, MLIR, TracedRNumber
 using ReactantCore: @trace
@@ -367,7 +368,7 @@ function NNlib.gather!(dst::TracedRArray, src::AnyTracedRArray, idxs::AbstractAr
     colons = ntuple(Returns(Colon()), dims)
     start_sizes = ntuple(i -> size(src, i), dims)
     results = map(CartesianIndices(idxs)) do k
-        res = src[colons..., Tuple(idxs[k])...]
+        res = @allowscalar src[colons..., Tuple(idxs[k])...]
         res isa TracedRNumber && (res = Reactant.broadcast_to_size(res, (1,)))
         return reshape(res, start_sizes..., :)
     end

src/ConcreteRArray.jl

@@ -86,6 +86,7 @@ function Base.convert(::Type{T}, X::ConcreteRArray{ElType,N}) where {T<:Array,El
     return data
     # XLA.from_row_major(data)
 end
+Base.Array(x::ConcreteRArray) = convert(Array, x)
 
 function synchronize(x::Union{ConcreteRArray,ConcreteRNumber})
     XLA.synced_buffer(x.data)
@@ -145,6 +146,20 @@ for T in (ConcreteRNumber, ConcreteRArray{<:Any,0})
     end
 end
 
+function Base.isapprox(x::ConcreteRArray, y::AbstractArray; kwargs...)
+    return Base.isapprox(convert(Array, x), convert(Array, y); kwargs...)
+end
+function Base.isapprox(x::AbstractArray, y::ConcreteRArray; kwargs...)
+    return Base.isapprox(convert(Array, x), convert(Array, y); kwargs...)
+end
+function Base.isapprox(x::ConcreteRArray, y::ConcreteRArray; kwargs...)
+    return Base.isapprox(convert(Array, x), convert(Array, y); kwargs...)
+end
+
+Base.:(==)(x::ConcreteRArray, y::AbstractArray) = convert(Array, x) == convert(Array, y)
+Base.:(==)(x::AbstractArray, y::ConcreteRArray) = convert(Array, x) == convert(Array, y)
+Base.:(==)(x::ConcreteRArray, y::ConcreteRArray) = convert(Array, x) == convert(Array, y)
+
 function Base.show(io::IO, X::ConcreteRScalar{T}) where {T}
     if X.data == XLA.AsyncEmptyBuffer
         println(io, "<Empty buffer>")
@@ -171,12 +186,11 @@ function Base.show(io::IO, X::ConcreteRArray)
     return print(io, "$(typeof(X))($(str))")
 end
 
-const getindex_warned = Ref(false)
 function Base.getindex(a::ConcreteRArray{T}, args::Vararg{Int,N}) where {T,N}
     if a.data == XLA.AsyncEmptyBuffer
         throw("Cannot getindex from empty buffer")
     end
-    # error("""Scalar indexing is disallowed.""")
+
     XLA.await(a.data)
     if XLA.BufferOnCPU(a.data.buffer)
         buf = a.data.buffer
@@ -193,16 +207,8 @@ function Base.getindex(a::ConcreteRArray{T}, args::Vararg{Int,N}) where {T,N}
             return unsafe_load(ptr, start)
         end
     end
-    if !getindex_warned[]
-        @warn(
-            """Performing scalar get-indexing on task $(current_task()).
-    Invocation resulted in scalar indexing of a ConcreteRArray.
-    This is typically caused by calling an iterating implementation of a method.
-    Such implementations *do not* execute on device, but very slowly on the CPU,
-    and require expensive copies and synchronization each time and therefore should be avoided."""
-        )
-        getindex_warned[] = true
-    end
+
+    GPUArraysCore.assertscalar("getindex(::ConcreteRArray, ::Vararg{Int, N})")
     return convert(Array, a)[args...]
 end
 
@@ -211,12 +217,11 @@ function mysetindex!(a, v, args::Vararg{Int,N}) where {N}
     return nothing
 end
 
