rename to _project_grad and fix tests

src/compiler/interface.jl

@@ -114,12 +114,14 @@ sensitivity(y::AbstractArray) = error("Output is an array, so the gradient is no
 sensitivity(y) = error("Output should be scalar; gradients are not defined for output $(repr(y))")
 
 # Preserves output as tuple when gradients are collapsed
-_project_sentinel(::NTuple{N}, ::Nothing) where {N} = ntuple(_ -> nothing, N)
-_project_sentinel(x::Tuple, dx::Tuple) = map(_project_sentinel, x, dx)
-_project_sentinel(::Any, ::NoTangent) = nothing
-_project_sentinel(::Any, ::ZeroTangent) = nothing
-_project_sentinel(::Any, ::Nothing) = nothing
-_project_sentinel(::Any, dx::Any) = dx
+_project_grad(::NTuple{N}, ::Nothing) where {N} = ntuple(_ -> nothing, N)
+_project_grad(x::Tuple, dx::Tuple) = map(_project_grad, x, dx)
+_project_grad(::Any, ::NoTangent) = nothing
+_project_grad(::Any, ::ZeroTangent) = nothing
+_project_grad(::Any, ::Nothing) = nothing
+_project_grad(::Any, dx::Any) = dx
+_project_grad(x::AbstractArray, dx::Tuple) = _project(x, dx)
+_project_grad(x::Any, dx::Base.RefValue) = _project(x, dx)
 
 """
     gradient(f, args...)
@@ -150,7 +152,7 @@ julia> gradient([7, 11], 0, 1) do x, y, d
 function gradient(f, args...)
   y, back = pullback(f, args...)
   grad = back(sensitivity(y))
-  return _project_sentinel(args, grad)
+  return _project_grad(args, grad)
 end
 
 # Base.adjoint(f::Function) = x -> gradient(f, x)[1]  # piracy!
@@ -216,7 +218,7 @@ function withgradient(f, args...)
   else
     back(sensitivity(y))
   end
-  results = _project_sentinel(args, grad)
+  results = _project_grad(args, grad)
   (val=y, grad=results)
 end
 
@@ -477,7 +479,7 @@ function pullback(f, ps::Params)
 end
 
 # No conversion required here
-_project_sentinel(_, dx::Grads) = dx
+_project_grad(_, dx::Grads) = dx
 
 # Code Reflection