test restructure

test/backend.jl

@@ -1,48 +0,0 @@
-xs = rand(20)
-d = Affine(20, 10)
-
-# MXNet
-
-@mxonly let dm = mxnet(d, (20, 1))
-  @test d(xs) ≈ dm(xs)
-end
-
-@mxonly let
-  # TODO: test run
-  using MXNet
-  f = mx.FeedForward(Chain(d, softmax))
-  @test mx.infer_shape(f.arch, data = (20, 1))[2] == [(10, 1)]
-
-  m = Chain(Input(28,28), Conv2D((5,5), out = 3), MaxPool((2,2)),
-            flatten, Affine(1587, 10), softmax)
-  f = mx.FeedForward(m)
-  @test mx.infer_shape(f.arch, data = (20, 20, 5, 1))[2] == [(10, 1)]
-end
-
-@mxonly let
-  model = TLP(Affine(10, 20), Affine(21, 15))
-  info("The following warning is normal")
-  e = try mxnet(model, (10, 1))
-  catch e e end
-
-  @test isa(e, DataFlow.Interpreter.Exception)
-  @test e.trace[1].func == Symbol("Flux.Affine")
-  @test e.trace[2].func == :TLP
-end
-
-# TensorFlow
-
-@tfonly let dt = tf(d)
-  @test d(xs) ≈ dt(xs)
-end
-
-@tfonly let
-  using TensorFlow
-
-  sess = TensorFlow.Session()
-  X = placeholder(Float32)
-  Y = Tensor(d, X)
-  run(sess, initialize_all_variables())
-
-  @test run(sess, Y, Dict(X=>xs')) ≈ d(xs)'
-end

test/backend/mxnet.jl

@@ -0,0 +1,34 @@
+using MXNet
+Flux.loadmx()
+
+@testset "MXNet" begin
+
+xs = rand(20)
+d = Affine(20, 10)
+
+dm = mxnet(d, (20, 1))
+@test d(xs) ≈ dm(xs)
+
+@testset "FeedForward interface" begin
+  # TODO: test run
+  f = mx.FeedForward(Chain(d, softmax))
+  @test mx.infer_shape(f.arch, data = (20, 1))[2] == [(10, 1)]
+
+  m = Chain(Input(28,28), Conv2D((5,5), out = 3), MaxPool((2,2)),
+            flatten, Affine(1587, 10), softmax)
+  f = mx.FeedForward(m)
+  @test mx.infer_shape(f.arch, data = (20, 20, 5, 1))[2] == [(10, 1)]
+end
+
+@testset "Stack Traces" begin
+  model = TLP(Affine(10, 20), Affine(21, 15))
+  info("The following warning is normal")
+  e = try mxnet(model, (10, 1))
+  catch e e end
+
+  @test isa(e, DataFlow.Interpreter.Exception)
+  @test e.trace[1].func == Symbol("Flux.Affine")
+  @test e.trace[2].func == :TLP
+end
+
+end

test/backend/tensorflow.jl

@@ -0,0 +1,21 @@
+using TensorFlow
+Flux.loadtf()
+
+@testset "TensorFlow" begin
+
+xs = rand(20)
+d = Affine(20, 10)
+
+dt = tf(d)
+@test d(xs) ≈ dt(xs)
+
+@testset "Tensor interface" begin
+  sess = TensorFlow.Session()
+  X = placeholder(Float32)
+  Y = Tensor(d, X)
+  run(sess, initialize_all_variables())
+
+  @test run(sess, Y, Dict(X=>xs')) ≈ d(xs)'
+end
+
+end

test/runtests.jl

@@ -16,4 +16,5 @@ end
 include("batching.jl")
 include("basic.jl")
 include("recurrent.jl")
-include("backend.jl")
+@tfonly include("backend/tensorflow.jl")
+@mxonly include("backend/mxnet.jl")