move setweights and copy_transpose

Manifest.toml

@@ -106,7 +106,7 @@ version = "4.0.0"
 
 [[CuArrays]]
 deps = ["AbstractFFTs", "Adapt", "CEnum", "CUDAapi", "CUDAdrv", "CUDAnative", "GPUArrays", "LinearAlgebra", "MacroTools", "NNlib", "Printf", "Random", "Requires", "SparseArrays", "TimerOutputs"]
-git-tree-sha1 = "155349d2c40568a23cbc4599f0e17e2fdf1bbbcc"
+git-tree-sha1 = "63b4a10d3a4f22ef215d0970483b18296717d1fb"
 repo-rev = "tb/flux"
 repo-url = "https://github.com/JuliaGPU/CuArrays.jl.git"
 uuid = "3a865a2d-5b23-5a0f-bc46-62713ec82fae"

Project.toml

@@ -11,7 +11,6 @@ Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
 CuArrays = "3a865a2d-5b23-5a0f-bc46-62713ec82fae"
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
 Juno = "e5e0dc1b-0480-54bc-9374-aad01c23163d"
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"

src/cuda/curnn.jl

@@ -1,32 +1,12 @@
 import ..Flux: Flux, relu
 using CuArrays.CUDAnative
 using CuArrays: @cuindex, cudims
-using LinearAlgebra
-
-function LinearAlgebra.copy_transpose!(dst::CuArray, src::CuArray)
-  function kernel(dst, src)
-    I = @cuindex dst
-    dst[I...] = src[reverse(I)...]
-    return
-  end
-  blk, thr = cudims(dst)
-  @cuda blocks=blk threads=thr kernel(dst, src)
-  return dst
-end
 
 CuRNN{T} = Flux.RNNCell{<:Union{typeof(tanh),typeof(relu)},<:CuArray{T,2},<:CuArray{T,1}}
 CuGRU{T} = Flux.GRUCell{<:CuArray{T,2},<:CuArray{T,1}}
 CuLSTM{T} = Flux.LSTMCell{<:CuArray{T,2},<:CuArray{T,1}}
 CuRNNs{T} = Union{CuRNN{T},CuGRU{T},CuLSTM{T}}
 
-function copyparams!(m::CuRNNs, d::CUDNN.RNNDesc)
-  Wi, Wh = d.weights
-  copy_transpose!(Wi, m.Wi)
-  copy_transpose!(Wh, m.Wh)
-  copy_transpose!(d.bias, m.b)
-  return
-end
-
 function CUDNN.RNNDesc(m::CuRNNs{T}) where T
   h, i = length(m.h), size(m.Wi, 2)
   mode = m isa CuRNN ?
@@ -40,7 +20,7 @@ const descs = WeakKeyDict()
 
 function desc(rnn)
   d = haskey(descs, rnn) ? descs[rnn] : (descs[rnn] = CUDNN.RNNDesc(rnn))
-  copyparams!(rnn, d)
+  CUDNN.setweights!(d, rnn.Wi, rnn.Wh, rnn.b)
   return d
 end
 

test/cuda/curnn.jl

@@ -22,8 +22,8 @@ end
       rand(10, batch_size)
     cux = gpu(x)
 
-    y, back = forward((r, x) -> (r(x)), rnn, x)
-    cuy, cuback = forward((r, x) -> (r(x)), curnn, cux)
+    y, back = forward((r, x) -> r(x), rnn, x)
+    cuy, cuback = forward((r, x) -> r(x), curnn, cux)
 
     @test y ≈ collect(cuy)
     @test haskey(Flux.CUDA.descs, curnn.cell)