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vincentmolinvincentmolin
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move exports to main source file
1 parent aa86827 commit 9cd9013

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14 files changed

+40
-55
lines changed

14 files changed

+40
-55
lines changed

‎src/NNlib.jl

Lines changed: 40 additions & 8 deletions
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@@ -12,29 +12,61 @@ const Numeric = Union{AbstractArray{<:T}, T} where {T<:Number}
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# Include APIs
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include("dim_helpers.jl")
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export ConvDims, DenseConvDims, PoolDims, DepthwiseConvDims
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is_nnpack_available() = false
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@init @require NNPACK_jll="a6bfbf70-4841-5cb9-aa18-3a8ad3c413ee" begin
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if isdefined(NNPACK_jll, :libnnpack)
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include("nnpack/NNPACK.jl")
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else
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@warn "NNPACK not available for your platform: " *
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"$( Pkg.BinaryPlatforms.platform_name(Pkg.BinaryPlatforms.platform_key_abi()))" *
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"($( Pkg.BinaryPlatforms.triplet(Pkg.BinaryPlatforms.platform_key_abi())))
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You will be able to use only the default Julia NNlib backend"
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end
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if isdefined(NNPACK_jll, :libnnpack)
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include("nnpack/NNPACK.jl")
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else
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@warn "NNPACK not available for your platform: " *
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"$( Pkg.BinaryPlatforms.platform_name(Pkg.BinaryPlatforms.platform_key_abi()))" *
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"($( Pkg.BinaryPlatforms.triplet(Pkg.BinaryPlatforms.platform_key_abi())))
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You will be able to use only the default Julia NNlib backend"
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end
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end
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include("activations.jl")
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for f in ACTIVATIONS
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@eval export $(f)
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end
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export sigmoid, hardsigmoid, logsigmoid, thresholdrelu # Aliases
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include("softmax.jl")
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export softmax, softmax!, ∇softmax, ∇softmax!, logsoftmax,
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logsoftmax!, ∇logsoftmax, ∇logsoftmax!, logsumexp
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include("batched/batchedmul.jl")
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export batched_mul, batched_mul!, ⊠, batched_vec,
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batched_transpose, batched_adjoint
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include("gemm.jl")
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export grid_sample, ∇grid_sample
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include("conv.jl")
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export conv, conv!, ∇conv_data, ∇conv_data!, ∇conv_filter,
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∇conv_filter!, depthwiseconv, depthwiseconv!,
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∇depthwiseconv_data, ∇depthwiseconv_data!,
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∇depthwiseconv_filter, ∇depthwiseconv_filter!
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include("conv_bias_act.jl")
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export conv_bias_act, conv_bias_act!
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include("pooling.jl")
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export maxpool, maxpool!, meanpool, meanpool!,
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∇maxpool, ∇maxpool!, ∇meanpool, ∇meanpool!
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include("padding.jl")
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export pad_constant, pad_repeat, pad_reflect, pad_zeros
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include("upsample.jl")
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export upsample_nearest, ∇upsample_nearest,
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upsample_linear, ∇upsample_linear,
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upsample_bilinear, ∇upsample_bilinear,
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upsample_trilinear, ∇upsample_trilinear,
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pixel_shuffle
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include("gather.jl")
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include("scatter.jl")
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include("utils.jl")

‎src/activations.jl

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Original file line numberDiff line numberDiff line change
@@ -11,13 +11,6 @@ ACTIVATIONS = [
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:tanh_fast, :sigmoid_fast,
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]
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for f in ACTIVATIONS
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@eval export $(f)
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end
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# Aliases
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export sigmoid, hardsigmoid, logsigmoid, thresholdrelu
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# of type float (to allow for integer inputs)
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oftf(x, y) = oftype(float(x), y)
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‎src/batched/batchedmul.jl

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@@ -1,7 +1,3 @@
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export batched_mul, batched_mul!, ⊠, batched_vec
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export batched_transpose, batched_adjoint
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include("./batchedadjtrans.jl")
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using LinearAlgebra: BlasFloat, Transpose, Adjoint, AdjOrTransAbsMat

‎src/conv.jl

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@@ -1,7 +1,3 @@
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export conv, conv!, ∇conv_data, ∇conv_data!, ∇conv_filter, ∇conv_filter!, depthwiseconv,
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depthwiseconv!, ∇depthwiseconv_data, ∇depthwiseconv_data!, ∇depthwiseconv_filter,
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∇depthwiseconv_filter!
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## Convolution API
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#
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# We provide the following generic methods, for 3d, 4d, and 5d tensors, calculating 1d,

‎src/conv_bias_act.jl

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@@ -1,5 +1,3 @@
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export conv_bias_act, conv_bias_act!
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function conv_bias_act(x::AbstractArray{xT,N}, w::AbstractArray{wT,N},
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cdims::ConvDims, b::AbstractArray{bT,N}, σ=identity; kwargs...) where {xT, wT, bT, N}
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y = similar(x, promote_type(xT, wT, bT), output_size(cdims)..., channels_out(cdims), size(x,N))

‎src/dim_helpers/ConvDims.jl

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@@ -1,5 +1,3 @@
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export ConvDims
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"""
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ConvDims
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‎src/dim_helpers/DenseConvDims.jl

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@@ -1,5 +1,3 @@
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export DenseConvDims
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"""
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DenseConvDims
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‎src/dim_helpers/DepthwiseConvDims.jl

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@@ -1,5 +1,3 @@
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export DepthwiseConvDims
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"""
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DepthwiseConvDims
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‎src/dim_helpers/PoolDims.jl

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@@ -1,5 +1,3 @@
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export PoolDims
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"""
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PoolDims(x_size::NTuple{M}, k::Union{NTuple{L, Int}, Int};
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stride=k, padding=0, dilation=1) where {M, L}

‎src/padding.jl

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@@ -1,5 +1,3 @@
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export pad_constant, pad_repeat, pad_reflect, pad_zeros
2-
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"""
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pad_zeros(x, pad::Tuple; [dims])
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pad_zeros(x, pad::Int; [dims])

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