cleanup

src/deprecations.jl

@@ -116,19 +116,6 @@ function Optimisers.update!(opt::Optimisers.AbstractRule, model::Chain, grad::Tu
 end
 
 
-macro functor(ex)
-  Base.depwarn("""The macro `Flux.@functor` is deprecated.
-      Most likely, you should write `Flux.@layer MyLayer` which will add 
-      various convenience methods for your type, such as pretty-printing, and use with Adapt.jl.
-      However, this is not strictly required: Flux.jl v0.15 uses Functors.jl v0.5, 
-      which makes exploration of most nested `struct`s opt-out instead of opt-in... 
-      so Flux will automatically see inside any custom struct definitions to take care of things
-      like moving data to the GPU.
-      """, Symbol("@functor"))
-
-  return :(Functors.functor($(esc(expr))))
-end
-
 ### v0.16 deprecations ####################
 
 

src/functor.jl

@@ -79,7 +79,7 @@ end
     cpu(m)
 
 Copies `m` onto the CPU, the opposite of [`gpu`](@ref).
-Recurses into structs marked [`@functor`](@ref).
+Recurses into structs (thanks to Functors.jl).
 
 # Example
 ```julia-repl
@@ -119,16 +119,14 @@ end
 
 Copies `m` to the current GPU device (using current GPU backend), if one is available.
 If no GPU is available, it does nothing (but prints a warning the first time).
-
-On arrays, this calls CUDA's `cu`, which also changes arrays
-with Float64 elements to Float32 while copying them to the device (same for AMDGPU).
-To act on arrays within a struct, the struct type must be marked with [`@functor`](@ref).
+It recurses into structs according to Functors.jl.
 
 Use [`cpu`](@ref) to copy back to ordinary `Array`s.
 See also [`f32`](@ref) and [`f16`](@ref) to change element type only.
 
-See the [CUDA.jl docs](https://juliagpu.github.io/CUDA.jl/stable/usage/multigpu/) 
-to help identify the current device.
+This function is just defined for convenience around [`gpu_device`](@ref), 
+and is equivalent to `gpu_device()(m)`.
+You may consider defining `device = gpu_device()` once and then using `device(m)` to move data.
 
 # Example
 ```julia-repl
@@ -147,10 +145,6 @@ CUDA.CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}
 """
 gpu(x) = gpu_device()(x)
 
-# TODO remove after https://github.com/LuxDL/Lux.jl/pull/1089
-ChainRulesCore.@non_differentiable gpu_device()
-ChainRulesCore.@non_differentiable gpu_device(::Any)
-
 # Precision
 
 struct FluxEltypeAdaptor{T} end