seperate number type
This commit is contained in:
Mike J Innes
parent
282889970d
commit
79e4e25fea
@ -27,8 +27,8 @@ function train!(loss, data, opt; cb = () -> ())
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opt = runall(opt)
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@progress for d in data
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l = loss(d...)
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isinf(l.data[]) && error("Loss is Inf")
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isnan(l.data[]) && error("Loss is NaN")
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isinf(l) && error("Loss is Inf")
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isnan(l) && error("Loss is NaN")
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back!(l)
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opt()
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cb() == :stop && break
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@ -27,22 +27,24 @@ mutable struct Tracked{T}
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Tracked{T}(f::Call, data::T, grad::T) where T = new(0, f, data, grad)
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end
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Tracked(f::Call, x) = Tracked{typeof(x)}(f, x)
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track(f::Call, x) = Tracked(f, x)
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track(f::Call) = track(f, f())
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track(f, xs...) = track(Call(f, xs...))
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istracked(x::Tracked) = true
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isleaf(x::Tracked) = x.f == Call(nothing)
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data(x::Tracked) = x.data
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grad(x::Tracked) = x.grad
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include("back.jl")
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include("scalar.jl")
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include("array.jl")
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include("numeric.jl")
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param(x::Number) = TrackedArray(fill(0))
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Base.isless(x::TrackedScalar, y) = isless(x.data[], y)
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Base.isless(x, y::TrackedScalar) = isless(x, y.data[])
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Base.isless(x::TrackedScalar, y::TrackedScalar) = isless(x.data[], y.data[])
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back!(x::TrackedScalar) = back!(x, 1)
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param(xs::AbstractArray) = TrackedArray(map(x -> AbstractFloat(x), xs))
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param(x::Number) = TrackedNumber(float(x))
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param(xs::AbstractArray) = TrackedArray(float.(xs))
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using DataFlow
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using DataFlow: inputnode, constant
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@ -8,19 +8,18 @@ end
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tracker(x::TrackedArray) = x.tracker
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TrackedScalar{T,A} = TrackedArray{T,0,A}
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TrackedVector{T,A} = TrackedArray{T,1,A}
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TrackedMatrix{T,A} = TrackedArray{T,2,A}
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TrackedVecOrMat{T,A} = Union{TrackedVector{T,A},TrackedMatrix{T,A}}
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track(c::Call, x::AbstractArray) = TrackedArray(c, x)
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TrackedArray(c::Call, x::A) where A <: AbstractArray =
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TrackedArray{eltype(A),ndims(A),A}(Tracked{A}(c, x), x)
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TrackedArray(c::Call, x::A, Δ::A) where A <: AbstractArray =
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TrackedArray{eltype(A),ndims(A),A}(Tracked{A}(c, x, Δ), x, Δ)
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TrackedArray(c::Call) = TrackedArray(c, c())
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TrackedArray(x::AbstractArray) = TrackedArray(Call(nothing), x, zeros(x))
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Base.show(io::IO, ::Type{TrackedArray{T,N,A}}) where {T,N,A<:AbstractArray{T,N}} =
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@ -40,6 +39,8 @@ end
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Base.setindex!(xs::TrackedArray, v, i...) =
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error("Can't differentiate `setindex!`")
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back!(::TrackedArray) = error("Use back!(x, Δ)")
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# Fallthrough methods
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for f in :[Base.size, Base.ndims].args
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@ -51,57 +52,47 @@ Base.similar(x::TrackedArray, dims::Union{AbstractUnitRange,Integer}...) =
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Base.similar(x::TrackedArray, T::Type) = similar(data(x), T)
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value(x) = data(x)
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value(x::TrackedScalar) = data(x)[]
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Base.:(==)(x::TrackedArray, y) = value(x) == y
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Base.:(==)(y, x::TrackedArray) = y == value(x)
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Base.:(==)(x::TrackedArray, y::TrackedArray) = value(x) == value(y)
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Base.:(==)(x::TrackedArray, y) = data(x) == y
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Base.:(==)(y, x::TrackedArray) = y == data(x)
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Base.:(==)(x::TrackedArray, y::TrackedArray) = data(x) == data(y)
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# Array Stdlib
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toarray(xs::AbstractArray, ys::AbstractArray) = ys
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toarray(xs::AbstractArray, y) = similar(xs, typeof(y), ()) .= y
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unarray(xs) = xs
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unarray(xs::AbstractArray{T,0} where T) = xs[]
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Base.getindex(xs::TrackedArray, i...) =
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TrackedArray(Call(getindex, xs, i...), toarray(xs.data, xs.data[i...]))
