Remove NNlib.

This functionality is now available under the NNlibCUDA subpackage of NNlib.jl

Manifest.toml

@@ -32,12 +32,6 @@ git-tree-sha1 = "215a9aa4a1f23fbd05b92769fdd62559488d70e9"
 uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82"
 version = "0.4.1"
 
-[[ChainRulesCore]]
-deps = ["Compat", "LinearAlgebra", "SparseArrays"]
-git-tree-sha1 = "de4f08843c332d355852721adb1592bce7924da3"
-uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-version = "0.9.29"
-
 [[Compat]]
 deps = ["Base64", "Dates", "DelimitedFiles", "Distributed", "InteractiveUtils", "LibGit2", "Libdl", "LinearAlgebra", "Markdown", "Mmap", "Pkg", "Printf", "REPL", "Random", "SHA", "Serialization", "SharedArrays", "Sockets", "SparseArrays", "Statistics", "Test", "UUIDs", "Unicode"]
 git-tree-sha1 = "919c7f3151e79ff196add81d7f4e45d91bbf420b"
@@ -153,12 +147,6 @@ uuid = "a63ad114-7e13-5084-954f-fe012c677804"
 [[MozillaCACerts_jll]]
 uuid = "14a3606d-f60d-562e-9121-12d972cd8159"
 
-[[NNlib]]
-deps = ["ChainRulesCore", "Compat", "LinearAlgebra", "Pkg", "Requires", "Statistics"]
-git-tree-sha1 = "df42d0816edfc24f5b82a728f46381613c4dff79"
-uuid = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
-version = "0.7.14"
-
 [[NetworkOptions]]
 uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908"
 

Project.toml

@@ -19,7 +19,6 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 Memoize = "c03570c3-d221-55d1-a50c-7939bbd78826"
-NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
@@ -40,7 +39,6 @@ GPUCompiler = "0.10.0"
 LLVM = "3"
 MacroTools = "0.5"
 Memoize = "0.4"
-NNlib = "0.7.7"
 Reexport = "0.2, 1.0"
 Requires = "0.5, 1.0"
 TimerOutputs = "0.5"

lib/cudnn/CUDNN.jl

@@ -12,8 +12,6 @@ using Memoize
 
 using DataStructures
 
-import NNlib
-
 
 # core library
 include("libcudnn_common.jl")
@@ -38,10 +36,6 @@ include("rnn.jl")
 include("multiheadattn.jl")
 include("normalization.jl")
 
-# high-level integrations
-include("nnlib.jl")
-include("batchnorm.jl")
-
 
 function math_mode(mode=CUDA.math_mode())
     if mode == CUDA.PEDANTIC_MATH

lib/cudnn/convolution.jl

@@ -120,24 +120,6 @@ function cudnnConvolutionForwardAD(w, x, bias, z; y, activation, convDesc, wDesc
     return y
 end
 
-
-# Deprecated methods
-using NNlib: DenseConvDims
-
-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
-
-
 # Helper for cudnnConvolutionDescriptor
 function cudnnSetConvolutionDescriptor(
     ptr::cudnnConvolutionDescriptor_t,