ditto remaining layers
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@ -42,7 +42,7 @@ forward pass.
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Takes the keyword arguments `pad`, `stride` and `dilation`.
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"""
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function Conv(w::AbstractArray{T,N}, b::AbstractVector{T}, σ = identity;
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function Conv(w::AbstractArray{T,N}, b::Union{Number, AbstractVector{T}}, σ = identity;
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stride = 1, pad = 0, dilation = 1) where {T,N}
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stride = expand(Val(N-2), stride)
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pad = expand(Val(2*(N-2)), pad)
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@ -105,19 +105,19 @@ struct ConvTranspose{N,M,F,A,V}
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dilation::NTuple{N,Int}
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end
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function ConvTranspose(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVector{T}}, σ = identity;
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function ConvTranspose(w::AbstractArray{T,N}, b::Union{Number, AbstractVector{T}}, σ = identity;
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stride = 1, pad = 0, dilation = 1) where {T,N}
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stride = expand(Val(N-2), stride)
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pad = expand(Val(2*(N-2)), pad)
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dilation = expand(Val(N-2), dilation)
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b = b isa Nothing ? ZeroType((size(w, ndims(w)), )) : b
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return ConvTranspose(σ, w, b, stride, pad, dilation)
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end
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function ConvTranspose(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity;
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init = glorot_uniform, stride = 1, pad = 0, dilation = 1, use_bias = true) where N
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b = use_bias ? zeros(ch[2]) : ZeroType((ch[2], ))
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ConvTranspose(init(k..., reverse(ch)...), b, σ,
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init = glorot_uniform, stride = 1, pad = 0, dilation = 1,
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weight = convweight(k, reverse(ch), init = init), bias = convbias(ch[2])) where N
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ConvTranspose(weight, bias, σ,
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stride = stride, pad = pad, dilation = dilation)
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end
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@ -178,22 +178,24 @@ struct DepthwiseConv{N,M,F,A,V}
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dilation::NTuple{N,Int}
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end
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function DepthwiseConv(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVector{T}}, σ = identity;
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function DepthwiseConv(w::AbstractArray{T,N}, b::Union{Number AbstractVector{T}}, σ = identity;
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stride = 1, pad = 0, dilation = 1) where {T,N}
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stride = expand(Val(N-2), stride)
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pad = expand(Val(2*(N-2)), pad)
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dilation = expand(Val(N-2), dilation)
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b = b isa Nothing ? ZeroType((size(w, ndims(w)), )) : b
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return DepthwiseConv(σ, w, b, stride, pad, dilation)
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end
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depthwiseconvweight(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer};
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init = glorot_uniform) where N = init(k..., div(ch[2], ch[1]), ch[1])
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function DepthwiseConv(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity;
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init = glorot_uniform, stride = 1, pad = 0, dilation = 1, use_bias = true) where N
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init = glorot_uniform, stride = 1, pad = 0, dilation = 1,
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weight = depthwiseconvweight(k, ch, init = init), bias = convbias(ch[2])) where N
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@assert ch[2] % ch[1] == 0 "Output channels must be integer multiple of input channels"
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b = use_bias ? zeros(ch[2]) : ZeroType((ch[2], ))
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return DepthwiseConv(
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init(k..., div(ch[2], ch[1]), ch[1]),
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b,
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weight,
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bias,
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σ;
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stride = stride,
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pad = pad,
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@ -252,7 +254,7 @@ struct CrossCor{N,M,F,A,V}
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dilation::NTuple{N,Int}
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end
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function CrossCor(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVector{T}}, σ = identity;
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function CrossCor(w::AbstractArray{T,N}, b::Union{Number, AbstractVector{T}}, σ = identity;
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stride = 1, pad = 0, dilation = 1) where {T,N}
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stride = expand(Val(N-2), stride)
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pad = expand(Val(2*(N-2)), pad)
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@ -262,9 +264,9 @@ function CrossCor(w::AbstractArray{T,N}, b::Union{Nothing, ZeroType, AbstractVec
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end
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function CrossCor(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity;
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init = glorot_uniform, stride = 1, pad = 0, dilation = 1, use_bias = true) where N
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b = use_bias ? zeros(ch[2]) : ZeroType((ch[2],))
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CrossCor(init(k..., ch...), b, σ,
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init = glorot_uniform, stride = 1, pad = 0, dilation = 1,
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weight = convweight(k, ch, init = init), bias = convbias(ch[2])) where N
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CrossCor(weight, bias, σ,
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stride = stride, pad = pad, dilation = dilation)
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end
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