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Base.getindex(xs::TrackedArray, i...) = track(getindex, xs, i...)
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function back(::typeof(getindex), Δ, xs::TrackedArray, i...)
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Δ′ = zeros(xs.data)
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Δ′[i...] = unarray(Δ)
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Δ′[i...] = Δ
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@back(xs, Δ′)
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end
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Base.:-(xs::TrackedArray) = TrackedArray(Call(-, xs))
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Base.:-(xs::TrackedArray) = track(-, xs)
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back(::typeof(-), Δ, xs::TrackedArray) = back(xs, -Δ)
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Base.transpose(xs::TrackedArray) = TrackedArray(Call(transpose, xs))
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Base.ctranspose(xs::TrackedArray) = TrackedArray(Call(ctranspose, xs))
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Base.transpose(xs::TrackedArray) = track(transpose, xs)
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Base.ctranspose(xs::TrackedArray) = track(ctranspose, xs)
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back(::typeof(transpose), Δ, xs) = @back(xs, trim(xs, Δ.'))
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back(::typeof(ctranspose), Δ, xs) = @back(xs, trim(xs, Δ'))
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Base.repmat(x::TrackedVecOrMat, a::Integer...) = TrackedArray(Call(repmat, x, a...))
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Base.repmat(x::TrackedVecOrMat, a::Int64...) = TrackedArray(Call(repmat, x, a...))
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Base.repmat(x::TrackedVecOrMat, a::Integer...) = track(repmat, x, a...)
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Base.repmat(x::TrackedVecOrMat, a::Int64...) = track(repmat, x, a...)
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Base.vcat(a::TrackedVector, b::TrackedVector) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::TrackedVector, b::TrackedVector...) = TrackedArray(Call(vcat, a, b...))
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Base.vcat(a::TrackedVector, b::AbstractVector) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::AbstractVector, b::TrackedVector) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::TrackedVector, b::TrackedVector) = track(vcat, a, b)
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Base.vcat(a::TrackedVector, b::TrackedVector...) = track(vcat, a, b...)
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Base.vcat(a::TrackedVector, b::AbstractVector) = track(vcat, a, b)
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Base.vcat(a::AbstractVector, b::TrackedVector) = track(vcat, a, b)
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Base.vcat(a::TrackedVecOrMat, b::TrackedVecOrMat) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::TrackedVecOrMat, b::TrackedVecOrMat...) = TrackedArray(Call(vcat, a, b...))
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Base.vcat(a::TrackedVecOrMat, b::AbstractVecOrMat) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::AbstractVecOrMat, b::TrackedVecOrMat) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::TrackedVecOrMat, b::TrackedVecOrMat) = track(vcat, a, b)
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Base.vcat(a::TrackedVecOrMat, b::TrackedVecOrMat...) = track(vcat, a, b...)
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Base.vcat(a::TrackedVecOrMat, b::AbstractVecOrMat) = track(vcat, a, b)
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Base.vcat(a::AbstractVecOrMat, b::TrackedVecOrMat) = track(vcat, a, b)
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Base.vcat(a::TrackedMatrix, b::TrackedMatrix) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::TrackedMatrix, b::TrackedMatrix...) = TrackedArray(Call(vcat, a, b...))
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Base.vcat(a::TrackedMatrix, b::AbstractMatrix) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::AbstractMatrix, b::TrackedMatrix) = TrackedArray(Call(vcat, a, b))
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Base.vcat(a::TrackedMatrix, b::TrackedMatrix) = track(vcat, a, b)
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Base.vcat(a::TrackedMatrix, b::TrackedMatrix...) = track(vcat, a, b...)
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Base.vcat(a::TrackedMatrix, b::AbstractMatrix) = track(vcat, a, b)
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Base.vcat(a::AbstractMatrix, b::TrackedMatrix) = track(vcat, a, b)
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function back(::typeof(vcat), Δ, xs...)
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i = Base.tail(map(_ -> :, size(Δ)))
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@ -113,27 +104,27 @@ function back(::typeof(vcat), Δ, xs...)
