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@paulxshen
paulxshen committed Jan 1, 2025
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2 changes: 1 addition & 1 deletion .gitignore
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.vscode/

temp/
# Files generated by invoking Julia with --code-coverage
*.jl.cov
*.jl.*.cov
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2 changes: 0 additions & 2 deletions .vscode/settings.json
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4 changes: 3 additions & 1 deletion Project.toml
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name = "ArrayPadding"
uuid = "fe5ef43c-4912-423d-9170-4bd5cb6a013a"
authors = ["Paul Shen <pxshen@alumni.stanford.edu>"]
version = "1.0.1"
version = "1.0.2"

[deps]
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"

[compat]
Statistics = "1"
Zygote = "0.6,0.7,1"
julia = "1"
175 changes: 7 additions & 168 deletions README.md
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@@ -1,175 +1,14 @@
# ArrayPadding.jl

Pads arrays of any dimension with various border options including constants, periodic, symmetric, mirror and smooth. Can control amount of padding applied to the left and right side of each dimension. Fully differentiable (compatible with `Zygote.jl` `Flux.jl`)
Pads arrays of any dimension with various border options including constants, periodic, symmetric, mirror and smooth. Can control amount of padding applied to the left and right side of each dimension. Fully differentiable and GPU compatible (plays well with `Zygote.jl` `Flux.jl` `CUDA.jl` )

`pad` eagerly allocates new bigger array while `pad!` mutates original array in place. For `pad!,` the effective border is set back by the padding amount when evaluating various border options. `pad` is AD (automatic differentiation) compatible while `pad!` requires `Zygote.Buffer` for AD (see usage )
`pad` eagerly allocates new bigger array while `pad!` mutates original array in place. `pad!` assumes argument to be the preallocated padded array so the effective border is set back by the padding amount when evaluating various border options. `pad` is AD (automatic differentiation) compatible while `pad!` requires `Zygote.Buffer` for AD (see usage )

```julia
pad(array, border, pad_amount)
pad(array, border, left_pad_amount, right_pad_amount)
pad(array, border, pad_amounts_for_dims)
pad(array, border, left_pad_amount_for_dims, right_pad_amount_for_dims)
See `test/runtests.jl` for examples of usage.

pad!(array, border, pad_amount)
pad!(array, border, left_pad_amount, right_pad_amount)
pad!(array, border, pad_amounts_for_dims)
pad!(array, border, left_pad_amount_for_dims, right_pad_amount_for_dims)
```
Consider starring or sponsoring us if you found this repo helpful. Feel free to request features or contribute PRs :)

## Border options
- any constant value `v`: a b c | v v
- `:periodic`: a b c | a b
- `:replicate`: a b c | c c
- `:symmetric`: a b c | c b
- `:mirror`: a b c | b a
- `:smooth`: a b c | 2c-b (Maintains C1 continuity)

