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[WIP] mode parameter for Convolution/cross-convolution #71

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Merged
merged 5 commits into from
Oct 8, 2018
Merged

[WIP] mode parameter for Convolution/cross-convolution #71

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b94257f
Initial commit
ayush1999 Oct 4, 2018
25dba3d
Changes for depthwiseconv
ayush1999 Oct 4, 2018
4584bef
Adapted to previous changes
ayush1999 Oct 5, 2018
c4d301d
crossconv for depthwise conv
ayush1999 Oct 5, 2018
56eee8e
Removed duplicate code
ayush1999 Oct 6, 2018
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36 changes: 28 additions & 8 deletions src/conv.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,12 @@ function conv(x::A, w::A; pad = 0, stride = 1, dilation = 1) where A<:AbstractAr
x, w, pad = pad_, stride = stride_, dilation = dilation)
end

function crossconv(x::A, w::A; pad = 0, stride = 1, dilation = 1) where A<:AbstractArray
pad_, stride_ = padtuple(x, pad), padtuple(x, stride)
crossconv!(similar(x, cdims(size(x), dilation_dims(w, dilation), pad_, stride_)),
x, w, pad = pad_, stride = stride_, dilation = dilation)
end

∇conv_data(dy::A, x::A, w::A; pad = 0, stride = 1, dilation = 1) where A<:AbstractArray =
∇conv_data!(zero(x), dy, x, w; pad = pad, stride = stride, dilation = dilation)

Expand All @@ -39,12 +45,17 @@ end
# N-D dispatch

function conv!(y::AbstractArray{T,3}, x::AbstractArray{T,3}, w::AbstractArray{T,3};
pad = 0, stride = 1, dilation = 1) where T
pad = 0, stride = 1, dilation = 1, flipkernel =0) where T
args = map(x -> reshape(x, size(x,1),1,size(x,2),size(x,3)), (y, x, w))
conv!(args..., pad = (pad...,0), stride = (stride...,1), dilation = (dilation...,1))
conv!(args..., pad = (pad...,0), stride = (stride...,1), dilation = (dilation...,1), flipkernel=flipkernel)
return y
end

function crossconv!(y::AbstractArray, x::AbstractArray, w::AbstractArray;
pad = 0, stride = 1, dilation = 1)
conv!(y, x, w, pad=pad, stride=stride, dilation=dilation, flipkernel=1)
end

function ∇conv_filter!(dw::AbstractArray{T,3}, dy::AbstractArray{T,3},
x::AbstractArray{T,3}, w::AbstractArray{T,3};
pad = 0, stride = 1, dilation = 1) where T
Expand All @@ -62,8 +73,8 @@ function ∇conv_data!(dx::AbstractArray{T,3}, dy::AbstractArray{T,3},
end

conv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
pad = 0, stride = 1, dilation = 1) where T =
conv2d!(y, x, w, padding = pad, stride = stride, dilation = dilation)
pad = 0, stride = 1, dilation = 1, flipkernel=0) where T =
conv2d!(y, x, w, padding = pad, stride = stride, dilation = dilation, mode=flipkernel)

∇conv_filter!(dw::AbstractArray{T,4}, dy::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
pad = 0, stride = 1, dilation = 1) where T =
Expand All @@ -74,8 +85,8 @@ conv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
conv2d_grad_x!(dx, x, w, dy, padding = pad, stride = stride, dilation = dilation)

conv!(y::AbstractArray{T,5}, x::AbstractArray{T,5}, w::AbstractArray{T,5};
pad = 0, stride = 1, dilation = 1) where T =
conv3d!(y, x, w, padding = pad, stride = stride, dilation = dilation)
pad = 0, stride = 1, dilation = 1, flipkernel=0) where T =
conv3d!(y, x, w, padding = pad, stride = stride, dilation = dilation, mode=flipkernel)

∇conv_filter!(dw::AbstractArray{T,5}, dy::AbstractArray{T,5}, x::AbstractArray{T,5}, w::AbstractArray{T,5};
pad = 0, stride = 1, dilation = 1) where T =
Expand All @@ -85,7 +96,7 @@ conv!(y::AbstractArray{T,5}, x::AbstractArray{T,5}, w::AbstractArray{T,5};
pad = 0, stride = 1, dilation = 1) where T =
conv3d_grad_x!(dx, x, w, dy, padding = pad, stride = stride, dilation = dilation)

# Depthwise Conv
# Depthwise Conv

function dcdims(x::NTuple{4,Int}, w::NTuple{4,Int}, pad, stride)
((x[1] + 2 * pad[1] - w[1])÷stride[1] + 1,(x[2] + 2 * pad[2] - w[2])÷stride[2] + 1,w[3]*w[4],x[4])
Expand All @@ -96,9 +107,18 @@ function depthwiseconv(x::A, w::A; pad = 0, stride = 1) where A<:AbstractArray
depthwiseconv!(similar(x, dcdims(size(x), size(w), pad_, stride_)), x, w, pad = pad_, stride = stride_)
end

function depthwisecrossconv(x::A, w::A; pad = 0, stride = 1) where A<:AbstractArray
pad_, stride_ = padtuple(x, pad), padtuple(x, stride)
depthwisecrossconv!(similar(x, dcdims(size(x), size(w), pad_, stride_)), x, w, pad = pad_, stride = stride_)
end

depthwiseconv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
pad = 0, stride = 1, flipkernel=0) where T =
depthwiseconv2d!(y, x, w, padding = pad, stride = stride, mode= flipkernel)

depthwisecrossconv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
pad = 0, stride = 1) where T =
depthwiseconv2d!(y, x, w, padding = pad, stride = stride)
depthwiseconv!(y, x, w, pad = pad, stride = stride, flipkernel=1)

∇depthwiseconv_data(dy::A, x::A, w::A; pad = 0, stride = 1) where A<:AbstractArray =
∇depthwiseconv_data!(zero(x), dy, x, w; pad = pad, stride = stride)
Expand Down