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fix: allow one arg of overloaded_mul to be a regular array #821

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Merged
avik-pal merged 1 commit into from
Feb 27, 2025
Merged

fix: allow one arg of overloaded_mul to be a regular array #821

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39 changes: 26 additions & 13 deletions src/stdlibs/LinearAlgebra.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -168,12 +168,13 @@ end
# Core functions
function overloaded_mul!(
@nospecialize(C::TracedRArray{T,1}),
@nospecialize(A::AnyTracedRMatrix),
@nospecialize(B::AnyTracedRVector),
@nospecialize(A::AbstractMatrix),
@nospecialize(B::AbstractVector),
α::Number=true,
β::Number=false,
) where {T}
# TODO: The reshape operations are not getting optimized, we should directly call dot_general
# TODO: The reshape operations are not getting optimized, we should directly call
# dot_general
rC = Ops.reshape(C, length(C), 1)
overloaded_mul!(rC, A, reshape(B, :, 1), α, β)
C.mlir_data = get_mlir_data(vec(rC))
Expand All @@ -182,8 +183,8 @@ end

function overloaded_mul!(
@nospecialize(C::TracedRArray{T,2}),
@nospecialize(A::AnyTracedRMatrix),
@nospecialize(B::AnyTracedRVector),
@nospecialize(A::AbstractMatrix),
@nospecialize(B::AbstractVector),
α::Number=true,
β::Number=false,
) where {T}
Expand All @@ -193,11 +194,14 @@ end

function overloaded_mul!(
@nospecialize(C::TracedRArray{T,2} where {T}),
@nospecialize(A::AnyTracedRMatrix),
@nospecialize(B::AnyTracedRMatrix),
@nospecialize(A::AbstractMatrix),
@nospecialize(B::AbstractMatrix),
α::Number=true,
β::Number=false,
)
A = TracedUtils.promote_to(TracedRArray{unwrapped_eltype(A),2}, A)
B = TracedUtils.promote_to(TracedRArray{unwrapped_eltype(B),2}, B)

if size(C) != (size(A, 1), size(B, 2))
throw(
DimensionMismatch(
Expand Down Expand Up @@ -399,24 +403,33 @@ end

function LinearAlgebra.axpy!(α::Number, x::TracedRArray{T}, y::TracedRArray{T}) where {T}
if length(x) != length(y)
throw(DimensionMismatch(lazy"x has length $(length(x)), but y has length $(length(y))"))
throw(
DimensionMismatch(
lazy"x has length $(length(x)), but y has length $(length(y))"
),
)
end
ax = Ops.multiply(x, TracedUtils.broadcast_to_size(T(α), size(x)))

set_mlir_data!(y, get_mlir_data(Ops.add(y, ax)))
return y
end

function LinearAlgebra.axpby!(α::Number, x::TracedRArray{T}, β::Number, y::TracedRArray{T}) where {T}
function LinearAlgebra.axpby!(
α::Number, x::TracedRArray{T}, β::Number, y::TracedRArray{T}
) where {T}
if length(x) != length(y)
throw(DimensionMismatch(lazy"x has length $(length(x)), but y has length $(length(y))"))
throw(
DimensionMismatch(
lazy"x has length $(length(x)), but y has length $(length(y))"
),
)
end
ax = Ops.multiply(x, TracedUtils.broadcast_to_size(T(α), size(x)))
by = Ops.multiply(y, TracedUtils.broadcast_to_size(T(β), size(y)))

set_mlir_data!(y, get_mlir_data(Ops.add(ax, by)))
return y
end


end
26 changes: 11 additions & 15 deletions test/integration/linear_algebra.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,7 @@ end
@test @jit(muladd2(A_ra, x_ra, b_ra)) ≈ muladd2(A, x, b)
@test @jit(muladd_5arg(A_ra, x_ra, b_ra)) ≈ muladd2(A, x, b)
@test @jit(muladd_5arg2(A_ra, x_ra, b_ra)) ≈ 2 .* A * x .+ b
@test @jit(A_ra * x) ≈ A * x

@test @jit(mul_with_view1(A_ra, x_ra)) ≈ mul_with_view1(A, x)

Expand Down Expand Up @@ -189,7 +190,7 @@ end
x = rand(Int64, 4)
x_ra = Reactant.to_rarray(x)
y = rand(Int64, 4)
y_ra = Reactant.to_rarray(y)
y_ra = Reactant.to_rarray(y)

@jit axpy!(α, x_ra, y_ra)
@test y_ra ≈ axpy!(α, x, y)
Expand All @@ -198,7 +199,7 @@ end
x = rand(4)
x_ra = Reactant.to_rarray(x)
y = rand(4)
y_ra = Reactant.to_rarray(y)
y_ra = Reactant.to_rarray(y)

@jit axpy!(α, x_ra, y_ra)
@test y_ra ≈ axpy!(α, x, y)
Expand All @@ -208,19 +209,18 @@ end
Y = rand(3, 5)
X_ra = Reactant.to_rarray(X)
Y_ra = Reactant.to_rarray(Y)

@jit axpy!(α, X_ra, Y_ra)
@test Y_ra ≈ axpy!(α, X, Y)

α = 3.2 + 1im
x = rand(Complex{Float32}, 4)
x_ra = Reactant.to_rarray(x)
y = rand(Complex{Float32}, 4)
y_ra = Reactant.to_rarray(y)
y_ra = Reactant.to_rarray(y)

@jit axpy!(α, x_ra, y_ra)
@test y_ra ≈ axpy!(α, x, y)

end

@testset "axpby!" begin
Expand All @@ -229,7 +229,7 @@ end
x = rand(Int64, 4)
x_ra = Reactant.to_rarray(x)
y = rand(Int64, 4)
y_ra = Reactant.to_rarray(y)
y_ra = Reactant.to_rarray(y)

@jit axpby!(α, x_ra, β, y_ra)
@test y_ra ≈ axpby!(α, x, β, y)
Expand All @@ -239,7 +239,7 @@ end
x = rand(4)
x_ra = Reactant.to_rarray(x)
y = rand(4)
y_ra = Reactant.to_rarray(y)
y_ra = Reactant.to_rarray(y)

@jit axpby!(α, x_ra, β, y_ra)
@test y_ra ≈ axpby!(α, x, β, y)
Expand All @@ -249,21 +249,17 @@ end
Y = rand(3, 5)
X_ra = Reactant.to_rarray(X)
Y_ra = Reactant.to_rarray(Y)

@jit axpby!(α, X_ra, β, Y_ra)
@test Y_ra ≈ axpby!(α, X, β, Y)

α = 3.2 + 1im
β = 2.1 - 4.2im
x = rand(Complex{Float32}, 4)
x_ra = Reactant.to_rarray(x)
y = rand(Complex{Float32}, 4)
y_ra = Reactant.to_rarray(y)
y_ra = Reactant.to_rarray(y)

@jit axpby!(α, x_ra, β, y_ra)
@test y_ra ≈ axpby!(α, x, β, y)

end



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