## Usage
```julia
a = collect(reshape(1:16, 4, 4))

@test pad(a, -1, 1) == [
-1 -1 -1 -1 -1 -1
-1 1 5 9 13 -1
-1 2 6 10 14 -1
-1 3 7 11 15 -1
-1 4 8 12 16 -1
-1 -1 -1 -1 -1 -1
]

@test pad!(copy(a), -1, 1) == [
-1 -1 -1 -1
-1 6 10 -1
-1 7 11 -1
-1 -1 -1 -1
]

@test pad(a, -1, 1, 0) == [
-1 -1 -1 -1 -1
-1 1 5 9 13
-1 2 6 10 14
-1 3 7 11 15
-1 4 8 12 16
]

@test pad!(copy(a), -1, 1, 0) == [
-1 -1 -1 -1
-1 6 10 14
-1 7 11 15
-1 8 12 16
]

@test pad(a, -1, (0, 1), (1, 0)) == [
-1 1 5 9 13
-1 2 6 10 14
-1 3 7 11 15
-1 4 8 12 16
-1 -1 -1 -1 -1
]

@test pad!(copy(a), -1, (0, 1), (1, 0)) == [
-1 5 9 13
-1 6 10 14
-1 7 11 15
-1 -1 -1 -1
]

@test pad(a, :periodic, (1, 1), (0, 0)) == [
16 4 8 12 16
13 1 5 9 13
14 2 6 10 14
15 3 7 11 15
16 4 8 12 16
]

@test pad!(copy(a), :periodic, (1, 1), (0, 0)) == [
16 8 12 16
14 6 10 14
15 7 11 15
16 8 12 16
]

@test pad(a, :symmetric, 1) == [
1 1 5 9 13 13
1 1 5 9 13 13
2 2 6 10 14 14
3 3 7 11 15 15
4 4 8 12 16 16
4 4 8 12 16 16
]

@test pad!(copy(a), :symmetric, 1) == [
6 6 10 10
6 6 10 10
7 7 11 11
7 7 11 11
]

@test pad(a, :mirror, 1) == [
6 2 6 10 14 10
5 1 5 9 13 9
6 2 6 10 14 10
7 3 7 11 15 11
8 4 8 12 16 12
7 3 7 11 15 11
]

@test pad!(copy(a), :mirror, 1) == [
11 7 11 7
10 6 10 6
11 7 11 7
10 6 10 6
]

@test pad(a, :replicate, 1) == [
1 1 5 9 13 13
1 1 5 9 13 13
2 2 6 10 14 14
3 3 7 11 15 15
4 4 8 12 16 16
4 4 8 12 16 16
]

@test pad!(copy(a), :replicate, 1) == [
6 6 10 10
6 6 10 10
7 7 11 11
7 7 11 11
]

@test pad(a, :smooth, 1) == [
-4 0 4 8 12 16
-3 1 5 9 13 17
-2 2 6 10 14 18
-1 3 7 11 15 19
0 4 8 12 16 20
1 5 9 13 17 21
]

@test pad!(copy(a), :smooth, 1) == [
1 5 9 13
2 6 10 14
3 7 11 15
4 8 12 16
]

using Zygote
using Zygote: Buffer

@test withgradient(a) do a
a = pad(a, 0, 1)
sum(a)
end == (val=136, grad=([1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0],))

@test withgradient(a) do a
a_ = Buffer(a)
a_ .= a
pad!(a_, 0, 1)
a = copy(a_)
sum(a)
end == (val=34, grad=([0.0 0.0 0.0 0.0; 0.0 1.0 1.0 0.0; 0.0 1.0 1.0 0.0; 0.0 0.0 0.0 0.0],))
```
## Contributing
Consider sponsoring this on Github if you found this repo helpful. Feel free to request features or contribute PRs :)
## Contributors
Paul Shen <pxshen@alumni.stanford.edu>
Paul Shen
<pxshen@alumni.stanford.edu>
Luminescent AI
125 changes: 66 additions & 59 deletions src/alg.jl
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function lr(a::T, b, i, l, r, out=true, ol=0, or=ol) where {T}
d = ndims(a)
sel = (1:d) .== i
function lr(a::S, v, i, l, r) where {S}
N = ndims(a)
T = eltype(a)
ax = axes(a, i)
sel = (1:N) .== i
al = ar = nothing
if l > 0
o = out ? 0 : l + ol
if b == :periodic
I = [j == i ? ((size(a, i)-l+1):size(a, i)) : (:) for j = 1:d]
o = l
if v == :periodic
I = ifelse.(sel, (ax[end-l+1:end],), :)
al = a[I...]
elseif b == :symmetric
I = [j == i ? (l+o:-1:1+o) : (:) for j = 1:d]
elseif v == :symmetric
I = ifelse.(sel, (ax[begin+o+l-1:-1:begin+o],), :)
al = a[I...]
elseif b == :mirror
I = [j == i ? (l+1+o:-1:2+o) : (:) for j = 1:d]
elseif v == :mirror
I = ifelse.(sel, (ax[begin+o+l:-1:begin+1+o],), :)
al = a[I...]
elseif b == :replicate
I = [j == i ? ((1+o):(1+o)) : (:) for j = 1:d]
# s = [j == i ? l : 1 for j = 1:d]
# al = repeat(a[I...], s...)
al = cat(fill(selectdim(a, i, o+1:o+1), l)..., dims=i)
# al = repeat(selectdim(a, i, o+1:o+1), (l .* sel + (1 .- sel))...)
elseif b == :smooth
I = [j == i ? (1+o:1+o) : (:) for j = 1:d]
if size(a, i) == 1
al = a[I...]
elseif v == :replicate
I = ifelse.(sel, (ax[begin+o:begin+o],), :)
al = repeat(a[I...], (sel .* l .+ .!(sel))...)
elseif v == :smooth
# @ignore_derivatives I[i]=(begin+o:begin+o)
# if size(a, i) == 1
# al = a[I...]
# else
# I2 = [j == i ? (2+o:2+o)
# al = 2a[I...] - a[I2...]
# end
elseif isa(v, ReplicateRamp)
# # @ignore_derivatives I[i]=((begin+o):(begin+o))
# @ignore_derivatives I[i]=((begin+o):(begin+o)) : (1:size(a, j)) for j = 1:N]
# v = a[I...]
# Δ = (v.v .- v) / l
# al = v .+ cat([c * Δ for c = l:-1:1]..., dims=i)
else
if isa(a, Buffer)

