TastyPancakes/Flux.jl
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Merge pull request #600 from FluxML/tb/cuptr

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Adapt to the new CUDAdrv.CuPtr pointer type.
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Tim Besard 2019-03-22 14:37:55 +01:00 committed by GitHub
commit f2dc57f938
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3 changed files with 40 additions and 39 deletions
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9
src/cuda/cuda.jl
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@ -1,17 +1,18 @@
module CUDA module CUDA
using ..CuArrays using ..CuArrays
import ..CuArrays.CUDAdrv: CuPtr, CU_NULL
using Pkg.TOML using Pkg.TOML
function version_check() function version_check()
minor_version = 9 major_version = 1
project = joinpath(dirname(pathof(CuArrays)), "../Project.toml") project = joinpath(dirname(pathof(CuArrays)), "../Project.toml")
project = TOML.parse(String(read(project))) project = TOML.parse(String(read(project)))
version = VersionNumber(get(project, "version", "0.0.0")) version = VersionNumber(get(project, "version", "0.0.0"))
if !(version.major == 0 && version.minor == minor_version) if version.major != major_version
@warn """ @warn """
Flux is only supported with CuArrays v0.$minor_version. Flux is only supported with CuArrays v$major_version.x.
Try running `] pin CuArrays@0.$minor_version`. Try running `] pin CuArrays@$major_version`.
""" """
end end
end end

36
src/cuda/cudnn.jl
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@ -17,7 +17,7 @@ function DropoutDesc(ρ::Real; seed::Integer=0)
@check ccall((:cudnnDropoutGetStatesSize,libcudnn),cudnnStatus_t,(Ptr{Nothing},Ptr{Csize_t}),handle(),s) @check ccall((:cudnnDropoutGetStatesSize,libcudnn),cudnnStatus_t,(Ptr{Nothing},Ptr{Csize_t}),handle(),s)
states = CuArray{UInt8}(undef, s[]) # TODO: can we drop this when ρ=0? states = CuArray{UInt8}(undef, s[]) # TODO: can we drop this when ρ=0?
desc = DropoutDesc(d[], states) desc = DropoutDesc(d[], states)
@check ccall((:cudnnSetDropoutDescriptor,libcudnn),cudnnStatus_t,(Ptr{Nothing},Ptr{Nothing},Cfloat,Ptr{Nothing},Csize_t,Culonglong), @check ccall((:cudnnSetDropoutDescriptor,libcudnn),cudnnStatus_t,(Ptr{Nothing},Ptr{Nothing},Cfloat,CuPtr{Nothing},Csize_t,Culonglong),
desc,handle(),ρ,states,length(states),seed) desc,handle(),ρ,states,length(states),seed)
finalizer(desc) do x finalizer(desc) do x
@check ccall((:cudnnDestroyDropoutDescriptor,libcudnn),cudnnStatus_t,(Ptr{Nothing},),x) @check ccall((:cudnnDestroyDropoutDescriptor,libcudnn),cudnnStatus_t,(Ptr{Nothing},),x)
@ -79,18 +79,18 @@ function cudnnBNForward!(y::CuArray{T}, g::CuArray{T}, b::CuArray{T}, x::CuArray
mean = zeros(CuArray{T}, dims...) mean = zeros(CuArray{T}, dims...)
ivar = ones(CuArray{T}, dims...) ivar = ones(CuArray{T}, dims...)
