move zeros to its own file
This commit is contained in:
Dhairya Gandhi
parent
5086c0f4f0
commit
534809ae78
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@ -27,6 +27,7 @@ using CuArrays
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const use_cuda = Ref(false)
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include("utils.jl")
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include("zeros.jl")
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include("onehot.jl")
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include("functor.jl")
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104
src/utils.jl
104
src/utils.jl
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@ -321,110 +321,6 @@ function throttle(f, timeout; leading=true, trailing=false)
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end
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end
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import Base: +, -, *, reshape, size
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import Base.Broadcast: broadcasted, Broadcasted, BroadcastStyle
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"""
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Zeros()
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Zeros(size...)
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Zeros(Type, size...)
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Acts as a stand-in for an array of zeros that can be
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used during training which is ignored by the optimisers.
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Useful to turn bias off for a forward pass of a layer.
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## Examples
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```julia
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julia> Flux.Zeros(3,3)
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3×3 Flux.Zeros{Bool,2}:
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false false false
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false false false
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false false false
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julia> Flux.Zeros(Float32, 3,3)
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3×3 Flux.Zeros{Float32,2}:
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0.0 0.0 0.0
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0.0 0.0 0.0
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0.0 0.0 0.0
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julia> rand(3,3) .+ Flux.Zeros()
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3×3 Array{Float64,2}:
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0.198739 0.490459 0.785386
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0.779074 0.39986 0.66383
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0.854981 0.447292 0.314497
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julia> bias_less_conv = Conv((2,2), 1=>3, bias = Flux.Zeros())
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Conv((2, 2), 1=>3)
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```
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"""
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struct Zeros{T,N} <: AbstractArray{T,N}
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size::Tuple
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end
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Zeros(::Type{T}, sz...) where T = Zeros{T,length(sz)}(sz)
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Zeros(sz::Integer...) = Zeros(Bool, sz...)
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Base.size(xs::Zeros) = xs.size
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Base.axes(xs::Zeros) = Base.OneTo.(size(xs))
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Base.IndexStyle(::Type{<:Zeros}) = IndexLinear()
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Base.getindex(xs::Zeros{T,N}, I::Int) where {T,N} = zero(T)
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Base.getindex(xs::Zeros{T,N}, inds::Union{Base.OneTo, Base.UnitRange}) where {T,N} =
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Zeros(T, inds.stop)
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Base.collect(xs::Zeros{T,N}) where {T,N} = fill(zero(T), size(xs))
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@adjoint reshape(xs::Zeros{T}, dims...) where T =
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reshape(xs, dims...), _ -> nothing
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# Define basic ops
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for f in (:+, :-)
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@eval @inline function $f(a::Union{AbstractArray{<:Number}, Zeros}, b::Zeros)
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@assert size(a) == size(b) throw(DimensionMismatch("dimensions must match"))
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a
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end
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end
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+(a::Zeros, b::AbstractArray) = b + a
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-(a::Zeros, b::AbstractArray) = -b + a
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Base.copy(xs::Zeros{T,N}) where {T,N} = xs
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# Define broadcasting behaviour
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for op in (:+, :-)
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@eval function broadcasted(::typeof($op), a::AbstractArray, b::Zeros)
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bs = Broadcast.broadcast_shape(size(a), size(b))
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size(a) == bs && return a
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sz = similar(a, bs)
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sz .= a
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end
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end
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broadcasted(::typeof(+), a::Zeros, b::AbstractArray) = broadcasted(+, b, a)
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broadcasted(::typeof(-), a::Zeros, b::AbstractArray) = broadcasted(+, -b, a)
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function broadcasted(::typeof(*), a::AbstractArray, b::Zeros)
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Zeros(Broadcast.broadcast_shape(size(a), size(b))...)
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end
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broadcasted(::typeof(*), a::Zeros, b::AbstractArray) = broadcasted(*, b, a)
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for op in (:+, :-, :*)
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@eval broadcasted(::typeof($op), a::Zeros, b::Zeros) = Zeros(Broadcast.broadcast_shape(size(a), size(b))...)
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end
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# Some opportunities to avoid scalar indexing, intermediaries
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broadcasted(::typeof(+), a::AbstractArray, b::Zeros{T,0}) where T = a
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broadcasted(::typeof(+), a::Zeros{T,0}, b::AbstractArray) where T = b
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broadcasted(::typeof(-), a::AbstractArray, b::Zeros{T,0}) where T = a
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broadcasted(::typeof(-), a::Zeros{T,0}, b::AbstractArray) where T = -b
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broadcasted(::typeof(*), a::AbstractArray, b::Zeros{T,0}) where T = zero(a)
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broadcasted(::typeof(*), a::Zeros{T,0}, b::AbstractArray) where T = zero(b)
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broadcasted(::typeof(/), a::Zeros{T,0}, b::AbstractArray) where T = zero(b)
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"""
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@jit ...
