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‎.JuliaFormatter.toml‎

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style = "blue"

‎.github/workflows/Documentation.yml‎

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name: Documentation
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on:
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push:
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branches:
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- main
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tags: '*'
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pull_request:
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jobs:
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build:
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permissions:
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contents: write
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pull-requests: read
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statuses: write
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actions: write
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: julia-actions/setup-julia@v2
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with:
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version: '1'
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arch: x64
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include-all-prereleases: false
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- name: Install dependencies
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run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.update(); Pkg.instantiate()'
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- name: Build and deploy
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env:
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GKSwstype: nul # turn off GR's interactive plotting for notebooks
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # If authenticating with GitHub Actions token
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DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
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run: julia --project=docs/ docs/make.jl

‎.github/workflows/Testing.yaml‎

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strategy:
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matrix:
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version:
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- '1.7'
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- '1.10'
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- '1'
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- 'nightly'
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- os: macOS-latest
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arch: x86
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steps:
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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- uses: actions/checkout@v4
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- uses: julia-actions/setup-julia@v2
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: actions/cache@v1
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- uses: actions/cache@v4
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env:
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cache-name: cache-artifacts
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with:

‎.gitignore‎

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# Prerequisites
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*.d
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# Object files
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*.o
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*.ko
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*.obj
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*.elf
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# Linker output
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*.ilk
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*.map
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*.exp
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# Precompiled Headers
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*.gch
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*.pch
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# Libraries
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*.lib
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*.a
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*.la
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*.lo
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# Shared objects (inc. Windows DLLs)
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*.dll
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*.so
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*.so.*
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*.dylib
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# Executables
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*.exe
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*.out
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*.app
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*.i*86
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*.x86_64
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*.hex
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# Debug files
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*.dSYM/
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*.su
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*.idb
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*.pdb
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# Kernel Module Compile Results
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*.mod*
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*.cmd
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.tmp_versions/
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modules.order
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Module.symvers
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Mkfile.old
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dkms.conf
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# Projects files
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Manifest.toml
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deps/build.log
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deps/deps.jl
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deps/usr/
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deps/tmp-build.jl
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Manifest*
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*.cov
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docs/build

‎NEWS.md‎

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- From v0.6.0, Libtask is implemented by recording all the computing
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to a tape and copying that tape. Before that version, it is based on
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a tricky hack on the Julia internals. You can check the commit
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history of this repo to see the details.
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- From version 0.9.0, the old `TArray` and `TRef` types are completely removed, where
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previously they were only deprecated. Additionally, the internals have been completely
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overhauled, and the public interface more precisely defined. See the docs for more info.

‎Project.toml‎

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version = "0.8.8"
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[deps]
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FunctionWrappers = "069b7b12-0de2-55c6-9aab-29f3d0a68a2e"
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LRUCache = "8ac3fa9e-de4c-5943-b1dc-09c6b5f20637"
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LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
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Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
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MistyClosures = "dbe65cb8-6be2-42dd-bbc5-4196aaced4f4"
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Mooncake = "da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"
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ScopedValues = "7e506255-f358-4e82-b7e4-beb19740aa63"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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[compat]
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FunctionWrappers = "1.1"
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LRUCache = "1.3"
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julia = "1.7"
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Aqua = "0.8.11"
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JuliaFormatter = "1.0.62"
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MistyClosures = "2.0.0"
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Mooncake = "0.4.99"
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ScopedValues = "1.3.0"
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Test = "1"
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julia = "1.10.8"
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[extras]
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BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
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Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
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JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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[targets]
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test = ["Test", "BenchmarkTools"]
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test = ["Aqua", "JuliaFormatter", "Test"]

