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Improve performance of sum of products with nonlinear expressions #3470

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Improve performance of sum of products with nonlinear expressions #3470

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28 changes: 4 additions & 24 deletions src/mutable_arithmetics.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -286,12 +286,7 @@ end
function _MA.add_mul(lhs::AbstractJuMPScalar, x::_Scalar, y::_Scalar)
T = _MA.promote_operation(_MA.add_mul, typeof(lhs), typeof(x), typeof(y))
expr = _MA.operate(convert, T, lhs)
# We can't use `operate!!` here because in the IsNotMutable case (e.g.,
# NonlinearExpr), it will fallback to this method and cause a StackOverflow.
if _MA.mutability(T) == _MA.IsNotMutable()
return expr + _MA.operate(*, x, y)
end
return _MA.operate!(_MA.add_mul, expr, x, y)
return _MA.operate!!(_MA.add_mul, expr, x, y)
end

function _MA.add_mul(
Expand All @@ -308,23 +303,13 @@ function _MA.add_mul(
typeof.(args)...,
)
expr = _MA.operate(convert, T, lhs)
# We can't use `operate!!` here because in the IsNotMutable case (e.g.,
# NonlinearExpr), it will fallback to this method and cause a StackOverflow.
if _MA.mutability(T) == _MA.IsNotMutable()
return expr + _MA.operate(*, x, y, args...)
end
return _MA.operate!(_MA.add_mul, expr, x, y, args...)
return _MA.operate!!(_MA.add_mul, expr, x, y, args...)
end

function _MA.sub_mul(lhs::AbstractJuMPScalar, x::_Scalar, y::_Scalar)
T = _MA.promote_operation(_MA.sub_mul, typeof(lhs), typeof(x), typeof(y))
expr = _MA.operate(convert, T, lhs)
# We can't use `operate!!` here because in the IsNotMutable case (e.g.,
# NonlinearExpr), it will fallback to this method and cause a StackOverflow.
if _MA.mutability(T) == _MA.IsNotMutable()
return expr - _MA.operate(*, x, y)
end
return _MA.operate!(_MA.sub_mul, expr, x, y)
return _MA.operate!!(_MA.sub_mul, expr, x, y)
end

function _MA.sub_mul(
Expand All @@ -341,10 +326,5 @@ function _MA.sub_mul(
typeof.(args)...,
)
expr = _MA.operate(convert, T, lhs)
# We can't use `operate!!` here because in the IsNotMutable case (e.g.,
# NonlinearExpr), it will fallback to this method and cause a StackOverflow.
if _MA.mutability(T) == _MA.IsNotMutable()
return expr - _MA.operate(*, x, y, args...)
end
return _MA.operate!(_MA.sub_mul, expr, x, y, args...)
return _MA.operate!!(_MA.sub_mul, expr, x, y, args...)
end
14 changes: 9 additions & 5 deletions src/nlp_expr.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -368,16 +368,20 @@ for f in (:+, :-, :*, :^, :/, :atan)
end

function _MA.operate!!(
::typeof(_MA.add_mul),
op::_MA.AddSubMul,
x::GenericNonlinearExpr,
y::AbstractJuMPScalar,
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I don't remember why I only wrote the binary case 😆

)
args::Vararg{Any,N},
) where {N}
_throw_if_not_real(x)
if x.head == :+
push!(x.args, y)
arg = *(args...)
if _MA.add_sub_op(op) != +
arg = _MA.add_sub_op(op)(arg)
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I really think we should avoid this. If the user writes x + y - 2 * z, we should make -(+(x, y), *(2, z)), not `+(x, y, -(*(2, z))).

Julia has a parsing precedence order. Let's follow that where possible.

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I thought flatten! was doing that anyway

end
push!(x.args, arg)
return x
end
return +(x, y)
return _MA.add_sub_op(op)(x, *(args...))
end

"""
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