TastyPancakes/Flux.jl
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ditto remaining layers

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This commit is contained in:
Dhairya Gandhi 2019-10-06 04:41:06 +05:30
parent 55ef7c1aba
commit 48a305bd21
1 changed files with 18 additions and 16 deletions
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34
src/layers/conv.jl
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@ -42,7 +42,7 @@ forward pass.
Takes the keyword arguments `pad`, `stride` and `dilation`. Takes the keyword arguments `pad`, `stride` and `dilation`.
""" """
function Conv(w::AbstractArray{T,N}, b::AbstractVector{T}, σ = identity; function Conv(w::AbstractArray{T,N}, b::Union{Number, AbstractVector{T}}, σ = identity;
stride = 1, pad = 0, dilation = 1) where {T,N} stride = 1, pad = 0, dilation = 1) where {T,N}
stride = expand(Val(N-2), stride) stride = expand(Val(N-2), stride)
pad = expand(Val(2*(N-2)), pad) pad = expand(Val(2*(N-2)), pad)
@ -105,19 +105,19 @@ struct ConvTranspose{N,M,F,A,V}
dilation::NTuple{N,Int} dilation::NTuple{N,Int}
end end
function ConvTranspose(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVector{T}}, σ = identity; function ConvTranspose(w::AbstractArray{T,N}, b::Union{Number, AbstractVector{T}}, σ = identity;
stride = 1, pad = 0, dilation = 1) where {T,N} stride = 1, pad = 0, dilation = 1) where {T,N}
stride = expand(Val(N-2), stride) stride = expand(Val(N-2), stride)
pad = expand(Val(2*(N-2)), pad) pad = expand(Val(2*(N-2)), pad)
dilation = expand(Val(N-2), dilation) dilation = expand(Val(N-2), dilation)
b = b isa Nothing ? ZeroType((size(w, ndims(w)), )) : b
return ConvTranspose(σ, w, b, stride, pad, dilation) return ConvTranspose(σ, w, b, stride, pad, dilation)
end end
function ConvTranspose(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity; function ConvTranspose(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity;
init = glorot_uniform, stride = 1, pad = 0, dilation = 1, use_bias = true) where N init = glorot_uniform, stride = 1, pad = 0, dilation = 1,
b = use_bias ? zeros(ch[2]) : ZeroType((ch[2], )) weight = convweight(k, reverse(ch), init = init), bias = convbias(ch[2])) where N
ConvTranspose(init(k..., reverse(ch)...), b, σ,
ConvTranspose(weight, bias, σ,
stride = stride, pad = pad, dilation = dilation) stride = stride, pad = pad, dilation = dilation)
end end
@ -178,22 +178,24 @@ struct DepthwiseConv{N,M,F,A,V}
dilation::NTuple{N,Int} dilation::NTuple{N,Int}
end end
function DepthwiseConv(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVector{T}}, σ = identity; function DepthwiseConv(w::AbstractArray{T,N}, b::Union{Number AbstractVector{T}}, σ = identity;
stride = 1, pad = 0, dilation = 1) where {T,N} stride = 1, pad = 0, dilation = 1) where {T,N}
stride = expand(Val(N-2), stride) stride = expand(Val(N-2), stride)
pad = expand(Val(2*(N-2)), pad) pad = expand(Val(2*(N-2)), pad)
dilation = expand(Val(N-2), dilation) dilation = expand(Val(N-2), dilation)
b = b isa Nothing ? ZeroType((size(w, ndims(w)), )) : b
return DepthwiseConv(σ, w, b, stride, pad, dilation) return DepthwiseConv(σ, w, b, stride, pad, dilation)
end end
depthwiseconvweight(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer};
init = glorot_uniform) where N = init(k..., div(ch[2], ch[1]), ch[1])
function DepthwiseConv(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity; function DepthwiseConv(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity;
init = glorot_uniform, stride = 1, pad = 0, dilation = 1, use_bias = true) where N init = glorot_uniform, stride = 1, pad = 0, dilation = 1,
weight = depthwiseconvweight(k, ch, init = init), bias = convbias(ch[2])) where N
@assert ch[2] % ch[1] == 0 "Output channels must be integer multiple of input channels" @assert ch[2] % ch[1] == 0 "Output channels must be integer multiple of input channels"
b = use_bias ? zeros(ch[2]) : ZeroType((ch[2], ))
return DepthwiseConv( return DepthwiseConv(
init(k..., div(ch[2], ch[1]), ch[1]), weight,
b, bias,
σ; σ;
stride = stride, stride = stride,
pad = pad, pad = pad,
@ -252,7 +254,7 @@ struct CrossCor{N,M,F,A,V}
dilation::NTuple{N,Int} dilation::NTuple{N,Int}
end end
function CrossCor(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVector{T}}, σ = identity; function CrossCor(w::AbstractArray{T,N}, b::Union{Number, AbstractVector{T}}, σ = identity;
stride = 1, pad = 0, dilation = 1) where {T,N} stride = 1, pad = 0, dilation = 1) where {T,N}
stride = expand(Val(N-2), stride) stride = expand(Val(N-2), stride)
pad = expand(Val(2*(N-2)), pad) pad = expand(Val(2*(N-2)), pad)
@ -262,9 +264,9 @@ function CrossCor(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVec
end end
function CrossCor(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity; function CrossCor(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity;
init = glorot_uniform, stride = 1, pad = 0, dilation = 1, use_bias = true) where N init = glorot_uniform, stride = 1, pad = 0, dilation = 1,
b = use_bias ? zeros(ch[2]) : ZeroType((ch[2],)) weight = convweight(k, ch, init = init), bias = convbias(ch[2])) where N
CrossCor(init(k..., ch...), b, σ, CrossCor(weight, bias, σ,
stride = stride, pad = pad, dilation = dilation) stride = stride, pad = pad, dilation = dilation)
end end