using OneHotArrays (#2025)

* using OneHotArrays

* rm tests

* skip a test

* don't export, add depwarns

* back to using

Author: mcabbott

Project.toml

@@ -13,6 +13,7 @@ MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 NNlibCUDA = "a00861dc-f156-4864-bf3c-e6376f28a68d"
+OneHotArrays = "0b1bfda6-eb8a-41d2-88d8-f5af5cad476f"
 Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 ProgressLogging = "33c8b6b6-d38a-422a-b730-caa89a2f386c"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
@@ -34,6 +35,7 @@ MLUtils = "0.2"
 MacroTools = "0.5"
 NNlib = "0.8.9"
 NNlibCUDA = "0.2.4"
+OneHotArrays = "0.1"
 Optimisers = "0.2.1"
 ProgressLogging = "0.1"
 Reexport = "0.2, 1.0"

src/Flux.jl

@@ -37,8 +37,8 @@ export Descent, Adam, Momentum, Nesterov, RMSProp,
 using CUDA
 const use_cuda = Ref{Union{Nothing,Bool}}(nothing)
 
+using Adapt, Functors, OneHotArrays
 include("utils.jl")
-include("onehot.jl")
 include("functor.jl")
 
 # Pirate error to catch a common mistake.

src/onehot.jl

@@ -49,9 +49,11 @@ end
   # construct from CuArray
   x = [1, 3, 2]
   y = Flux.onehotbatch(x, 0:3)
+  @test_skip begin  # https://github.com/FluxML/OneHotArrays.jl/issues/16
   y2 = Flux.onehotbatch(x |> gpu, 0:3)
   @test y2.indices isa CuArray
   @test y2 |> cpu == y
+  end
 end
 
 @testset "onecold gpu" begin