diff --git a/src/backend/mxnet/graph.jl b/src/backend/mxnet/graph.jl
index 1e430f14..c60f1db6 100644
--- a/src/backend/mxnet/graph.jl
+++ b/src/backend/mxnet/graph.jl
@@ -85,7 +85,7 @@ function tograph(model, args...; feedforward = false)
                 params = Dict(), stacks = Dict(),
                 feedforward = feedforward)
   out = @ithrow graph(ctx, model, args...)
-  return ctx[:params], ctx[:stacks], out
+  return Graph(out, ctx[:params], ctx[:stacks])
 end
 
 # Error Handling
diff --git a/src/backend/mxnet/model.jl b/src/backend/mxnet/model.jl
index 4ae1f93f..10f3df17 100644
--- a/src/backend/mxnet/model.jl
+++ b/src/backend/mxnet/model.jl
@@ -1,10 +1,15 @@
 using Flux: batchone, rebatch
 
+type Graph
+  node::mx.SymbolicNode
+  params::Dict{Symbol,Any}
+  stacks::Dict{Any,Any}
+end
+
 type Model <: Flux.Model
   model::Any
-  params::Dict{Symbol,Any}
+  graph::Graph
   grads::Dict{Symbol,Any}
-  stack::Dict{Any,Any}
   exec::mx.Executor
 end
 
@@ -30,19 +35,19 @@ end
 
 function loadparams!(model::Model)
   for (name, arr) in model.exec.arg_dict
-    haskey(model.params, name) && copy!(arr, model.params[name])
+    haskey(model.graph.params, name) && copy!(arr, model.graph.params[name])
   end
   return model
 end
 
 function mxnet(model::Flux.Model, input)
-  params, stacks, node = tograph(model, mx.Variable(:input))
-  args = merge(mxargs(params), Dict(:input => mx.zeros(input)))
+  graph = tograph(model, mx.Variable(:input))
+  args = merge(mxargs(graph.params), Dict(:input => mx.zeros(input)))
   grads = mxgrads(args)
-  model = @mxerr stacks Model(model, params, grads, stacks,
-                                mx.bind(node, args = args,
-                                              args_grad = grads,
-                                              grad_req = mx.GRAD_ADD))
+  model = @mxerr graph.stacks Model(model, graph, grads,
+                                    mx.bind(graph.node, args = args,
+                                            args_grad = grads,
+                                            grad_req = mx.GRAD_ADD))
   loadparams!(model)
   return model
 end
@@ -94,8 +99,8 @@ end
 
 function mx.FeedForward(model::Flux.Model; input = :data, label = :softmax, context = mx.cpu())
   model = rewrite_softmax(model, label)
-  vars, stacks, node = tograph(model, mx.Variable(input), feedforward=true)
-  ff = mx.FeedForward(node, context = context)
-  isempty(vars) || (ff.arg_params = mxargs(vars))
+  graph = tograph(model, mx.Variable(input), feedforward=true)
+  ff = mx.FeedForward(graph.node, context = context)
+  isempty(graph.params) || (ff.arg_params = mxargs(graph.params))
   return ff
 end