Added tests for outdims

src/layers/basic.jl

@@ -49,7 +49,7 @@ m = Chain(Conv((3, 3), 3 => 16), Conv((3, 3), 16 => 32))
 outdims(m, (10, 10)) == (6, 6)
 ```
 """
-outdims(c::Chain, isize) = foldl(∘, map(l -> (x -> outdims(l, x)), c.layers))
+outdims(c::Chain, isize) = foldl(∘, map(l -> (x -> outdims(l, x)), c.layers))(isize)
 
 # This is a temporary and naive implementation
 # it might be replaced in the future for better performance
@@ -138,7 +138,7 @@ outdims(m, (5, 2)) == (5,)
 outdims(m, (10,)) == (5,)
 ```
 """
-outdims(l::Dense, isize) = (size(l.W)[2],)
+outdims(l::Dense, isize) = (size(l.W)[1],)
 
 """
     Diagonal(in::Integer)
@@ -234,11 +234,11 @@ end
 Calculate the output dimensions given the input dimensions, `isize`.
 
 ```julia
-m = Maxout(Conv((3, 3), 3 => 16), Conv((3, 3), 16 => 32))
+m = Maxout(() -> Conv((3, 3), 3 => 16), 2)
 outdims(m, (10, 10)) == (8, 8)
 ```
 """
-outdims(l::Maxout, isize) = outdims(first(l.over))
+outdims(l::Maxout, isize) = outdims(first(l.over), isize)
 
 """
     SkipConnection(layers, connection)

src/layers/conv.jl

@@ -1,7 +1,7 @@
 using NNlib: conv, ∇conv_data, depthwiseconv
 
 _convoutdims(isize, ksize, ssize, pad) = Int.(floor.((isize .- ksize .+ 2 .* pad) ./ ssize .+ 1))
-_convtransoutdims(isize, ksize, ssize, pad) = Int.(ssize .* (isize .- 1) .+ ksize .- 2 .* pad))
+_convtransoutdims(isize, ksize, ssize, pad) = Int.(ssize .* (isize .- 1) .+ ksize .- 2 .* pad)
 
 expand(N, i::Tuple) = i
 expand(N, i::Integer) = ntuple(_ -> i, N)
@@ -238,7 +238,7 @@ end
 Calculate the output dimensions given the input dimensions, `isize`.
 
 ```julia
-m = DepthwiseConv((3, 3), 3 => 16)
+m = DepthwiseConv((3, 3), 3 => 6)
 outdims(m, (10, 10)) == (8, 8)
 ```
 """
@@ -366,7 +366,7 @@ m = MaxPool((2, 2))
 outdims(m, (10, 10)) == (5, 5)
 ```
 """
-outdims(l::MaxPool{N}, isize) where N = _convoutdims(isize, l.weight, l.stride, l.pad[1:N])
+outdims(l::MaxPool{N}, isize) where N = _convoutdims(isize, l.k, l.stride, l.pad[1:N])
 
 """
     MeanPool(k)
@@ -406,4 +406,4 @@ m = MeanPool((2, 2))
 outdims(m, (10, 10)) == (5, 5)
 ```
 """
-outdims(l::MeanPool{N}, isize) where N = _convoutdims(isize, l.weight, l.stride, l.pad[1:N])
+outdims(l::MeanPool{N}, isize) where N = _convoutdims(isize, l.k, l.stride, l.pad[1:N])

test/layers/basic.jl

@@ -92,4 +92,19 @@ import Flux: activations
       @test size(SkipConnection(Dense(10,10), (a,b) -> cat(a, b, dims = 2))(input)) == (10,4)
     end
   end
+
+  @testset "output dimensions" begin
+    m = Chain(Conv((3, 3), 3 => 16), Conv((3, 3), 16 => 32))
+    @test Flux.outdims(m, (10, 10)) == (6, 6)
+
+    m = Dense(10, 5)
+    @test Flux.outdims(m, (5, 2)) == (5,)
+    @test Flux.outdims(m, (10,)) == (5,)
+
+    m = Flux.Diagonal(10)
+    @test Flux.outdims(m, (10,)) == (10,)
+
+    m = Maxout(() -> Conv((3, 3), 3 => 16), 2)
+    @test Flux.outdims(m, (10, 10)) == (8, 8)
+  end
 end

test/layers/conv.jl

@@ -107,3 +107,23 @@ end
     true
   end
 end
+
+@testset "conv output dimensions" begin
+  m = Conv((3, 3), 3 => 16)
+  @test Flux.outdims(m, (10, 10)) == (8, 8)
+
+  m = ConvTranspose((3, 3), 3 => 16)
+  @test Flux.outdims(m, (8, 8)) == (10, 10)
+
+  m = DepthwiseConv((3, 3), 3 => 6)
+  @test Flux.outdims(m, (10, 10)) == (8, 8)
+
+  m = CrossCor((3, 3), 3 => 16)
+  @test Flux.outdims(m, (10, 10)) == (8, 8)
+
+  m = MaxPool((2, 2))
+  @test Flux.outdims(m, (10, 10)) == (5, 5)
+
+  m = MeanPool((2, 2))
+  @test Flux.outdims(m, (10, 10)) == (5, 5)
+end