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end
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Base.reshape(xs::TrackedArray, dims::Union{Colon,Int64}...) =
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TrackedArray(Call(reshape, xs, dims...))
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track(reshape, xs, dims...)
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back(::typeof(reshape), Δ, xs::TrackedArray, _...) =
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back(xs, reshape(Δ, size(xs)))
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# Reductions
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Base.sum(xs::TrackedArray, dim) = TrackedArray(Call(sum, xs, dim))
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Base.sum(xs::TrackedArray) = TrackedArray(Call(sum, xs), toarray(xs.data, sum(xs.data)))
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Base.sum(xs::TrackedArray, dim) = track(sum, xs, dim)
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Base.sum(xs::TrackedArray) = track(sum, xs)
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back(::typeof(sum), Δ, xs::TrackedArray, dim...) = back(xs, similar(xs.data) .= Δ)
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Base.maximum(xs::TrackedArray, args...) = maximum(xs.data, args...)
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Base.findfirst(xs::TrackedArray, args...) = findfirst(xs.data, args...)
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Base.mean(xs::TrackedArray) = TrackedArray(Call(mean, xs), toarray(xs.data, mean(xs.data)))
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Base.mean(xs::TrackedArray, region) = TrackedArray(Call(mean, xs, region))
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Base.mean(xs::TrackedArray) = track(mean, xs)
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Base.mean(xs::TrackedArray, region) = track(mean, xs, region)
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LinAlg.dot(xs::TrackedVector, ys::TrackedVector) = TrackedArray(Call(dot, xs, ys), toarray(xs.data, dot(data(xs), data(ys))))
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LinAlg.dot(xs::AbstractVector, ys::TrackedVector) = TrackedArray(Call(dot, xs, ys), toarray(xs.data, dot(data(xs), data(ys))))
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LinAlg.dot(xs::TrackedVector, ys::AbstractVector) = TrackedArray(Call(dot, xs, ys), toarray(xs.data, dot(data(xs), data(ys))))
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LinAlg.dot(xs::TrackedVector, ys::TrackedVector) = track(dot, xs, ys)
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LinAlg.dot(xs::AbstractVector, ys::TrackedVector) = track(dot, xs, ys)
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LinAlg.dot(xs::TrackedVector, ys::AbstractVector) = track(dot, xs, ys)
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function back(::typeof(dot), Δ, xs, ys)
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@back(xs, Δ.*ys)
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@ -152,23 +143,23 @@ back(::typeof(mean), Δ, xs::TrackedArray, region) =
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# BLAS
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Base.diagm(x::TrackedVector) = TrackedArray(Call(diagm, x))
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Base.diagm(x::TrackedVector) = track(diagm, x)
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back(::typeof(diagm), Δ, x) = @back(x, diag(Δ))
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for f in :[*, Ac_mul_B, A_mul_Bc].args
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@eval begin
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import Base.$f
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$f(a::TrackedMatrix, b::TrackedMatrix) = TrackedArray(Call($f, a, b))
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$f(a::TrackedMatrix, b::AbstractMatrix) = TrackedArray(Call($f, a, b))
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$f(a::AbstractMatrix, b::TrackedMatrix) = TrackedArray(Call($f, a, b))
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$f(a::TrackedMatrix, b::TrackedMatrix) = track($f, a, b)
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$f(a::TrackedMatrix, b::AbstractMatrix) = track($f, a, b)
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$f(a::AbstractMatrix, b::TrackedMatrix) = track($f, a, b)
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$f(a::TrackedMatrix, b::TrackedVector) = TrackedArray(Call($f, a, b))
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$f(a::TrackedMatrix, b::AbstractVector) = TrackedArray(Call($f, a, b))
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$f(a::AbstractMatrix, b::TrackedVector) = TrackedArray(Call($f, a, b))
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$f(a::TrackedMatrix, b::TrackedVector) = track($f, a, b)
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$f(a::TrackedMatrix, b::AbstractVector) = track($f, a, b)
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$f(a::AbstractMatrix, b::TrackedVector) = track($f, a, b)
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$f(a::TrackedVector, b::TrackedVector) = TrackedArray(Call($f, a, b))
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$f(a::TrackedVector, b::AbstractVector) = TrackedArray(Call($f, a, b))
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$f(a::AbstractVector, b::TrackedVector) = TrackedArray(Call($f, a, b))
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$f(a::TrackedVector, b::TrackedVector) = track($f, a, b)
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$f(a::TrackedVector, b::AbstractVector) = track($f, a, b)
