Merge pull request #24930 from JuliaLang/sk/revert-24500

Revert "improvements to accuracy/performance for float^integer (#24500)"
JuliaLang · Dec 5, 2017 · 11d5a53 · 11d5a53 · nanosoldier · Dec 6, 2017
2 parents d78bed1 + 482aafe
commit 11d5a53
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Showing 3 changed files with 3 additions and 18 deletions.
diff --git a/base/intfuncs.jl b/base/intfuncs.jl
@@ -234,12 +234,6 @@ const HWNumber = Union{HWReal, Complex{<:HWReal}, Rational{<:HWReal}}
 @inline literal_pow(::typeof(^), x::HWNumber, ::Val{2}) = x*x
 @inline literal_pow(::typeof(^), x::HWNumber, ::Val{3}) = x*x*x
 
-# don't use the inv(x) transformation here since float^p is slightly more accurate
-@inline literal_pow(::typeof(^), x::AbstractFloat, ::Val{p}) where {p} = x^p
-@inline literal_pow(::typeof(^), x::AbstractFloat, ::Val{-1}) = inv(x)
-
-# for other types, define x^-n as inv(x)^n so that negative literal powers can
-# be computed in a type-stable way even for e.g. integers.
 @inline @generated function literal_pow(f::typeof(^), x, ::Val{p}) where {p}
     if p < 0
         :(literal_pow(^, inv(x), $(Val{-p}())))

diff --git a/base/math.jl b/base/math.jl
@@ -732,9 +732,9 @@ end
     end
     z
 end
-@inline ^(x::Float64, y::Integer) = ccall("llvm.pow.f64", llvmcall, Float64, (Float64, Float64), x, Float64(y))
-@inline ^(x::Float32, y::Integer) = ccall("llvm.pow.f32", llvmcall, Float32, (Float32, Float32), x, Float32(y))
-@inline ^(x::Float16, y::Integer) = Float16(Float32(x) ^ y)
+@inline ^(x::Float64, y::Integer) = x ^ Float64(y)
+@inline ^(x::Float32, y::Integer) = x ^ Float32(y)
+@inline ^(x::Float16, y::Integer) = Float16(Float32(x) ^ Float32(y))
 @inline literal_pow(::typeof(^), x::Float16, ::Val{p}) where {p} = Float16(literal_pow(^,Float32(x),Val(p)))
 
 function angle_restrict_symm(theta)

diff --git a/test/numbers.jl b/test/numbers.jl
@@ -2965,15 +2965,6 @@ module M20889 # do we get the expected behavior without importing Base.^?
     Test.@test PR20889(2)^3 == 5
 end
 
-@testset "literal negative power accuracy" begin
-    # a few cases chosen to maximize the error for inv(x)^+n:
-    @test 0.7130409001548401^-2 === 1.9668494399322154
-    @test 0.09496527f0^-2 === 110.88438f0
-    @test 0.20675883960662367^-100 === 2.841786121808917e68
-    @test 0.6123676f0^-100 === 1.9896729f21
-    @test 0.004155780785470562^-1 === 240.6286692253353
-end
-
 @testset "iszero & isone" begin
     # Numeric scalars
     for T in [Float16, Float32, Float64, BigFloat,