beginnings of gpu support

src/Flux.jl

@@ -4,11 +4,11 @@ module Flux
 
 # Zero Flux Given
 
-using Juno
+using Juno, Requires
 using Lazy: @forward
 
 export Chain, Dense, RNN, LSTM,
-  SGD, params
+  SGD, params, mapparams
 
 using NNlib
 export σ, relu, softmax

src/layers/basic.jl

@@ -56,7 +56,10 @@ Dense(in::Integer, out::Integer, σ = identity; init = initn) =
 
 treelike(Dense)
 
-(a::Dense)(x) = a.σ.(a.W*x .+ a.b)
+function (a::Dense)(x)
+  W, b, σ = a.W, a.b, a.σ
+  σ.(W*x .+ b)
+end
 
 function Base.show(io::IO, l::Dense)
   print(io, "Dense(", size(l.W, 2), ", ", size(l.W, 1))

src/onehot.jl

@@ -9,8 +9,8 @@ Base.getindex(xs::OneHotVector, i::Integer) = i == xs.ix
 
 Base.:*(A::AbstractMatrix, b::OneHotVector) = A[:, b.ix]
 
-struct OneHotMatrix <: AbstractMatrix{Bool}
+struct OneHotMatrix{A<:AbstractVector{OneHotVector}} <: AbstractMatrix{Bool}
-  data::Vector{OneHotVector}
+  data::A
 end
 
 Base.size(xs::OneHotMatrix) = (Int64(length(xs.data[1])),length(xs.data))
@@ -21,6 +21,10 @@ Base.:*(A::AbstractMatrix, B::OneHotMatrix) = A[:, map(x->x.ix, B.data)]
 
 Base.hcat(x::OneHotVector, xs::OneHotVector...) = OneHotMatrix([x, xs...])
 
+@require CuArrays begin
+  CuArrays.cu(xs::OneHotMatrix) = OneHotMatrix(CuArrays.cu(xs.data))
+end
+
 onehot(l, labels) = OneHotVector(findfirst(labels, l), length(labels))
 onehotbatch(ls, labels) = OneHotMatrix([onehot(l, labels) for l in ls])
 

src/tree.jl

@@ -8,13 +8,18 @@ function treelike(T, fs = fieldnames(T))
   end
 end
 
-using DataFlow: OSet
+# TODO: prewalk/postwalk with correct caching
+# This is only correct in general for idempotent functions
 
-params(ps, p::AbstractArray) = push!(ps, p)
+mapparams(f, x::AbstractArray) = f(x)
-params(ps, m) = foreach(m -> params(ps, m), children(m))
+mapparams(f, x) = mapchildren(x -> mapparams(f, x), x)
+
+forparams(f, x) = (mapparams(x -> (f(x); x), x); return)
+
+using DataFlow: OSet
 
 function params(m)
   ps = OSet()
-  params(ps, m)
+  forparams(p -> push!(ps, p), m)
   return collect(ps)
 end