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$f(a::AbstractVector, b::TrackedVector) = track($f, a, b)
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end
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end
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@ -202,11 +193,11 @@ end
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using NNlib
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import NNlib: softmax, ∇softmax, logsoftmax, ∇logsoftmax, conv2d, pool
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softmax(xs::TrackedArray) = TrackedArray(Call(softmax, xs))
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softmax(xs::TrackedArray) = track(softmax, xs)
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back(::typeof(softmax), Δ, xs) = @back(xs, ∇softmax(Δ, data(xs)))
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logsoftmax(xs::TrackedArray) = TrackedArray(Call(logsoftmax, xs))
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logsoftmax(xs::TrackedArray) = track(logsoftmax, xs)
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back(::typeof(logsoftmax), Δ, xs) = @back(xs, ∇logsoftmax(Δ, data(xs)))
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@ -214,11 +205,11 @@ back(::typeof(logsoftmax), Δ, xs) = @back(xs, ∇logsoftmax(Δ, data(xs)))
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_conv2d(x, w, stride, pad) = conv2d(x, w, stride = stride, padding = pad)
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conv2d(x::TrackedArray{<:Any,4}, w::TrackedArray{<:Any,4}; stride = 1, padding = 0) =
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TrackedArray(Call(_conv2d, x, w, stride, padding))
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track(_conv2d, x, w, stride, padding)
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conv2d(x::AbstractArray{<:Any,4}, w::TrackedArray{<:Any,4}; stride = 1, padding = 0) =
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TrackedArray(Call(_conv2d, x, w, stride, padding))
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track(_conv2d, x, w, stride, padding)
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conv2d(x::TrackedArray{<:Any,4}, w::AbstractArray{<:Any,4}; stride = 1, padding = 0) =
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TrackedArray(Call(_conv2d, x, w, stride, padding))
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track(_conv2d, x, w, stride, padding)
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function back(::typeof(_conv2d), Δ, x, w, stride, pad)
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@back(x, NNlib.conv2d_grad_x(data(x), data(w), Δ; stride = stride, padding = pad))
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@ -228,7 +219,7 @@ end
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_pool(x, k, pad, mode) = pool(x, window = k, mode = mode, padding = pad)
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pool(x::TrackedArray{<:Any,4}; window = 2, mode = 0, padding = 0) =
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TrackedArray(Call(_pool, x, window, padding, mode))
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track(_pool, x, window, padding, mode)
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back_(::typeof(_pool), y, Δ, x, k, pad, mode) =
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back(x, NNlib.pool_grad(data(x), y, Δ, window=k, mode=mode, padding=pad))
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@ -246,23 +237,24 @@ end
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dualify(xs, n) = xs
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dualify(xs::TrackedArray, ps) = map(x -> Dual(x, ps), data(xs))
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dualify(xs::TrackedNumber, ps) = Dual(data(xs), ps)
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function tracked_broadcast(f, args::Vararg{Any,N}) where N
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dargs = map((x,i) -> dualify(x, ntuple(j -> i==j, Val{N})), args, ntuple(identity, Val{N}))
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out = broadcast(f, dargs...)
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eltype(out) <: Dual || return out
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# TrackedArray(Call(Broadcasted(f, broadcast(f, dargs...)), args...))
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# Works around a 0.6 type inference issue
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b = Broadcasted(f, out)
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TrackedArray(Call(b, args...), b())
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track(Call(b, args...), b())
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end
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trim(x, Δ) = reshape(Δ, ntuple(i -> size(Δ, i), Val{ndims(x)}))
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unbroadcast(x, Δ) =
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unbroadcast(x::AbstractArray, Δ) =
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size(x) == size(Δ) ? Δ :
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trim(x, sum(Δ, filter(n -> size(x, n) == 1, 1:ndims(Δ))))
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unbroadcast(x::Number, Δ) = sum(Δ)
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function getpartial(Δ, x, i)
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@inbounds p = getindex(partials(x), i)
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return Δ * p
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@ -19,10 +19,13 @@ back_(f, y, args...) = back(f, args...)
