minor test fixes

NEWS.md

@@ -1,5 +1,34 @@
+Knet v1.4.10 Release Notes
+=========================
+
+* switch default GPU array type from KnetArray to CuArray
+* allow loading on Apple M1
+* support SpecialFunctions 2.x
+* fix674: libknet8 compile error on unknown architectures
+* tutorial updates
+* minor test fixes
+
+
+Knet v1.4.9 Release Notes
+=========================
+4720782 2021-10-13
+
+* progress on layers21
+* added vae chapter to docs
+* updated libknet8 for windows
+* made tutorial colab compatible
+
+
+Knet v1.4.8 Release Notes
+=========================
+13fea96 2021-08-08
+
+* fixed libknet8 path
+
+
 Knet v1.4.7 Release Notes
 =========================
+d4af838 2021-07-23
 
 * Compatibility fixes for Julia 1.6/1.7 and CUDA 3.x.
 * Starting ops21, layers21, models21.

Project.toml

@@ -1,7 +1,7 @@
 name = "Knet"
 uuid = "1902f260-5fb4-5aff-8c31-6271790ab950"
 authors = ["Deniz Yuret <[email protected]>"]
-version = "1.4.9"
+version = "1.4.10"
 
 [deps]
 AutoGrad = "6710c13c-97f1-543f-91c5-74e8f7d95b35"
@@ -27,8 +27,8 @@ FileIO = "1.0"
 ImageCore = "0.7, 0.8, 0.9"
 ImageMagick = "1.0"
 JLD2 = "0.1, 0.2, 0.3, 0.4"
-NNlib = "0.6, 0.7"
-SpecialFunctions = "0.8, 0.9, 0.10, 1.0, 2"
+NNlib = "0.6, 0.7, 0.8"
+SpecialFunctions = "0.8, 0.9, 0.10, 1.0, 2.0"
 julia = "1.0"
 
 [extras]

test/karray.jl

@@ -33,10 +33,10 @@ if CUDA.functional()
  ([1,3],:), (:,[1,3]), # Vector{Int},Colon
  ([2,2],:), (:,[2,2]), # Repeated index
  # ([],), # Empty Array: fails with CuArray
- ((a.>0.5),),  # BitArray
+ (trues(size(a)),), # BitArray: may fail when using (a.>0.5) as index if all false.
  ([1 3; 2 4],), # Array{Int}
  (CartesianIndex(3,),), (CartesianIndex(2,3),), # CartesianIndex
- (:,a[1,:].>0.5),(a[:,1].>0.5,:), # BitArray2 # FAIL for julia4
+ (:,trues(size(a[1,:]))),(trues(size(a[:,1])),:), # BitArray2 # FAIL for julia4
  ([CartesianIndex(2,2), CartesianIndex(2,1)],), # Array{CartesianIndex} # FAIL for julia4
  )
  #@show i
@@ -144,7 +144,7 @@ if CUDA.functional()
  (:,:,2), # Colon, Colon, Int
  (:,:,1:2), # Colon, Colon, UnitRange
  # ([],), # Empty Array fails with CuArray
- ((a.>0.5),),  # BitArray
+ (trues(size(a)),), # BitArray
  )
  #@show i
  k = KnetArray(a)

test/kptr.jl

@@ -42,11 +42,9 @@ end
 # Test the cuda allocator.
 if CUDA.functional()
  cuallocator[]=true
- cxt = CUDA.context()
- usedmem() = CUDA.usage(cxt)[] - CUDA.cached_memory()
- used = usedmem()
+ used = CUDA.used_memory()
  @testset "kptr:cuda" begin
- @test (p = KnetPtr(128); usedmem() == used + 128)
+ @test (p = KnetPtr(128); CUDA.used_memory() == used + 128)
  p = nothing
  end
 end
@@ -55,7 +53,7 @@ GC.gc(true)
 
 if CUDA.functional()
  @testset "kptr:cudagc" begin
- @test usedmem() == used
+ @test CUDA.used_memory() == used
  end
 end
 

test/serialize.jl

@@ -1,7 +1,7 @@
 using Test, Random, FileIO, JLD2
 using Knet.KnetArrays: KnetArray, Cptr, jld2serialize, cpucopy, gpucopy
 using Knet.Ops20: RNN, conv4
-using CUDA: CUDA, functional
+using CUDA: CUDA, functional, @allowscalar
 using AutoGrad: Param, params, @diff, value
 
 struct M370; layer; end;
@@ -10,12 +10,12 @@ struct M370; layer; end;
  M1 = RNN(2,3)
  M2 = M1 |> cpucopy
  @test typeof(M2.w.value) <: Array
- @test M2.w.value == M1.w.value
+ @test @allowscalar M2.w.value == M1.w.value
  @test Array{Float32} == jld2serialize(Array{Float32})
  if CUDA.functional()
  M3 = M2 |> gpucopy
  @test typeof(M3.w.value) <: KnetArray
- @test M3.w.value == M2.w.value
+ @test @allowscalar M3.w.value == M2.w.value
  array_of_ka = map(value,params(M3))
  array_of_ca = array_of_ka |> cpucopy
  @test first(array_of_ca) isa Array