-const setindex_warned = Ref(false)
-
 function Base.setindex!(a::ConcreteRArray{T}, v, args::Vararg{Int,N}) where {T,N}
     if a.data == XLA.AsyncEmptyBuffer
         throw("Cannot setindex! to empty buffer")
     end
+
     XLA.await(a.data)
     if XLA.BufferOnCPU(a.data.buffer)
         buf = a.data.buffer
@@ -234,19 +239,8 @@ function Base.setindex!(a::ConcreteRArray{T}, v, args::Vararg{Int,N}) where {T,N
         end
         return a
     end
-    if !setindex_warned[]
-        @warn(
-            """Performing scalar set-indexing on task $(current_task()).
-    Invocation resulted in scalar indexing of a ConcreteRArray.
-    This is typically caused by calling an iterating implementation of a method.
-    Such implementations *do not* execute on device, but very slowly on the CPU,
-    and require expensive copies and synchronization each time and therefore should be avoided.
- 
-    This error message will only be printed for the first invocation for brevity.
-"""
-        )
-        setindex_warned[] = true
-    end
+
+    GPUArraysCore.assertscalar("setindex!(::ConcreteRArray, ::Any, ::Vararg{Int, N})")
     fn = Reactant.compile(mysetindex!, (a, v, args...))
     fn(a, v, args...)
     return a

src/Reactant.jl

@@ -4,6 +4,9 @@ using ReactantCore: ReactantCore, @trace, MissingTracedValue
 
 using LinearAlgebra: LinearAlgebra
 using Adapt: Adapt, WrappedArray
+using GPUArraysCore: GPUArraysCore, @allowscalar, allowscalar # keep this import to allow users to do `Reactant.allowscalar(false)`
+
+export @allowscalar # re-exported from GPUArraysCore
 
 # auxiliary types and functions
 include("OrderedIdDict.jl")
@@ -114,8 +117,7 @@ function set_default_backend(backend::XLA.Client)
 end
 
 function set_default_backend(backend::String)
-    backend = XLA.backends[backend]
-    return XLA.default_backend[] = backend
+    return set_default_backend(XLA.backends[backend])
 end
 
 end # module

src/TracedRArray.jl

@@ -59,13 +59,7 @@ end
 function Base.getindex(
     a::TracedRArray{T,N}, index::Vararg{Union{Int,TracedRNumber{Int}},N}
 ) where {T,N}
-    @warn(
-        """Performing scalar indexing on task $(current_task()).
-Invocation resulted in scalar indexing of a TracedRArray.
-This is typically caused by calling an iterating implementation of a method.
-Such implementations *do not* execute on device, but very slowly on the CPU,
-and require expensive copies and synchronization each time and therefore should be avoided."""
-    )
+    GPUArraysCore.assertscalar("getindex(::TracedRArray, ::Vararg{Int, N})")
 
     start_indices = [promote_to(TracedRNumber{Int}, i - 1).mlir_data for i in index]
     slice_sizes = [Int64(1) for _ in index]

src/XLA.jl

@@ -130,6 +130,7 @@ function __init__()
             end
         end
     end
+
     return nothing
 end
 

test/basic.jl

@@ -3,8 +3,6 @@ using Test
 using Enzyme
 using Statistics
 
-# Reactant.set_default_backend("gpu")
-
 fastmax(x::AbstractArray{T}) where {T} = reduce(max, x; dims=1, init=float(T)(-Inf))
 
 using InteractiveUtils
@@ -16,7 +14,7 @@ using InteractiveUtils
 
     a = Reactant.ConcreteRArray(x)
 
-    c_res = sum(a)
+    c_res = @allowscalar sum(a)
     @test c_res ≈ r_res
 
     @test @jit(sum(a)) ≈ r_res
@@ -29,7 +27,7 @@ end
 
     a = Reactant.ConcreteRArray(x)
 
-    c_res = fastmax(a)
+    c_res = @allowscalar fastmax(a)
     @test c_res ≈ r_res
 
     @test @jit(fastmax(a)) ≈ r_res
@@ -45,7 +43,7 @@ sinexpbc(x) = sinexp.(x)
 
     a = Reactant.ConcreteRArray(x)
 
