TastyPancakes/Flux.jl
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fix conv2d shape inference

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This commit is contained in:
Mike J Innes 2016-10-10 23:20:40 +01:00
parent 4961bf72af
commit 438dc9d40a
1 changed files with 2 additions and 2 deletions
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4
src/layers/shims.jl
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@ -1,7 +1,7 @@
export Conv2D, MaxPool export Conv2D, MaxPool
type Conv2D <: Model type Conv2D <: Model
filter::Param{Array{Float32,4}} # [height, width, outchans, inchans] filter::Param{Array{Float32,4}} # [height, width, inchans, outchans]
stride::Dims{2} stride::Dims{2}
end end
@ -9,7 +9,7 @@ Conv2D(size; in = 1, out = 1, stride = (1,1), init = initn) =
Conv2D(param(initn(size..., in, out)), stride) Conv2D(param(initn(size..., in, out)), stride)
shape(c::Conv2D, in::Dims{2}) = shape(c::Conv2D, in::Dims{2}) =
(map(i -> (in[i]-size(c.filter,i))÷c.stride[i]+1, (1,2))..., size(c.filter, 3)) (map(i -> (in[i]-size(c.filter,i))÷c.stride[i]+1, (1,2))..., size(c.filter, 4))
shape(c::Conv2D, in::Dims{3}) = shape(c::Conv2D, in::Dims{3}) =
shape(c, (in[1],in[2])) shape(c, (in[1],in[2]))