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github ci (#83)
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‎.github/workflows/Documenter.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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- master
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tags: '*'
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pull_request:
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jobs:
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docs-build:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- name: Install dependencies
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run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate(); Pkg.build(;verbose=true)'
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- name: Build and deploy
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: julia --project=docs/ docs/make.jl

‎.github/workflows/UnitTest.yml‎

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name: Unit Tests
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on:
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pull_request:
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push:
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branches:
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- master
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jobs:
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Test:
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strategy:
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fail-fast: false
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matrix:
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os: [macos-latest, ubuntu-latest]
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julia_version: ["1.0", "1", "nightly"]
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exclude:
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- os: macos-latest
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julia_version: '1.0'
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runs-on: ${{ matrix.os }}
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env:
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MPICH_INTERFACE_HOSTNAME: localhost
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JULIA_MPIEXEC_ARGS: ${{ matrix.mpiexec_args }}
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steps:
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- name: Checkout
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uses: actions/checkout@v2
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- name: Install Julia
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uses: julia-actions/setup-julia@latest
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with:
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version: ${{ matrix.julia_version }}
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# https://discourse.julialang.org/t/recommendation-cache-julia-artifacts-in-ci-services/35484
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- name: Cache artifacts
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uses: actions/cache@v1
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env:
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cache-name: cache-artifacts
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with:
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path: ~/.julia/artifacts
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key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
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restore-keys: |
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${{ runner.os }}-test-${{ env.cache-name }}-
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${{ runner.os }}-test-
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${{ runner.os }}-
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- name: Disable broken dependencies on old Julia v1.0
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if: matrix.julia_version == '1.0'
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run: cp compat/Project.toml Project.toml
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- uses: julia-actions/julia-runtest@latest
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‎.travis.yml‎

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‎Project.toml‎

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name = "TensorBoardLogger"
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uuid = "899adc3e-224a-11e9-021f-63837185c80f"
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authors = ["Filippo Vicentini <filippovicentini@gmail.com>"]
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version = "0.1.11"
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version = "0.1.12"
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[deps]
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CRC32c = "8bf52ea8-c179-5cab-976a-9e18b702a9bc"

‎README.md‎

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# TensorBoardLogger
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[![Build Status](https://travis-ci.org/PhilipVinc/TensorBoardLogger.jl.svg?branch=master)](https://travis-ci.org/PhilipVinc/TensorBoardLogger.jl) [![codecov](https://codecov.io/gh/PhilipVinc/TensorBoardLogger.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/PhilipVinc/TensorBoardLogger.jl)
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[![codecov](https://codecov.io/gh/PhilipVinc/TensorBoardLogger.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/PhilipVinc/TensorBoardLogger.jl)
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[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://philipvinc.github.io/TensorBoardLogger.jl/dev/)
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**TensorBoardLogger.jl** is a native library for logging arbitrary data to

‎compat/Project.toml‎

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name = "TensorBoardLogger"
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uuid = "899adc3e-224a-11e9-021f-63837185c80f"
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authors = ["Filippo Vicentini <filippovicentini@gmail.com>"]
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version = "0.1.12"
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[deps]
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CRC32c = "8bf52ea8-c179-5cab-976a-9e18b702a9bc"
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ColorTypes = "3da002f7-5984-5a60-b8a6-cbb66c0b333f"
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FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
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FixedPointNumbers = "53c48c17-4a7d-5ca2-90c5-79b7896eea93"
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ImageCore = "a09fc81d-aa75-5fe9-8630-4744c3626534"
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ProtoBuf = "3349acd9-ac6a-5e09-bcdb-63829b23a429"
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Requires = "ae029012-a4dd-5104-9daa-d747884805df"
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StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
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[compat]
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ColorTypes = "0.7, 0.8, 0.9, 0.10"
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FileIO = "1"
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FixedPointNumbers = "0.6, 0.7, 0.8"
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ImageCore = "0.7, 0.8"
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ProtoBuf = "0.7, 0.8"
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Requires = "0.5, 1"
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StatsBase = "0.27, 0.28, 0.29, 0.30, 0.31, 0.32, 0.33"
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julia = "0.7, 1"
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[extras]
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ImageMagick = "6218d12a-5da1-5696-b52f-db25d2ecc6d1"
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LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
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Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
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Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
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QuartzImageIO = "dca85d43-d64c-5e67-8c65-017450d5d020"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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TestImages = "5e47fb64-e119-507b-a336-dd2b206d9990"
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ValueHistories = "98cad3c8-aec3-5f06-8e41-884608649ab7"
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WAV = "8149f6b0-98f6-5db9-b78f-408fbbb8ef88"
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[targets]
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test = ["Test", "TestImages", "ImageMagick", "Logging", "LightGraphs", "Plots", "WAV", "ValueHistories", "QuartzImageIO"]

‎docs/Project.toml‎

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[deps]
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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TensorBoardLogger = "899adc3e-224a-11e9-021f-63837185c80f"