-    c_res = sinexpbc(a)
+    c_res = @allowscalar sinexpbc(a)
     @test c_res ≈ r_res
 
     @test @jit(sinexpbc(a)) ≈ r_res
@@ -427,10 +425,10 @@ end
     @test y ≈ y_ra
 
     x_ra_array = Array(x_ra)
-    @test all(iszero, x_ra_array[1, :])
-    @test all(iszero, x_ra_array[2, :])
-    @test all(isone, x_ra_array[3, :])
-    @test all(isone, x_ra_array[4, :])
+    @test @allowscalar all(iszero, x_ra_array[1, :])
+    @test @allowscalar all(iszero, x_ra_array[2, :])
+    @test @allowscalar all(isone, x_ra_array[3, :])
+    @test @allowscalar all(isone, x_ra_array[4, :])
 end
 
 tuple_byref(x) = (; a=(; b=x))
@@ -504,14 +502,14 @@ end
 
         f2 = @compile f1(x_ra)
         res2 = f2(Reactant.to_rarray((5, [3.14]); track_numbers=(Number,)))
-        @test only(res2) ≈ 5 * 3.14
+        @test @allowscalar(only(res2)) ≈ 5 * 3.14
         @test res2 isa ConcreteRArray
 
         x_ra = Reactant.to_rarray(x)
 
         f3 = @compile f1(x_ra)
         res3 = f3(Reactant.to_rarray((5, [3.14])))
-        @test only(res3) ≈ only(f1(x))
+        @test @allowscalar(only(res3)) ≈ only(f1(x))
         @test res3 isa ConcreteRArray
     end
 end
@@ -544,18 +542,22 @@ end
     x_ra = Reactant.to_rarray(x)
 
     y = @jit(clamp!(x_ra, 0.0, 0.25))
-    @test maximum(y) ≤ 0.25
-    @test minimum(y) ≥ 0.0
-    @test maximum(x_ra) == maximum(y)
-    @test minimum(x_ra) == minimum(y)
+    @allowscalar begin
+        @test maximum(y) ≤ 0.25
+        @test minimum(y) ≥ 0.0
+        @test maximum(x_ra) == maximum(y)
+        @test minimum(x_ra) == minimum(y)
+    end
 
     x = randn(2, 3)
     x_ra = Reactant.to_rarray(x)
 
     y = @jit(clamp.(x_ra, 0.0, 0.25))
-    @test maximum(y) ≤ 0.25
-    @test minimum(y) ≥ 0.0
-    @test x_ra ≈ x
+    @allowscalar begin
+        @test maximum(y) ≤ 0.25
+        @test minimum(y) ≥ 0.0
+        @test x_ra ≈ x
+    end
 end
 
 @testset "dynamic indexing" begin
@@ -565,6 +567,8 @@ end
     idx = [1, 2, 3]
     idx_ra = Reactant.to_rarray(idx)
 
-    y = @jit(getindex(x_ra, idx_ra, :))
+    fn(x, idx) = @allowscalar x[idx, :]
+
+    y = @jit(fn(x_ra, idx_ra))
     @test y ≈ x[idx, :]
 end

test/closure.jl

@@ -4,9 +4,11 @@ using Reactant
 muler(x) = y -> x * y
 
 @testset "closure" begin
-    x = Reactant.ConcreteRArray(ones(2, 2))
-    y = Reactant.ConcreteRArray(ones(2, 2))
+    x = ones(2, 2)
+    y = ones(2, 2)
+    x_ra = Reactant.ConcreteRArray(x)
+    y_ra = Reactant.ConcreteRArray(y)
 
-    f = muler(x)
-    @test @jit(f(y)) ≈ x * y
+    f = muler(x_ra)
+    @test @jit(f(y_ra)) ≈ x * y
 end

test/compile.jl

@@ -16,22 +16,25 @@ Base.sum(x::NamedTuple{(:a,),Tuple{T}}) where {T<:Reactant.TracedRArray} = (; a=
     end
 
