multi test is redundant

test/backend/mxnet.jl

@@ -9,10 +9,6 @@ d = Affine(20, 10)
 dm = mxnet(d)
 @test d(xs) ≈ dm(xs)
 
-m = Multi(20, 15)
-mm = mxnet(m)
-@test all(isapprox.(mm(xs, ys), m(xs, ys)))
-
 @testset "Tuple I/O" begin
   @test mxnet(@net x -> (x,))([1,2,3]) == ([1,2,3],)
   @test mxnet(@net x -> x[1].*x[2])(([1,2,3],[4,5,6])) == [4,10,18]

test/backend/tensorflow.jl

@@ -9,10 +9,6 @@ d = Affine(20, 10)
 dt = tf(d)
 @test d(xs) ≈ dt(xs)
 
-m = Multi(20, 15)
-mm = tf(m)
-@test all(isapprox.(mm(xs, ys), m(xs, ys)))
-
 @testset "Tuple I/O" begin
   @test tf(@net x -> (identity(x),))([1,2,3]) == ([1,2,3],)
   @test tf(@net x -> x[1].*x[2])(([1,2,3],[4,5,6])) == [4,10,18]

test/basic.jl

@@ -32,10 +32,4 @@ let tlp = TLP(Affine(10, 21), Affine(20, 15))
   @test e.trace[end-1].func == Symbol("Flux.Affine")
 end
 
-let m = Multi(10, 15)
-  x, y = rand(1, 10), rand(1, 10)
-  @test all(isapprox.(m(x, y), (x * m.W.x, y * m.V.x)))
-  @test all(isapprox.(m(x, y), Flux.interpmodel(m, x, y)))
-end
-
 end

test/runtests.jl

@@ -22,15 +22,6 @@ end
   end
 end
 
-@net type Multi
-  W
-  V
-  (x, y) -> (x*W, y*V)
-end
-
-Multi(in::Integer, out::Integer) =
-  Multi(randn(in, out), randn(in, out))
-
 include("batching.jl")
 include("basic.jl")
 include("recurrent.jl")