Updated with all basic and conv layers outdims

src/layers/basic.jl

@@ -40,7 +40,7 @@ function Base.show(io::IO, c::Chain)
 end
 
 """
-    outdims(c::Chain, isize::Tuple)
+    outdims(c::Chain, isize)
 
 Calculate the output dimensions given the input dimensions, `isize`.
 
@@ -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::Tuple) = foldl(∘, map(l -> (x -> outdims(l, x)), c.layers))
+outdims(c::Chain, isize) = foldl(∘, map(l -> (x -> outdims(l, x)), c.layers))
 
 # This is a temporary and naive implementation
 # it might be replaced in the future for better performance
@@ -228,6 +228,18 @@ function (mo::Maxout)(input::AbstractArray)
     mapreduce(f -> f(input), (acc, out) -> max.(acc, out), mo.over)
 end
 
+"""
+    outdims(c::Maxout, isize)
+
+Calculate the output dimensions given the input dimensions, `isize`.
+
+```julia
+m = Maxout(Conv((3, 3), 3 => 16), Conv((3, 3), 16 => 32))
+outdims(m, (10, 10)) == (8, 8)
+```
+"""
+outdims(l::Maxout, isize) = outdims(first(l.over))
+
 """
     SkipConnection(layers, connection)
 

src/layers/conv.jl

@@ -1,6 +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))
 
 expand(N, i::Tuple) = i
 expand(N, i::Integer) = ntuple(_ -> i, N)
@@ -155,6 +156,18 @@ end
 (a::ConvTranspose{<:Any,<:Any,W})(x::AbstractArray{<:Real}) where {T <: Union{Float32,Float64}, W <: AbstractArray{T}} =
   a(T.(x))
 
+"""
+    outdims(l::ConvTranspose, isize::Tuple)
+
+Calculate the output dimensions given the input dimensions, `isize`.
+
+```julia
+m = ConvTranspose((3, 3), 3 => 16)
+outdims(m, (8, 8)) == (10, 10)
+```
+"""
+outdims(l::ConvTranspose{N}, isize) where N = _convtransoutdims(isize, size(l.weight)[1:N], l.stride, l.pad[1:N])
+
 """
     DepthwiseConv(size, in=>out)
     DepthwiseConv(size, in=>out, relu)
@@ -302,6 +315,18 @@ end
 (a::CrossCor{<:Any,<:Any,W})(x::AbstractArray{<:Real}) where {T <: Union{Float32,Float64}, W <: AbstractArray{T}} =
   a(T.(x))
 
+"""
+    outdims(l::CrossCor, isize::Tuple)
+
+Calculate the output dimensions given the input dimensions, `isize`.
+
+```julia
+m = CrossCor((3, 3), 3 => 16)
+outdims(m, (10, 10)) == (8, 8)
+```
+"""
+outdims(l::CrossCor{N}, isize) where N = _convoutdims(isize, size(l.weight)[1:N], l.stride, l.pad[1:N])
+
 """
     MaxPool(k)