     @testset "world-age" begin
-        a = Reactant.ConcreteRArray(ones(2, 10))
-        b = Reactant.ConcreteRArray(ones(10, 2))
+        a = ones(2, 10)
+        b = ones(10, 2)
+        a_ra = Reactant.ConcreteRArray(a)
+        b_ra = Reactant.ConcreteRArray(b)
 
-        fworld(x, y) = @jit(*(x, y))
+        fworld(x, y) = @jit(x * y)
 
-        @test fworld(a, b) ≈ ones(2, 2) * 10
+        @test fworld(a_ra, b_ra) ≈ ones(2, 2) * 10
     end
 
     @testset "type casting & optimized out returns" begin
-        a = Reactant.ConcreteRArray(rand(2, 10))
+        a = ones(2, 10)
+        a_ra = Reactant.ConcreteRArray(a)
 
         ftype1(x) = Float64.(x)
         ftype2(x) = Float32.(x)
 
-        y1 = @jit ftype1(a)
-        y2 = @jit ftype2(a)
+        y1 = @jit ftype1(a_ra)
+        y2 = @jit ftype2(a_ra)
 
         @test y1 isa Reactant.ConcreteRArray{Float64,2}
         @test y2 isa Reactant.ConcreteRArray{Float32,2}

test/complex.jl

@@ -99,6 +99,7 @@ end
 end
 
 @testset "complex reduction" begin
-    x_ra = Reactant.ConcreteRArray(randn(ComplexF32, 10, 10))
-    @test @jit(sum(abs2, x_ra)) ≈ sum(abs2, x_ra)
+    x = randn(ComplexF32, 10, 10)
+    x_ra = Reactant.ConcreteRArray(x)
+    @test @jit(sum(abs2, x_ra)) ≈ sum(abs2, x)
 end

test/control_flow.jl

@@ -365,20 +365,20 @@ end
     x_ra = Reactant.to_rarray(x)
 
     res_ra = @jit(condition10_condition_with_setindex(x_ra))
-    @test res_ra[1, 1] == -1.0
-    @test res_ra[2, 1] == -1.0
-    @test x_ra[1, 1] == -1.0 broken = true
-    @test x_ra[2, 1] == -1.0 broken = true
+    @test @allowscalar(res_ra[1, 1]) == -1.0
+    @test @allowscalar(res_ra[2, 1]) == -1.0
+    @test @allowscalar(x_ra[1, 1]) == -1.0 broken = true
+    @test @allowscalar(x_ra[2, 1]) == -1.0 broken = true
 
     x = -rand(2, 10)
     x[2, 1] = 0.0
     x_ra = Reactant.to_rarray(x)
 
     res_ra = @jit(condition10_condition_with_setindex(x_ra))
-    @test res_ra[1, 1] == 1.0
-    @test res_ra[2, 1] == 0.0
-    @test x_ra[1, 1] == 1.0 broken = true
-    @test x_ra[2, 1] == 0.0
+    @test @allowscalar(res_ra[1, 1]) == 1.0
+    @test @allowscalar(res_ra[2, 1]) == 0.0
+    @test @allowscalar(x_ra[1, 1]) == 1.0 broken = true
+    @test @allowscalar(x_ra[2, 1]) == 0.0
 end
 
 function condition11_nested_ifff(x, y, z)
@@ -538,7 +538,7 @@ end
 function cumsum!(x)
     v = zero(eltype(x))
     @trace for i in 1:length(x)
-        v += x[i]
+        v += @allowscalar x[i]
         x[i] = v
     end
     return x

test/layout.jl

@@ -12,8 +12,10 @@ using Test
 
     # @show [y[1,1], y[1,2], y[2, 1], y[2, 2]]
 
-    @test y[1, 1] == x[1, 1]
-    @test y[1, 2] == x[1, 2]
-    @test y[2, 1] == x[2, 1]
-    @test y[2, 2] == x[2, 2]
+    @allowscalar begin
+        @test y[1, 1] == x[1, 1]
+        @test y[1, 2] == x[1, 2]
+        @test y[2, 1] == x[2, 1]
+        @test y[2, 2] == x[2, 2]
+    end
 end