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Groupwise #422

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aaeb377
removing depthwise since conv can proxy
arhik Nov 30, 2019
f861c25
arhik Dec 8, 2019
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44 changes: 22 additions & 22 deletions src/lib/nnlib.jl
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
using NNlib
import NNlib: softmax, ∇softmax, logsoftmax, ∇logsoftmax, conv, depthwiseconv, ∇conv_data, ∇depthwiseconv_data, maxpool, meanpool, σ, relu
import NNlib: softmax, ∇softmax, logsoftmax, ∇logsoftmax, conv, depthwiseconv, ∇conv_data, maxpool, meanpool, σ, relu

@adjoint function Base.Broadcast.broadcasted(::typeof(relu), x::Numeric)
relu.(x), Δ -> (nothing, ifelse.(x .> 0, Δ, zero.(x)))
Expand All @@ -14,8 +14,8 @@ end

@adjoint logsoftmax(xs) = logsoftmax(xs), Δ -> (∇logsoftmax(Δ, xs),)

@adjoint NNlib.DenseConvDims(args...; kwargs...) = NNlib.DenseConvDims(args...; kwargs...), _ -> nothing
@adjoint NNlib.DepthwiseConvDims(args...; kwargs...) = NNlib.DepthwiseConvDims(args...; kwargs...), _ -> nothing
@adjoint NNlib.ConvDims(args...; kwargs...) = NNlib.ConvDims(args...; kwargs...), _ -> nothing
# @adjoint NNlib.DepthwiseConvDims(args...; kwargs...) = NNlib.DepthwiseConvDims(args...; kwargs...), _ -> nothing
@adjoint NNlib.PoolDims(args...; kwargs...) = NNlib.PoolDims(args...; kwargs...), _ -> nothing

@adjoint conv(x, w, cdims; kw...) =
Expand All @@ -38,25 +38,25 @@ end
)
end

@adjoint depthwiseconv(x, w, cdims; kw...) =
depthwiseconv(x, w, cdims; kw...),
Δ -> begin
return (
NNlib.∇depthwiseconv_data(Δ, w, cdims; kw...),
NNlib.∇depthwiseconv_filter(x, Δ, cdims; kw...),
nothing,
)
end

@adjoint ∇depthwiseconv_data(x, w, cdims; kw...) =
∇depthwiseconv_data(x, w, cdims; kw...),
Δ -> begin
return (
NNlib.depthwiseconv(Δ, w, cdims; kw...),
NNlib.∇depthwiseconv_filter(Δ, x, cdims; kw...),
nothing,
)
end
# @adjoint depthwiseconv(x, w, cdims; kw...) =
# depthwiseconv(x, w, cdims; kw...),
# Δ -> begin
# return (
# NNlib.∇depthwiseconv_data(Δ, w, cdims; kw...),
# NNlib.∇depthwiseconv_filter(x, Δ, cdims; kw...),
# nothing,
# )
# end
#
# @adjoint ∇depthwiseconv_data(x, w, cdims; kw...) =
# ∇depthwiseconv_data(x, w, cdims; kw...),
# Δ -> begin
# return (
# NNlib.depthwiseconv(Δ, w, cdims; kw...),
# NNlib.∇depthwiseconv_filter(Δ, x, cdims; kw...),
# nothing,
# )
# end

@adjoint function maxpool(x, pdims; kw...)
y = maxpool(x, pdims; kw...)
Expand Down