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remove some old cruft #21

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merged 4 commits into from
Jul 15, 2021
Merged

remove some old cruft #21

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b68d082
remove some old cruft
CarloLucibello Jul 15, 2021
b44c045
fix pooling
CarloLucibello Jul 15, 2021
45e94e5
fix pooling
CarloLucibello Jul 15, 2021
e94cafd
fix tests
CarloLucibello Jul 15, 2021
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295 changes: 0 additions & 295 deletions Manifest.toml
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49 changes: 4 additions & 45 deletions src/cudnn/conv.jl
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Original file line number Diff line number Diff line change
@@ -1,9 +1,6 @@

# Deprecated methods
using NNlib: DenseConvDims
import NNlib: stride, padding, dilation, flipkernel, spatial_dims, kernel_size,
conv!, ∇conv_filter!, ∇conv_data!,
maxpool!, meanpool!, ∇maxpool!, ∇meanpool!, PoolDims
import NNlib: conv!, ∇conv_filter!, ∇conv_data!, conv_bias_act!

using CUDA.CUDNN: scalingParameter, CUDNN_CONVOLUTION, convdims,
cudnnConvolutionDescriptor, cudnnConvolutionBwdDataAlgoPerf,
Expand All @@ -13,18 +10,7 @@ using CUDA.CUDNN: scalingParameter, CUDNN_CONVOLUTION, convdims,

const CUDNNFloat = Union{Float16,Float32,Float64}

# Since CUDNN does not support 1D convolution, Conv in Flux will give a CUDNNError if the size is 1-dimensional.
fix1d(x) = x
fix1d(x::DenseCuArray{T, 3}) where T = reshape(x, 1, size(x, 1), size(x, 2), size(x, 3))
fix1d(cdims::DenseConvDims{1,K,C_in,C_out,S,P,D,F}) where {K,C_in,C_out,S,P,D,F} =
DenseConvDims{2,(1,K...),C_in,C_out,(1,S...),(0,0,P...),(1,D...),F}((1,cdims.I...))
fix1d(pdims::PoolDims{1,K,S,P,D}) where {K,S,P,D,F} =
PoolDims{2,(1,K...),(1,S...),(0,0,P...),(1,D...)}((1,pdims.I...), pdims.C_in)

# Convolution

function cudnnConvolutionDescriptor(cdims::DenseConvDims, x::DenseCuArray{T}) where T
cdims, x = fix1d(cdims), fix1d(x)
mode=(NNlib.flipkernel(cdims) ? CUDNN_CROSS_CORRELATION : CUDNN_CONVOLUTION)
cudnnConvolutionDescriptor(convdims(nnlibPadding(cdims),size(x),0),
convdims(NNlib.stride(cdims),size(x),1),
Expand All @@ -48,9 +34,9 @@ function conv!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T}, cdims
cudnnConvolutionForward!(y, w, x, d; alpha, beta, z=y)
end

function NNlib.conv_bias_act!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T},
cdims::DenseConvDims, bias::DenseCuArray{T}, σ=identity;
z::DenseCuArray{T}=y, alpha=1, beta=0, algo=-1) where T<:CUDNNFloat
function conv_bias_act!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T},
cdims::DenseConvDims, bias::DenseCuArray{T}, σ=identity;
z::DenseCuArray{T}=y, alpha=1, beta=0, algo=-1) where T<:CUDNNFloat
if cudnnversion() < v"6"
all(x -> x == 1, dilation(cdims)) || error("Only dilation = 1 is supported in cuDNN version < 6")
end
Expand Down Expand Up @@ -103,36 +89,9 @@ function ∇conv_filter!(dw::DenseCuArray{T}, x::DenseCuArray{T}, dy::DenseCuArr
return dw
end


function ∇conv_bias!(db::DenseCuArray{T}, dy::DenseCuArray{T}; alpha=1, beta=0) where T<:CUDNNFloat
alpha,beta = scalingParameter(T,alpha), scalingParameter(T,beta)
bDesc, yDesc = cudnnTensorDescriptor.((db,dy))
cudnnConvolutionBackwardBias(handle(), alpha, yDesc, dy, beta, bDesc, db)
return db
end

# Compatibility shims until users upgrade to new NNlib format
function conv!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T}; pad=0, stride=1, flipkernel=0, dilation=1, kwargs...) where {T<:CUDNNFloat}
cdims = DenseConvDims(x, w; padding=pad, stride=stride, flipkernel=(flipkernel!=0), dilation=dilation)
return conv!(y, x, w, cdims; kwargs...)
end

function ∇conv_filter!(dw::DenseCuArray{T}, dy::DenseCuArray{T}, x::DenseCuArray{T}; pad=0, stride=1, flipkernel=0, dilation=1, kwargs...) where {T<:CUDNNFloat}
cdims = DenseConvDims(x, dw; padding=pad, stride=stride, flipkernel=(flipkernel!=0), dilation=dilation)
# NOTE!!! This compat shim re-arranges the argument order!
return ∇conv_filter!(dw, x, dy, cdims; kwargs...)
end


function cudnnConvolutionForward(y::DenseCuArray{T,N}, x::DenseCuArray{T,N}, w::DenseCuArray{T,N},
cdims::DenseConvDims; algo=0, alpha=1, beta=0) where {T,N}
# @warn "`cudnnConvolutionForward(y,x,w,c::DenseConvDims)` is deprecated, please use one of the methods in `@doc cudnnConvolutionForward!`." maxlog=1
cudnnConvolutionForward!(y, w, x; alpha, beta, padding=nnlibPadding(cdims), stride=NNlib.stride(cdims), dilation=NNlib.dilation(cdims), mode=(NNlib.flipkernel(cdims) ? CUDNN_CROSS_CORRELATION : CUDNN_CONVOLUTION))
end

function cudnnConvolutionBiasActivationForward(y::DenseCuArray{T,N}, x::DenseCuArray{T,N}, w::DenseCuArray{T,N}, z::DenseCuArray{T,N}, bias::DenseCuArray{T,N},
cdims::DenseConvDims; algo=0, alpha1=1, alpha2=1,
activationMode=CUDNN_ACTIVATION_RELU, activationCoeff=0.0, activationReluNanOpt=CUDNN_NOT_PROPAGATE_NAN) where {T,N}
# @warn "`cudnnConvolutionBiasActivationForward` is deprecated, please use one of the methods in `@doc cudnnConvolutionForward!`." maxlog=1
cudnnConvolutionForward!(y, w, x; bias, activation=activationMode, z, alpha=alpha1, beta=alpha2, padding=nnlibPadding(cdims), stride=NNlib.stride(cdims), dilation=NNlib.dilation(cdims), mode=(NNlib.flipkernel(cdims) ? CUDNN_CROSS_CORRELATION : CUDNN_CONVOLUTION))
end
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