silo the compiler

src/Flux.jl

@@ -2,17 +2,10 @@ __precompile__()
 
 module Flux
 
-using MacroTools, Lazy, DataFlow, Juno
-using DataFlow: graphm, syntax, prewalk!, postwalk!, prewalk, postwalk,
-  iscyclic, Constant, constant, isconstant, group, Split, splitnode,
-  detuple, value, inputs, thread!, value, inputs, Split, splitnode, inputnode,
-  spliceinputs, bumpinputs, Line, Frame, applylines, graphinputs
-using DataFlow.Interpreter
+using Juno
+using Lazy: @forward
 
-export @net, unroll, unroll1, @shapes,
-  @Chain, Chain, Input, Affine, Conv2D, Recurrent, GatedRecurrent, LSTM,
-  σ, relu, softmax,
-  tf, mxnet
+export Chain, Affine, σ, softmax
 
 # Zero Flux Given
 
@@ -23,9 +16,8 @@ export track, back!
 include("utils.jl")
 include("params.jl")
 
-include("compiler/code.jl")
-include("compiler/loops.jl")
-include("compiler/interp.jl")
+include("compiler/Compiler.jl")
+using .Compiler: @net
 
 include("layers/control.jl")
 include("layers/affine.jl")

src/compiler/Compiler.jl

@@ -0,0 +1,14 @@
+module Compiler
+
+using MacroTools, DataFlow, DataFlow.Interpreter
+
+using DataFlow: graphm, syntax, prewalk!, postwalk!, prewalk, postwalk,
+  iscyclic, Constant, constant, isconstant, group, Split, splitnode,
+  detuple, value, inputs, thread!, value, inputs, Split, splitnode, inputnode,
+  spliceinputs, bumpinputs, Line, Frame, applylines, graphinputs
+
+include("code.jl")
+include("interp.jl")
+include("loops.jl")
+
+end

src/compiler/code.jl

@@ -1,5 +1,6 @@
 import DataFlow: cse
 using MacroTools: @q, @>
+import ..Flux: Param, param, state
 
 graph(m) = nothing
 
@@ -18,11 +19,11 @@ function makegraph(graph, args, params = [])
   end
   graph = map(graph) do x
     x isa Offset ?
-      :(Flux.Offset($(Expr(:quote, x.name)), $(x.n),
+      :(Flux.Compiler.Offset($(Expr(:quote, x.name)), $(x.n),
                     $(x.name in params ? :(self.$(x.name)) : x.name))) :
       x
   end
-  vertex(:(Flux.Frame(self)), graph)
+  vertex(:($DataFlow.Frame(self)), graph)
 end
 
 function build_type(T, params)
@@ -68,7 +69,7 @@ function process_type(ex)
   quote
     $(build_type(T, params))
     $(esc(:((self::$T)($(args...)) = $(build_forward(body, args)))))
-    $(esc(:(Flux.graph(self::$T)))) = $(DataFlow.constructor(map(esc, makegraph(body, args, params))))
+    $(esc(:(Flux.Compiler.graph(self::$T)))) = $(DataFlow.constructor(map(esc, makegraph(body, args, params))))
     nothing
   end
 end

src/compiler/loops.jl

@@ -1,3 +1,5 @@
+using ..Flux: stack, unstack
+
 # Stateful Models
 
 mutable struct Stateful

src/layers/control.jl

@@ -8,7 +8,7 @@ end
 
 (s::Chain)(x) = foldl((x, m) -> m(x), x, s.layers)
 
-graph(s::Chain) =
+Compiler.graph(s::Chain) =
   foldl((v, m) -> vertex(m, v), constant(inputnode(1)), s.layers)
 
 Base.getindex(c::Chain, i::AbstractArray) = Chain(c.layers[i]...)

src/utils.jl

@@ -15,27 +15,6 @@ convertel{T}(::Type{T}, xs::AbstractArray{T}) = xs
 
 a ∘ b = a .* b
 
-broadcastto(xs::AbstractArray, shape) = xs .* ones(shape)
-
-# Tuples
-
-mapt(f, x) = f(x)
-mapt(f, xs::Tuple) = map(x -> mapt(f, x), xs)
-
-function collectt(xs)
-  ys = []
-  mapt(x -> push!(ys, x), xs)
-  return ys
-end
-
-function shapecheckt(xs::Tuple, ys::Tuple)
-  length(xs) == length(ys) || error("Expected tuple length $(length(xs)), got $ys")
-  shapecheckt.(xs, ys)
-end
-
-shapecheckt(xs::Tuple, ys) = error("Expected tuple, got $ys")
-shapecheckt(xs, ys) = nothing
-
 # Other
 
 function accuracy(m, data)

test/backend/common.jl

@@ -19,7 +19,7 @@ end
 function test_recurrence(bk)
   @testset "Recurrence" begin
     seq = unsqueeze(stack(rand(10) for i = 1:3))
-    r = unroll(Recurrent(10, 5), 3)
+    r = Flux.Compiler.unroll(Recurrent(10, 5), 3)
     rm = bk(r)
     @test r(seq) ≈ rm(seq)
   end

test/basic.jl

@@ -1,3 +1,5 @@
+using Flux: Affine
+
 syntax(v::Vertex) = prettify(DataFlow.syntax(v))
 syntax(x) = syntax(graph(x))
 
@@ -21,12 +23,12 @@ test_anon(identity)
 let a1 = Affine(10, 20), a2 = Affine(20, 15)
   tlp = TLP(a1, a2)
   @test tlp(xs) ≈ softmax(a2(σ(a1(xs))))
-  @test Flux.interpmodel(tlp, xs) ≈ softmax(a2(σ(a1(xs))))
+  @test Flux.Compiler.interpmodel(tlp, xs) ≈ softmax(a2(σ(a1(xs))))
 end
 
 let tlp = TLP(Affine(10, 21), Affine(20, 15))
   e = try
-    Flux.interpmodel(tlp, rand(1, 10))
+    Flux.Compiler.interpmodel(tlp, rand(1, 10))
   catch e
     e
   end

test/recurrent.jl

@@ -1,3 +1,5 @@
+using Flux: Recurrent
+
 function apply(model, xs, state)
   ys = similar(xs, 0)
   for x in xs
@@ -10,8 +12,8 @@ end
 @testset "RNN unrolling" begin
   r = Recurrent(10, 5)
   xs = [rand(1, 10) for _ = 1:3]
-  _, ys = apply(unroll1(r).model, xs, (r.y.x,))
+  _, ys = apply(Flux.Compiler.unroll1(r).model, xs, (r.y.x,))
   @test ys[1] == tanh(xs[1] * r.Wxy.x .+ r.y.x * r.Wyy.x .+ r.by.x)
-  ru = unroll(r, 3)
+  ru = Flux.Compiler.unroll(r, 3)
   ru(unsqueeze(stack(squeeze.(xs))))[1] == squeeze.(ys)
 end

test/runtests.jl

@@ -1,5 +1,6 @@
 using Flux, DataFlow, MacroTools, Base.Test
-using Flux: graph, Param, squeeze, unsqueeze, stack, update!, flatten
+using Flux: Param, param, squeeze, unsqueeze, stack, update!, flatten
+using Flux.Compiler: @net
 using DataFlow: Line, Frame
 
 @testset "Flux" begin