Use logten and logtwo from IrrationalConstants (#555)

* Use `logten` and `logtwo` from IrrationalConstants

* Update Project.toml

* Update Project.toml

Author: devmotion

Project.toml

@@ -1,10 +1,11 @@
 name = "ChainRules"
 uuid = "082447d4-558c-5d27-93f4-14fc19e9eca2"
-version = "1.22" 
+version = "1.23"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
+IrrationalConstants = "92d709cd-6900-40b7-9082-c6be49f344b6"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RealDot = "c1ae055f-0cd5-4b69-90a6-9a35b1a98df9"
@@ -15,6 +16,7 @@ ChainRulesCore = "1.11.5"
 ChainRulesTestUtils = "1"
 Compat = "3.35"
 FiniteDifferences = "0.12.20"
+IrrationalConstants = "0.1.1"
 JuliaInterpreter = "0.8" # latest is "0.9.1"
 RealDot = "0.1"
 StaticArrays = "1.2"

src/ChainRules.jl

@@ -3,6 +3,7 @@ module ChainRules
 using Base.Broadcast: materialize, materialize!, broadcasted, Broadcasted, broadcastable
 using ChainRulesCore
 using Compat
+using IrrationalConstants: logtwo, logten
 using LinearAlgebra
 using LinearAlgebra.BLAS
 using Random

src/rulesets/Base/fastmath_able.jl

@@ -54,13 +54,13 @@ let
         @scalar_rule inv(x) -(Ω ^ 2)
         @scalar_rule sqrt(x) inv(2Ω)  # gradient +Inf at x==0
         @scalar_rule exp(x) Ω
-        @scalar_rule exp10(x) Ω * log(oftype(x, 10))
-        @scalar_rule exp2(x) Ω * log(oftype(x, 2))
+        @scalar_rule exp10(x) logten * Ω
+        @scalar_rule exp2(x) logtwo * Ω
         @scalar_rule expm1(x) exp(x)
         @scalar_rule log(x) inv(x)
-        @scalar_rule log10(x) inv(x) / log(oftype(x, 10))
+        @scalar_rule log10(x) inv(logten * x)
         @scalar_rule log1p(x) inv(x + 1)
-        @scalar_rule log2(x) inv(x) / log(oftype(x, 2))
+        @scalar_rule log2(x) inv(logtwo * x)
 
         # Unary complex functions
         ## abs