Type inference problem with binary operators on Julia master about forwarddiff.jl HOT 9 CLOSED

julia> @code_warntype *(Array(ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}}),1.0)
Variables:
  A::Array{ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},0}
  B::Float64

Body:
  begin  # abstractarraymath.jl, line 55:
      return A::Array{ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},0} .* B::Float64::Array{ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},0}
  end::Array{ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},0}

julia> @code_warntype /(Array(ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}}),1.0)
Variables:
  A::Array{ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},0}
  B::Float64

Body:
  begin  # abstractarraymath.jl, line 57:
      return A::Array{ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},0} ./ B::Float64::Array{ForwardDiff.GradientNumber{N,T,C},0}
  end::Array{ForwardDiff.GradientNumber{N,T,C},0}

      GenSym(4) = x::ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}} ./ y::Float64::ForwardDiff.GradientNumber{N,T,C}

julia> Base.return_types(*, (ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},Float64))
1-element Array{Any,1}:
 ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}}

julia> Base.return_types(*, (ForwardDiff.GradientNumber{2,Float64,Tuple{Float64,Float64}},Float64))
1-element Array{Any,1}:
 ForwardDiff.GradientNumber{N,T,C}

julia> versioninfo()
Julia Version 0.5.0-dev+3977
Commit 957f1d1 (2016-05-08 00:28 UTC)
Platform Info:
  System: Darwin (x86_64-apple-darwin15.4.0)
  CPU: Intel(R) Core(TM) i7-4980HQ CPU @ 2.80GHz
  WORD_SIZE: 64
  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)
  LAPACK: libopenblas64_
  LIBM: libopenlibm
  LLVM: libLLVM-3.7.1 (ORCJIT, haswell)