else else
mean = C_NULL mean = CU_NULL
ivar = C_NULL ivar = CU_NULL
end end
@check ccall((:cudnnBatchNormalizationForwardTraining, libcudnn), cudnnStatus_t, @check ccall((:cudnnBatchNormalizationForwardTraining, libcudnn), cudnnStatus_t,
(cudnnHandle_t,cudnnBatchNormMode_t, (cudnnHandle_t,cudnnBatchNormMode_t,
Ptr{T}, Ptr{T}, Ptr{T}, Ptr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{T}, Ptr{Nothing}, CuPtr{T}, CuPtr{T},
Cdouble, Ptr{T}, Ptr{T}, Cdouble, CuPtr{T}, CuPtr{T},
Cdouble, Ptr{T}, Ptr{T}), Cdouble, CuPtr{T}, CuPtr{T}),
handle(), BATCHNORM_SPATIAL, handle(), BATCHNORM_SPATIAL,
Ref(T(alpha)), Ref(T(beta)), Ref(T(alpha)), Ref(T(beta)),
xd, x, xd, x,
@ -107,10 +107,10 @@ function cudnnBNForward!(y::CuArray{T}, g::CuArray{T}, b::CuArray{T}, x::CuArray
@check ccall((:cudnnBatchNormalizationForwardInference, libcudnn), cudnnStatus_t, @check ccall((:cudnnBatchNormalizationForwardInference, libcudnn), cudnnStatus_t,
(Ptr{cudnnHandle_t},cudnnBatchNormMode_t, (Ptr{cudnnHandle_t},cudnnBatchNormMode_t,
Ptr{T}, Ptr{T}, Ptr{T}, Ptr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{T}, Ptr{Nothing}, CuPtr{T}, CuPtr{T},
Ptr{T}, Ptr{T}, CuPtr{T}, CuPtr{T},
Cdouble), Cdouble),
handle(), BATCHNORM_SPATIAL, handle(), BATCHNORM_SPATIAL,
Ref(T(alpha)), Ref(T(beta)), Ref(T(alpha)), Ref(T(beta)),
@ -159,7 +159,7 @@ function cudnnBNBackward!(dg::CuArray{T}, g::CuArray{T}, db::CuArray{T},
mean, ivar = cache.mean, cache.ivar mean, ivar = cache.mean, cache.ivar
info("mean and ivar are fetched from the cache") info("mean and ivar are fetched from the cache")
else else
mean, ivar = C_NULL, C_NULL mean, ivar = CU_NULL, CU_NULL
end end
if eps < BATCHNORM_MIN_EPS if eps < BATCHNORM_MIN_EPS
@ -170,11 +170,11 @@ function cudnnBNBackward!(dg::CuArray{T}, g::CuArray{T}, db::CuArray{T},
(cudnnHandle_t,cudnnBatchNormMode_t, (cudnnHandle_t,cudnnBatchNormMode_t,
Ptr{T}, Ptr{T}, Ptr{T}, Ptr{T},
Ptr{T}, Ptr{T}, Ptr{T}, Ptr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{T}, Ptr{T}, Ptr{Nothing}, CuPtr{T}, CuPtr{T}, CuPtr{T},
Cdouble, Ptr{T}, Ptr{T}), Cdouble, CuPtr{T}, CuPtr{T}),
handle(), BATCHNORM_SPATIAL, handle(), BATCHNORM_SPATIAL,
Ref(T(alpha)), Ref(T(beta)), Ref(T(alpha)), Ref(T(beta)),
Ref(T(dalpha)), Ref(T(dbeta)), Ref(T(dalpha)), Ref(T(dbeta)),

34
src/cuda/curnn.jl
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@ -101,18 +101,18 @@ function cudnnRNNForward(rnn::RNNDesc{T}, seqlen, xd, x, hd, h, cd, c, wd, w, yd
if reserve == nothing if reserve == nothing
@check ccall((:cudnnRNNForwardInference, libcudnn), cudnnStatus_t, @check ccall((:cudnnRNNForwardInference, libcudnn), cudnnStatus_t,
(Ptr{Nothing}, Ptr{Nothing}, Cint, (Ptr{Nothing}, Ptr{Nothing}, Cint,
Ptr{Ptr{Nothing}}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Ptr{Nothing}}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Ptr{Nothing}}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Ptr{Nothing}}, CuPtr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Csize_t), CuPtr{Nothing}, Csize_t),
handle(), rnn, seqlen, handle(), rnn, seqlen,
xd, x, hd, h, cd, c, wd, w, yd, y, hod, ho, cod, co, xd, x, hd, h, cd, c, wd, w, yd, y, hod, ho, cod, co,
workspace, length(workspace)) workspace, length(workspace))
else else
@check ccall((:cudnnRNNForwardTraining, libcudnn), cudnnStatus_t, @check ccall((:cudnnRNNForwardTraining, libcudnn), cudnnStatus_t,