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back_(c::Call, y, Δ) = back_(c.func, y, Δ, c.args...)
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back_(::Call{Void}, y, Δ) = nothing
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accum!(x::Tracked, Δ) = (x.grad += Δ)
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accum!(x::Tracked{<:AbstractArray}, Δ) = (x.grad .+= Δ)
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function back(x::Tracked, Δ)
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ref = x.ref -= 1
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if isdefined(x, :grad)
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x.grad .+= Δ
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accum!(x, Δ)
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ref == 0 && back_(x.f, x.data, x.grad)
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else
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ref == 0 && back_(x.f, x.data, Δ)
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@ -31,6 +34,7 @@ function back(x::Tracked, Δ)
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end
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back(x, Δ) = back(tracker(x), Δ)
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back(x::Void, Δ) = error("Can't backpropagate through `nothing`")
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macro back(x, Δ)
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quote
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63
src/tracker/scalar.jl
Normal file
63
src/tracker/scalar.jl
Normal file
@ -0,0 +1,63 @@
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struct TrackedNumber{T<:Number} <: Number
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tracker::Tracked{T}
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end
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TrackedNumber(x::Number) = TrackedNumber(Tracked(Call(nothing), x))
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tracker(x::TrackedNumber) = x.tracker
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track(f::Call, x::Number) = TrackedNumber(Tracked(f, x))
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back!(x::TrackedNumber) = back!(x, 1)
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function Base.show(io::IO, x::TrackedNumber)
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show(io, data(x))
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print(io, " (tracked)")
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end
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Base.convert(::Type{TrackedNumber{T}}, x::TrackedNumber{T}) where T = x
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Base.convert(::Type{TrackedNumber{T}}, x::TrackedNumber) where T =
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TrackedNumber(Tracked(x.tracker.f, convert(T, x.tracker.data)))
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Base.convert(::Type{TrackedNumber{T}}, x::Number) where T = TrackedNumber(convert(T, x))
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Base.isless(x::TrackedNumber, y::Number) = isless(data(x), y)
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Base.isless(x::Number, y::TrackedNumber) = isless(x, data(y))
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Base.isless(x::TrackedNumber, y::TrackedNumber) = isless(data(x), data(y))
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Base.:(==)(x::TrackedNumber, y::Number) = data(x) == y
|
||||
Base.:(==)(x::Number, y::TrackedNumber) = x == data(y)
|
||||
Base.:(==)(x::TrackedNumber, y::TrackedNumber) = data(x) == data(y)
|
||||
|
||||
for f in :[isinf, isnan].args
|
||||
@eval Base.$f(x::TrackedNumber) = isinf(data(x))
|
||||
end
|
||||
|
||||
Base.promote_rule(::Type{TrackedNumber{S}},::Type{T}) where {S,T} =
|
||||
TrackedNumber{promote_type(S,T)}
|
||||
|
||||
using DiffRules, SpecialFunctions, NaNMath
|
||||
|
||||
for (M, f, arity) in DiffRules.diffrules()
|
||||
arity == 1 || continue
|
||||
@eval begin
|
||||
$M.$f(a::TrackedNumber) = track($M.$f, a)
|
||||
back(::typeof($M.$f), Δ::Number, a::TrackedNumber) =
|
||||
back(a, Δ * $(DiffRules.diffrule(M, f, :(data(a)))))
|
||||
end
|
||||
end
|
||||
|
||||
for (M, f, arity) in DiffRules.diffrules()
|
||||
arity == 2 || continue
|
||||
da, db = DiffRules.diffrule(M, f, :(data(a)), :(data(b)))
|
||||
@eval begin
|
||||
$M.$f(a::TrackedNumber, b::TrackedNumber) = track($M.$f, a, b)
|
||||
$M.$f(a::TrackedNumber, b::Number) = track($M.$f, a, b)
|
||||
$M.$f(a::Number, b::TrackedNumber) = track($M.$f, a, b)
|
||||
function back(::typeof($M.$f), Δ::Number, a::Number, b::Number)
|
||||
@back(a, Δ * $da)
|
||||
@back(b, Δ * $db)
|
||||
end
|
||||
end
|
||||
end
|
||||
Loading…
Reference in New Issue
Block a user