https://github.com/fluxml/onehotarrays.jl

Memory efficient one-hot array encodings
https://github.com/fluxml/onehotarrays.jl

Last synced: over 1 year ago
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Memory efficient one-hot array encodings

• Host: GitHub
• URL: https://github.com/fluxml/onehotarrays.jl
• Owner: FluxML
• License: mit
• Created: 2022-03-01T16:18:07.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2024-11-16T17:41:26.000Z (over 1 year ago)
• Last Synced: 2025-02-20T22:05:45.916Z (over 1 year ago)
• Language: Julia
• Homepage: https://fluxml.ai/OneHotArrays.jl/dev/
• Size: 408 KB
• Stars: 18
• Watchers: 11
• Forks: 7
• Open Issues: 15
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# OneHotArrays.jl

[![Documentation](https://img.shields.io/badge/docs-latest-blue.svg)](https://fluxml.ai/OneHotArrays.jl/dev/)

[![Tests](https://github.com/FluxML/OneHotArrays.jl/actions/workflows/CI.yml/badge.svg)](https://github.com/FluxML/OneHotArrays.jl/actions/workflows/CI.yml)

This package provides memory efficient one-hot array encodings.

It was originally part of [Flux.jl](https://github.com/FluxML/Flux.jl).

```julia

julia> using OneHotArrays

julia> m = onehotbatch([10, 20, 30, 10, 10], 10:10:40)

4×5 OneHotMatrix(::Vector{UInt32}) with eltype Bool:

 1  ⋅  ⋅  1  1

 ⋅  1  ⋅  ⋅  ⋅

 ⋅  ⋅  1  ⋅  ⋅

 ⋅  ⋅  ⋅  ⋅  ⋅

julia> dump(m)

OneHotMatrix{UInt32, 4, Vector{UInt32}}

  indices: Array{UInt32}((5,)) UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000001, 0x00000001]

julia> @which rand(100, 4) * m

*(A::AbstractMatrix, B::Union{OneHotArray{var"#s14", L, 1, var"N+1", I}, Base.ReshapedArray{Bool, var"N+1", <:OneHotArray{var"#s14", L, <:Any, <:Any, I}}} where {var"#s14", var"N+1", I}) where L

     @ OneHotArrays ~/.julia/dev/OneHotArrays/src/linalg.jl:7

```