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@ -0,0 +1,103 @@
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import Base: +, -, *, reshape, size
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import Base.Broadcast: broadcasted, Broadcasted, BroadcastStyle
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"""
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Zeros()
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Zeros(size...)
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Zeros(Type, size...)
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Acts as a stand-in for an array of zeros that can be
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used during training which is ignored by the optimisers.
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Useful to turn bias off for a forward pass of a layer.
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## Examples
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```julia
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julia> Flux.Zeros(3,3)
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3×3 Flux.Zeros{Bool,2}:
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false false false
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false false false
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false false false
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julia> Flux.Zeros(Float32, 3,3)
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3×3 Flux.Zeros{Float32,2}:
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0.0 0.0 0.0
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0.0 0.0 0.0
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0.0 0.0 0.0
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julia> rand(3,3) .+ Flux.Zeros()
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3×3 Array{Float64,2}:
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0.198739 0.490459 0.785386
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0.779074 0.39986 0.66383
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0.854981 0.447292 0.314497
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julia> bias_less_conv = Conv((2,2), 1=>3, bias = Flux.Zeros())
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Conv((2, 2), 1=>3)
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```
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"""
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struct Zeros{T,N} <: AbstractArray{T,N}
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size::Tuple
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end
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Zeros(::Type{T}, sz...) where T = Zeros{T,length(sz)}(sz)
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Zeros(sz::Integer...) = Zeros(Bool, sz...)
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Base.size(xs::Zeros) = xs.size
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Base.axes(xs::Zeros) = Base.OneTo.(size(xs))
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Base.IndexStyle(::Type{<:Zeros}) = IndexLinear()
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Base.getindex(xs::Zeros{T,N}, I::Int) where {T,N} = zero(T)
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Base.getindex(xs::Zeros{T,N}, inds::Union{Base.OneTo, Base.UnitRange}) where {T,N} =
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Zeros(T, inds.stop)
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Base.collect(xs::Zeros{T,N}) where {T,N} = fill(zero(T), size(xs))
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@adjoint reshape(xs::Zeros{T}, dims...) where T =
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reshape(xs, dims...), _ -> nothing
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# Define basic ops
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for f in (:+, :-)
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@eval @inline function $f(a::Union{AbstractArray{<:Number}, Zeros}, b::Zeros)
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@assert size(a) == size(b) throw(DimensionMismatch("dimensions must match"))
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a
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end
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end
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+(a::Zeros, b::AbstractArray) = b + a
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-(a::Zeros, b::AbstractArray) = -b + a
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Base.copy(xs::Zeros{T,N}) where {T,N} = xs
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# Define broadcasting behaviour
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for op in (:+, :-)
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@eval function broadcasted(::typeof($op), a::AbstractArray, b::Zeros)
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bs = Broadcast.broadcast_shape(size(a), size(b))
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size(a) == bs && return a
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sz = similar(a, bs)
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sz .= a
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end
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end
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broadcasted(::typeof(+), a::Zeros, b::AbstractArray) = broadcasted(+, b, a)
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broadcasted(::typeof(-), a::Zeros, b::AbstractArray) = broadcasted(+, -b, a)
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function broadcasted(::typeof(*), a::AbstractArray, b::Zeros)
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Zeros(Broadcast.broadcast_shape(size(a), size(b))...)
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end
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broadcasted(::typeof(*), a::Zeros, b::AbstractArray) = broadcasted(*, b, a)
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for op in (:+, :-, :*)
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@eval broadcasted(::typeof($op), a::Zeros, b::Zeros) = Zeros(Broadcast.broadcast_shape(size(a), size(b))...)
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end
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# Some opportunities to avoid scalar indexing, intermediaries
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broadcasted(::typeof(+), a::AbstractArray, b::Zeros{T,0}) where T = a
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broadcasted(::typeof(+), a::Zeros{T,0}, b::AbstractArray) where T = b
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broadcasted(::typeof(-), a::AbstractArray, b::Zeros{T,0}) where T = a
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broadcasted(::typeof(-), a::Zeros{T,0}, b::AbstractArray) where T = -b
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broadcasted(::typeof(*), a::AbstractArray, b::Zeros{T,0}) where T = zero(a)
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broadcasted(::typeof(*), a::Zeros{T,0}, b::AbstractArray) where T = zero(b)
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broadcasted(::typeof(/), a::Zeros{T,0}, b::AbstractArray) where T = zero(b)
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