‎test/runtests.jl‎

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using TensorBoardLogger, Logging
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using TensorBoardLogger: preprocess, summary_impl
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using Test
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using MLDatasets
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using TestImages
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using ImageCore
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using ColorTypes
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@test π != log_image(logger, "rand/CLN", rand(3, 10, 2), CLN, step = step)
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@test π != log_image(logger, "rand/LCN", rand(10, 3, 2), LCN, step = step)
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sample = MNIST.traintensor(1:3)
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@test π != log_image(logger, "mnist/HWN", sample, HWN, step = step)
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@test π != log_image(logger, "mnist2/HWN", Gray.(sample), step = step)
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sample = permutedims(sample, (2, 1, 3))
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@test π != log_image(logger, "mnist/WHN", sample, WHN, step = step)
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@test π != log_image(logger, "mnist2/WHN", Gray.(sample), WHN, step = step)
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sample = permutedims(sample, (3, 2, 1))
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@test π != log_image(logger, "mnist/NHW", sample, NHW, step = step)
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@test π != log_image(logger, "mnist2/NHW", Gray.(sample), NHW, step = step)
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sample = permutedims(sample, (1, 3, 2))
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@test π != log_image(logger, "mnist/NWH", sample, NWH, step = step)
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@test π != log_image(logger, "mnist2/NWH", Gray.(sample), NWH, step = step)
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sample = testimage("toucan")
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@test π != log_image(logger, "toucan/auto", sample, step = step)
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sample = [sample, sample, sample]
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@test π != log_images(logger, "toucans/auto", sample, step = step)
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@test π != log_images(logger, "toucans", sample, CHW, step = step)
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sample = hcat(sample...)
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sample = reshape(sample, (150, 162, 3))
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@test π != log_image(logger, "toucan/CHWN", sample, CHWN, step = step)
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sample = permutedims(sample, (2, 1, 3))
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@test π != log_image(logger, "toucan/CWHN", sample, CWHN, step = step)
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sample = channelview(sample) #CWHN
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sample = permutedims(sample, (4, 1, 2, 3))
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@test π != log_image(logger, "toucan/NCWH", sample, NCWH, step = step)
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sample = permutedims(sample, (1, 2, 4, 3))
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@test π != log_image(logger, "toucan/NCHW", sample, NCHW, step = step)
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sample = permutedims(sample, (1, 4, 3, 2))
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@test π != log_image(logger, "toucan/NWHC", sample, NWHC, step = step)
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sample = permutedims(sample, (1, 3, 2, 4))
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@test π != log_image(logger, "toucan/NHWC", sample, NHWC, step = step)
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sample = permutedims(sample, (2, 3, 4, 1))
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@test π != log_image(logger, "toucan/HWCN", sample, HWCN, step = step)
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sample = permutedims(sample, (2, 1, 3, 4))
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@test π != log_image(logger, "toucan/WHCN", sample, WHCN, step = step)
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if VERSION >= v"1.3.0"
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using MLDatasets: MNIST
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sample = MNIST.traintensor(1:3)
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@test π != log_image(logger, "mnist/HWN", sample, HWN, step = step)
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@test π != log_image(logger, "mnist2/HWN", Gray.(sample), step = step)
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sample = permutedims(sample, (2, 1, 3))
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@test π != log_image(logger, "mnist/WHN", sample, WHN, step = step)
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@test π != log_image(logger, "mnist2/WHN", Gray.(sample), WHN, step = step)
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sample = permutedims(sample, (3, 2, 1))
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@test π != log_image(logger, "mnist/NHW", sample, NHW, step = step)
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@test π != log_image(logger, "mnist2/NHW", Gray.(sample), NHW, step = step)
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sample = permutedims(sample, (1, 3, 2))
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@test π != log_image(logger, "mnist/NWH", sample, NWH, step = step)
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@test π != log_image(logger, "mnist2/NWH", Gray.(sample), NWH, step = step)
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sample = testimage("toucan")
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@test π != log_image(logger, "toucan/auto", sample, step = step)
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sample = [sample, sample, sample]
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@test π != log_images(logger, "toucans/auto", sample, step = step)
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@test π != log_images(logger, "toucans", sample, CHW, step = step)
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sample = hcat(sample...)
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sample = reshape(sample, (150, 162, 3))
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@test π != log_image(logger, "toucan/CHWN", sample, CHWN, step = step)
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sample = permutedims(sample, (2, 1, 3))
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@test π != log_image(logger, "toucan/CWHN", sample, CWHN, step = step)
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sample = channelview(sample) #CWHN
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sample = permutedims(sample, (4, 1, 2, 3))
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@test π != log_image(logger, "toucan/NCWH", sample, NCWH, step = step)
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sample = permutedims(sample, (1, 2, 4, 3))
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@test π != log_image(logger, "toucan/NCHW", sample, NCHW, step = step)
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sample = permutedims(sample, (1, 4, 3, 2))
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@test π != log_image(logger, "toucan/NWHC", sample, NWHC, step = step)
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sample = permutedims(sample, (1, 3, 2, 4))
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@test π != log_image(logger, "toucan/NHWC", sample, NHWC, step = step)
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sample = permutedims(sample, (2, 3, 4, 1))
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@test π != log_image(logger, "toucan/HWCN", sample, HWCN, step = step)
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sample = permutedims(sample, (2, 1, 3, 4))
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@test π != log_image(logger, "toucan/WHCN", sample, WHCN, step = step)
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end
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end
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@testset "Image processing interface" begin
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include("Optional/test_Plots.jl")
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# Don't run PyPlot tests until I figure a way to install the dependencies
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#include("Optional/test_PyPlot.jl")
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include("Optional/test_Tracker.jl")
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if VERSION >= v"1.5.0"
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include("Optional/test_Tracker.jl")
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end
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end
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@testset "Logger dispatch overrides" begin

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