handling of multiple outputs

src/backend/tensorflow/model.jl

@@ -3,17 +3,19 @@ type Model
   session::Session
   params::Dict{Flux.Param,Tensor}
   inputs::Vector{Tensor}
-  outputs::Vector{Tensor}
+  output
   gradients::Vector{Tensor}
 end
 
+ismultioutput(m::Model) = !isa(m.output, Tensor)
+
 function tf(model)
   sess = Session(Graph())
   input = placeholder(Float32)
   params, output = tograph(model, input)
   run(sess, initialize_all_variables())
   Model(model, sess, params,
-        [input], [output],
+        [input], output,
         [gradients(output, input)])
 end
 
@@ -28,10 +30,14 @@ end
 
 function (m::Model)(args::Batch...)
   @assert length(args) == length(m.inputs)
-  batch(run(m.session, m.outputs[1], Dict(zip(m.inputs, args))))
+  output = run(m.session, m.output, Dict(zip(m.inputs, args)))
+  ismultioutput(m) ? (batch.(output)...,) : batch(output)
 end
 
-(m::Model)(args...) = first(m(map(batchone, args)...))
+function (m::Model)(args...)
+  output = m(map(batchone, args)...)
+  ismultioutput(m) ? map(first, output) : first(output)
+end
 
 function Flux.back!(m::Model, Δ, args...)
   @assert length(args) == length(m.inputs)