basic MXNet output

REQUIRE

@@ -1 +1,2 @@
 julia 0.5-
+MXNet

src/Flux.jl

@@ -21,4 +21,6 @@ include("layers/dense.jl")
 include("layers/sequence.jl")
 include("utils.jl")
 
+include("backend/mxnet/mxnet.jl")
+
 end # module

src/backend/mxnet/graph.jl

@@ -0,0 +1,30 @@
+cvalue(x) = x
+cvalue(c::Constant) = c.value
+cvalue(v::Vertex) = cvalue(value(v))
+
+graph(vars, model, args...) = node(model, args...)
+
+graph(vars, x::mx.SymbolicNode) = x
+
+# TODO: detect parameters used more than once
+function graph(vars, value::AArray)
+  id = gensym()
+  vars[id] = value
+  return mx.Variable(id)
+end
+
+function graph(vars, model::Model, args...)
+  g = Flux.graph(model)
+  g = Flow.mapconst(g) do x
+    !isa(x, Flux.Parameter) ? x :
+    isa(x.name, Integer) ? args[x.name] : getfield(model, x.name)
+  end
+  postwalk(g) do v
+    vertex(graph(vars, cvalue(v), cvalue.(inputs(v))...))
+  end |> value
+end
+
+# Built-in implemenations
+
+node(::typeof(*), args...) = mx.dot(args...)
+node(::typeof(+), args...) = mx.broadcast_plus(args...)

src/backend/mxnet/model.jl

@@ -0,0 +1,21 @@
+type MXModel
+  model::Any
+  params::Dict{Symbol,Any}
+  exec::mx.Executor
+end
+
+mxdims(dims::NTuple) =
+  length(dims) == 1 ? (1, dims...) : reverse(dims)
+
+function mxargs(args)
+  map(args) do kv
+    arg, value = kv
+    arg => mx.zeros(mxdims(size(value)))
+  end
+end
+
+function mxnet(model::Model, input)
+  vars = Dict{Symbol,Any}(:input => mx.zeros(mxdims(input)))
+  node = graph(vars, model, mx.Variable(:input))
+  MXModel(model, vars, mx.bind(node, args = mxargs(vars), grad_req = mx.GRAD_NOP))
+end

src/backend/mxnet/mxnet.jl

@@ -0,0 +1,12 @@
+module MX
+
+using MXNet, Flow, ..Flux
+
+include("graph.jl")
+include("model.jl")
+
+# d = Dense(20, 10)
+
+# model = mxnet(d, (1,20))
+
+end

src/layers/dense.jl

@@ -1,3 +1,5 @@
+export Dense
+
 @model type Dense
   W
   b

src/utils.jl

@@ -1,4 +1,6 @@
-export onehot, onecold
+export AArray, onehot, onecold
+
+const AArray = AbstractArray
 
 onehot(label, labels) = [i == label for i in labels]
 onecold(pred, labels = 1:length(pred)) = labels[findfirst(pred, maximum(pred))]