From 1686f1250835702a764cebf80ffccc8773b3c8bd Mon Sep 17 00:00:00 2001
From: Michael Abbott <32575566+mcabbott@users.noreply.github.com>
Date: Sun, 24 Jul 2022 22:27:42 -0400
Subject: [PATCH 1/2] add AbstractArray construction methods

---
 src/onehot.jl | 28 ++++++++++++++++++++++------
 1 file changed, 22 insertions(+), 6 deletions(-)

diff --git a/src/onehot.jl b/src/onehot.jl
index 6231f3c..a2d75dd 100644
--- a/src/onehot.jl
+++ b/src/onehot.jl
@@ -83,20 +83,36 @@ julia> reshape(1:15, 3, 5) * oh  # this matrix multiplication is done efficientl
 """
 onehotbatch(data, labels, default...) = _onehotbatch(data, length(labels) < 32 ? Tuple(labels) : labels, default...)
 
-function _onehotbatch(data, labels)
-  indices = UInt32[something(_findval(i, labels), 0) for i in data]
-  if 0 in indices
+function _onehotbatch(data, labels)  # this accepts any iterator
+  indices = UInt32[something(_findval(x, labels), 0) for x in data]
+  if any(iszero, indices)
     for x in data
-      isnothing(_findval(x, labels)) && error("Value $x not found in labels")
+      isnothing(_findval(x, labels)) && throw(ArgumentError("Value x = $x not found in labels = $labels"))
     end
   end
   return OneHotArray(indices, length(labels))
 end
+function _onehotbatch(data::AbstractArray, labels)  # this works for GPUArrays too
+  indices = similar(data, UInt32)
+  map!(x -> something(_findval(x, labels), 0), indices, data)
+  if any(iszero, indices)
+    badx = @allowscalar data[findfirst(iszero, indices)]
+    throw(ArgumentError("Value x = $badx not found in labels = $labels"))
+  end
+  return OneHotArray(indices, length(labels))
+end
 
 function _onehotbatch(data, labels, default)
   default_index = _findval(default, labels)
-  isnothing(default_index) && error("Default value $default is not in labels")
-  indices = UInt32[something(_findval(i, labels), default_index) for i in data]
+  isnothing(default_index) && throw(ArgumentError("Default value $default is not in labels = $labels"))
+  indices = UInt32[something(_findval(x, labels), default_index) for x in data]
+  return OneHotArray(indices, length(labels))
+end
+function _onehotbatch(data::AbstractArray, labels, default)
+  default_index = _findval(default, labels)
+  isnothing(default_index) && throw(ArgumentError("Default value $default is not in labels = $labels"))
+  indices = similar(data, UInt32)
+  map!(x -> something(_findval(x, labels), default_index), indices, data)
   return OneHotArray(indices, length(labels))
 end
 

From f05824432ef4c807ee45645b4dc54842df1d810f Mon Sep 17 00:00:00 2001
From: Michael Abbott <32575566+mcabbott@users.noreply.github.com>
Date: Sun, 24 Jul 2022 22:27:50 -0400
Subject: [PATCH 2/2] tests

---
 test/gpu.jl | 49 +++++++++++++++++++++++++++----------------------
 1 file changed, 27 insertions(+), 22 deletions(-)

diff --git a/test/gpu.jl b/test/gpu.jl
index 13c208c..1cb508a 100644
--- a/test/gpu.jl
+++ b/test/gpu.jl
@@ -1,29 +1,23 @@
 
-# Tests from Flux, probably not the optimal testset organisation!
-
-@testset "CUDA" begin
-  x = randn(5, 5)
-  cx = cu(x)
-  @test cx isa CuArray
-
-  @test_skip onecold(cu([1.0, 2.0, 3.0])) == 3  # passes with CuArray with Julia 1.6, but fails with JLArray
-
-  x = onehotbatch([1, 2, 3], 1:3)
-  cx = cu(x)
-  @test cx isa OneHotMatrix && cx.indices isa CuArray
-  @test (cx .+ 1) isa CuArray
-
+@testset "onehotbatch gpu" begin
+  # move to GPU after construction
+  x = onehotbatch([1, 2, 3, 2], 1:3)
+  @test cu(x) isa OneHotMatrix
+  @test cu(x).indices isa CuArray
+  
+  # broadcast style works:
+  @test (cu(x) .+ 1) isa CuArray
   xs = rand(5, 5)
-  ys = onehotbatch(1:5,1:5)
+  ys = onehotbatch(rand(1:5, 5), 1:5)
   @test collect(cu(xs) .+ cu(ys)) ≈ collect(xs .+ ys)
-end
 
-@testset "onehot gpu" begin
-  y = onehotbatch(ones(3), 1:2) |> cu;
-  @test (repr("text/plain", y); true)
-
-  gA = rand(3, 2) |> cu;
-  @test_broken gradient(A -> sum(A * y), gA)[1] isa CuArray  # fails with JLArray, bug in Zygote?
+  # move to GPU before construction
+  z1 = onehotbatch(cu([3f0, 1f0, 2f0, 2f0]), (1.0, 2f0, 3))
+  @test z1.indices isa CuArray
+  z2 = onehotbatch(cu([3f0, 1f0, 2f0, 2f0]), [1, 2], 2)  # with default
+  @test z2.indices isa CuArray
+  @test_throws ArgumentError onehotbatch(cu([1, 2, 3]), [1, 2])  # friendly error, not scalar indexing
+  @test_throws ArgumentError onehotbatch(cu([1, 2, 3]), [1, 2], 5)
 end
 
 @testset "onecold gpu" begin
@@ -32,6 +26,17 @@ end
   @test onecold(y) isa CuArray
   @test y[3,:] isa CuArray
   @test onecold(y, l) == ['a', 'a', 'a']
+
+  @test_skip onecold(cu([1.0, 2.0, 3.0])) == 3  # passes with CuArray with Julia 1.6, but fails with JLArray
+end
+
+@testset "matrix multiplication gpu" begin
+  y = onehotbatch([1, 2, 1], [1, 2]) |> cu;
+  A = rand(3, 2) |> cu;
+  
+  @test_broken collect(A * y) ≈ collect(A) * collect(y)
+  
+  @test_broken gradient(A -> sum(abs, A * y), A)[1] isa CuArray  # gather!(dst::JLArray, ...) fails
 end
 
 @testset "onehot forward map to broadcast" begin