(Ptr{Nothing}, Ptr{Nothing}, Cint, (Ptr{Nothing}, Ptr{Nothing}, Cint,
Ptr{Ptr{Nothing}}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Ptr{Nothing}}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Ptr{Nothing}}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Ptr{Nothing}}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Csize_t, Ptr{Nothing}, Csize_t), CuPtr{Nothing}, Csize_t, CuPtr{Nothing}, Csize_t),
handle(), rnn, seqlen, handle(), rnn, seqlen,
xd, x, hd, h, cd, c, wd, w, yd, y, hod, ho, cod, co, xd, x, hd, h, cd, c, wd, w, yd, y, hod, ho, cod, co,
workspace, length(workspace), reserve, length(reserve)) workspace, length(workspace), reserve, length(reserve))
@ -121,7 +121,7 @@ end
xDesc(x) = [TensorDesc(eltype(x), (1, size(x, 1), size(x, 2)))] xDesc(x) = [TensorDesc(eltype(x), (1, size(x, 1), size(x, 2)))]
hDesc(h::Nothing) = C_NULL, C_NULL hDesc(h::Nothing) = C_NULL, CU_NULL
hDesc(x::Integer) = (@assert x == 0; hDesc(nothing)) hDesc(x::Integer) = (@assert x == 0; hDesc(nothing))
function hDesc(h::CuArray) function hDesc(h::CuArray)
TensorDesc(eltype(h), (size(h, 1), size(h, 2), 1)), h TensorDesc(eltype(h), (size(h, 1), size(h, 2), 1)), h
@ -169,10 +169,10 @@ function cudnnRNNBackwardData(rnn::RNNDesc{T}, seqlen, yd, y, dyd, dy, dhod, dho
wd, w, hd, h, cd, c, dxd, dx, dhd, dh, dcd, dc, ws, rs) where T wd, w, hd, h, cd, c, dxd, dx, dhd, dh, dcd, dc, ws, rs) where T
@check ccall((:cudnnRNNBackwardData,libcudnn),cudnnStatus_t, @check ccall((:cudnnRNNBackwardData,libcudnn),cudnnStatus_t,
(Ptr{Nothing}, Ptr{Nothing}, Cint, (Ptr{Nothing}, Ptr{Nothing}, Cint,
Ptr{Ptr{Nothing}}, Ptr{T}, Ptr{Ptr{Nothing}}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Ptr{Nothing}}, CuPtr{T}, Ptr{Ptr{Nothing}}, CuPtr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing},
Ptr{T}, Ptr{Ptr{Nothing}}, Ptr{T}, Ptr{Nothing}, Ptr{T}, Ptr{Nothing}, Ptr{T}, CuPtr{T}, Ptr{Ptr{Nothing}}, CuPtr{T}, Ptr{Nothing}, CuPtr{T}, Ptr{Nothing}, CuPtr{T},
Ptr{Nothing}, Csize_t, Ptr{Nothing}, Csize_t), CuPtr{Nothing}, Csize_t, CuPtr{Nothing}, Csize_t),
handle(), rnn, seqlen, yd, y, dyd, dy, dhod, dho, dcod, dco, handle(), rnn, seqlen, yd, y, dyd, dy, dhod, dho, dcod, dco,
wd, w, hd, h, cd, c, dxd, dx, dhd, dh, dcd, dc, ws, length(ws), rs, length(rs)) wd, w, hd, h, cd, c, dxd, dx, dhd, dh, dcd, dc, ws, length(ws), rs, length(rs))
end end
@ -199,12 +199,12 @@ function cudnnRNNBackwardWeights(rnn::RNNDesc{T}, seqlen, xd, x, hd, h, yd, y, d
workspace, reserve) where T workspace, reserve) where T
@check ccall((:cudnnRNNBackwardWeights,libcudnn), cudnnStatus_t, @check ccall((:cudnnRNNBackwardWeights,libcudnn), cudnnStatus_t,
(Ptr{Nothing}, Ptr{Nothing}, Cint, # handle, rnnDesc, seqLength (Ptr{Nothing}, Ptr{Nothing}, Cint, # handle, rnnDesc, seqLength
Ptr{Ptr{Nothing}}, Ptr{T}, #x Ptr{Ptr{Nothing}}, CuPtr{T}, #x
Ptr{Nothing}, Ptr{T}, #hx Ptr{Nothing}, CuPtr{T}, #hx
Ptr{Ptr{Nothing}}, Ptr{T}, #y Ptr{Ptr{Nothing}}, CuPtr{T}, #y
Ptr{Nothing}, Csize_t, #ws CuPtr{Nothing}, Csize_t, #ws
Ptr{Nothing}, Ptr{T}, #dw Ptr{Nothing}, CuPtr{T}, #dw
Ptr{Nothing}, Csize_t), #rs CuPtr{Nothing}, Csize_t), #rs
handle(), rnn, seqlen, xd, x, hd, h, yd, y, handle(), rnn, seqlen, xd, x, hd, h, yd, y,
workspace, length(workspace), dwd, dw, reserve, length(reserve)) workspace, length(workspace), dwd, dw, reserve, length(reserve))
end end