# al = fillfunc(S)(T(v), (sel .* l .+ .!(sel) .* size(a))...)
al = fill(T(v), (sel .* l .+ .!(sel) .* size(a))...)
else
I2 = [j == i ? (2+o:2+o) : (:) for j = 1:d]
al = 2a[I...] - a[I2...]
al = T(v)
end
elseif isa(b, ReplicateRamp)
# I = [j == i ? ((1+o):(1+o)) : (:) for j = 1:d]
I = [j == i ? ((1+o):(1+o)) : (1:size(a, j)) for j = 1:d]
v = a[I...]
Δ = (b.v .- v) / l
al = v .+ cat([c * Δ for c = l:-1:1]..., dims=i)
else
al = fill(b, Tuple(sel .* l .+ (1 .- sel) .* size(a)))
end
end
if r > 0
o = out ? 0 : r + or
if b == :periodic
I = [j == i ? (1:r) : (:) for j = 1:d]
o = r
if v == :periodic
I = ifelse.(sel, (1:r,), :)
ar = a[I...]
elseif b == :replicate
# I = [j == i ? axes(a, i)[end-o:end-o] : (:) for j = 1:d]
# s = [j == i ? r : 1 for j = 1:d]
# ar = repeat(a[I...], s...)
j = size(a, i) - o
ar = cat(fill(selectdim(a, i, j:j), r)..., dims=i)
# ar = repeat(selectdim(a, i, j:j), (r .* sel + (1 .- sel))...)
elseif b == :symmetric
I = [j == i ? axes(a, i)[end-o:-1:end-r+1-o] : (:) for j = 1:d]
elseif v == :replicate
I = ifelse.(sel, (ax[end-o:end-o],), :)
ar = repeat(a[I...], (sel .* r .+ .!(sel))...)
elseif v == :symmetric
I = ifelse.(sel, (ax[end-o:-1:end-r+1-o],), :)
ar = a[I...]
elseif b == :mirror
I = [j == i ? axes(a, i)[end-1-o:-1:end-r-o] : (:) for j = 1:d]
elseif v == :mirror
I = ifelse.(sel, (ax[end-1-o:-1:end-r-o],), :)
ar = a[I...]
elseif b == :smooth
I = [j == i ? axes(a, i)[end-o:end-o] : (:) for j = 1:d]
if size(a, i) == 1
ar = a[I...]
elseif v == :smooth
# @ignore_derivatives I[i]=ax[end-o:end-o]
# if size(a, i) == 1
# ar = a[I...]
# else
# I2 = [j == i ? ax[end-o-1:end-o-1]
# ar = 2a[I...] - a[I2...]
# end
elseif isa(v, ReplicateRamp)
# @ignore_derivatives I[i]=ax[end-o:end-o]
# v = a[I...]
# Δ = (v.v .- v) / r
# ar = v .+ cat([c * Δ for c = 1:r]..., dims=i)
else
if isa(a, Buffer)
# ar = fillfunc(S)(T(v), (sel .* r .+ .!(sel) .* size(a))...)
ar = fill(T(v), (sel .* r .+ .!(sel) .* size(a))...)
else
I2 = [j == i ? axes(a, i)[end-o-1:end-o-1] : (:) for j = 1:d]
ar = 2a[I...] - a[I2...]
ar = T(v)
end
elseif isa(b, ReplicateRamp)
I = [j == i ? axes(a, i)[end-o:end-o] : (:) for j = 1:d]
v = a[I...]
Δ = (b.v .- v) / r
ar = v .+ cat([c * Δ for c = 1:r]..., dims=i)
else
ar = fill(b, Tuple(sel .* r .+ (1 .- sel) .* size(a)))
end
end
return (al, ar)
end

Base.vec(x::Number, d) = fill(x, d)
Base.vec(v::Union{AbstractVector,Tuple}, d) = v
Base.vec(x::Number, N) = fill(x, N)
Base.vec(v::Union{AbstractVector,Tuple}, N) = v

fillfunc(S) = (args...) -> Base.fill(args...)
5 changes: 3 additions & 2 deletions src/main.jl
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using Statistics
# using Zygote: Buffer, bufferfrom
using Statistics, Zygote
using Zygote: Buffer, @ignore_derivatives

include("types.jl")
include("alg.jl")
include("pad.jl")
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