‎README.md‎

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[![Libtask Testing](https://github.com/TuringLang/Libtask.jl/workflows/Libtask%20Testing/badge.svg)](https://github.com/TuringLang/Libtask.jl/actions?branch=main)
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Tape based task copying in Turing
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## Getting Started
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Resumable and copyable functions in Julia, with optional dynamic scope.
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See the docs for example usage.
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Stack allocated objects are always deep copied:
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```julia
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using Libtask
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function f()
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t = 0
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for _ in 1:10
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produce(t)
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t = 1 + t
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end
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end
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ttask = TapedTask(f)
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@show consume(ttask) # 0
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@show consume(ttask) # 1
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a = copy(ttask)
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@show consume(a) # 2
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@show consume(a) # 3
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@show consume(ttask) # 2
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@show consume(ttask) # 3
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```
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Heap-allocated Array and Ref objects are deep copied by default:
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```julia
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using Libtask
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function f()
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t = [0 1 2]
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for _ in 1:10
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produce(t[1])
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t[1] = 1 + t[1]
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end
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end
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ttask = TapedTask(f)
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@show consume(ttask) # 0
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@show consume(ttask) # 1
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a = copy(ttask)
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@show consume(a) # 2
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@show consume(a) # 3
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@show consume(ttask) # 2
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@show consume(ttask) # 3
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```
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Other heap-allocated objects (e.g., `Dict`) are shallow copied, by default:
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```julia
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using Libtask
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function f()
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t = Dict(1=>10, 2=>20)
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while true
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produce(t[1])
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t[1] = 1 + t[1]
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end
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end
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ttask = TapedTask(f)
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@show consume(ttask) # 10
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@show consume(ttask) # 11
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a = copy(ttask)
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@show consume(a) # 12
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@show consume(a) # 13
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@show consume(ttask) # 14
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@show consume(ttask) # 15
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```
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Notes:
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- The [Turing](https://github.com/TuringLang/Turing.jl) probabilistic
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programming language uses this task copying feature in an efficient
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implementation of the [particle
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filtering](https://en.wikipedia.org/wiki/Particle_filter) sampling
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algorithm for arbitrary order [Markov
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processes](https://en.wikipedia.org/wiki/Markov_model#Hidden_Markov_model).
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- From v0.6.0, Libtask is implemented by recording all the computing
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to a tape and copying that tape. Before that version, it is based on
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a tricky hack on the Julia internals. You can check the commit
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history of this repo to see the details.
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Used in the [Turing](https://github.com/TuringLang/Turing.jl) probabilistic programming language to implement various particle-based inference methods, for example those in [AdvancedPS.jl](https://github.com/TuringLang/AdvancedPS.jl/).

‎docs/Project.toml‎

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[deps]
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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Libtask = "6f1fad26-d15e-5dc8-ae53-837a1d7b8c9f"

‎docs/make.jl‎

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using Documenter, Libtask
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DocMeta.setdocmeta!(Libtask, :DocTestSetup, :(using Libtask); recursive=true)
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makedocs(;
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sitename="Libtask", doctest=true, pages=["index.md", "internals.md"], modules=[Libtask]
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)
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deploydocs(; repo="github.com/TuringLang/Libtask.jl.git", push_preview=true)

‎docs/src/index.md‎

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# Libtask
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Libtask is best explained by the docstring for [`TapedTask`](@ref):
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```@docs; canonical=true
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Libtask.TapedTask
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```
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The functions discussed the above docstring (in addition to [`TapedTask`](@ref) itself) form the
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public interface of Libtask.jl.
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They divide neatly into two kinds of functions: those which are used to manipulate
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[`TapedTask`](@ref)s, and those which are intended to be used _inside_ a
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[`TapedTask`](@ref).
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First, manipulation of [`TapedTask`](@ref)s:
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```@docs; canonical=true
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Libtask.consume
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Base.copy(::Libtask.TapedTask)
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Libtask.set_dynamic_scope!
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```
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Functions for use inside a [`TapedTask`](@ref)s are:
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```@docs; canonical=true
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Libtask.produce
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Libtask.get_dynamic_scope
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```

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