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Merge pull request #150 from DiamondLightSource/removecucim
retiring cucim dependency
2 parents 52deaaa + c4738bb commit 7ae56bd

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16 files changed

+89
-190
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.github/workflows/doc_conda.yml renamed to .github/workflows/httomolibgpu_doc_conda.yml

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name: HTTomolibGPU doc test
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name: HTTomolibgpu docs
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on:
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workflow_dispatch:
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with:
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python-version: "3.10"
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- name: httomolibgpu
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- name: httomolib
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uses: conda-incubator/setup-miniconda@v2
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with:
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auto-update-conda: false
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- name: Run ghp-import
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run: ghp-import -n -p -f ./docs/build
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env:
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GITHUB_TOKEN: ${{ github.token }}
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GITHUB_TOKEN: ${{ github.token }}
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.github/workflows/nightly_build.yml renamed to .github/workflows/httomolibgpu_nightly_build.yml

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name: httomolibgpu nightly dev conda package build + upload
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name: httomolibgpu nightly dev
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on:
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schedule:
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# Run at midnight every day
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- cron: '0 0 * * *'
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jobs:
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build-linux:
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main-conda-build:
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runs-on: ubuntu-20.04
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defaults:
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ref: "main"
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fetch-depth: 0
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# setup Python 3.9
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- name: Setup Python 3.9
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uses: actions/setup-python@v2
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# setup Python 3.10
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- name: Setup Python 3.10
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uses: actions/setup-python@v4
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with:
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python-version: 3.9
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python-version: '3.10'
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- name: Decrypt a secret
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run: ./.scripts/decrypt_secret.sh

.github/workflows/tests_run.yml renamed to .github/workflows/httomolibgpu_tests_run_iris.yml

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name: httomolibgpu tests on Iris
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name: httomolibgpu tests
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on:
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push:
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branches:
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- main
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jobs:
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build-linux:
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iris-gpu:
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runs-on: iris-gpu
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container:
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image: nvidia/cuda:11.6.2-devel-ubi8

.github/workflows/conda_upload.yml renamed to .github/workflows/httomolibgpu_version_tag.yml

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name: httomolibgpu conda upload
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name: httomolibgpu version tag pushed
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# Run the workflow whenever a tag beginning with `v` is pushed to any branch
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on:
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- v*
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jobs:
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build-linux:
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conda-upload-main:
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runs-on: ubuntu-20.04
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defaults:
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fetch-depth: 0
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ref: ${{ github.ref_name }}
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# setup Python 3.9
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- name: Setup Python 3.9
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uses: actions/setup-python@v2
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# setup Python 3.10
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- name: Setup Python 3.10
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uses: actions/setup-python@v4
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with:
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python-version: 3.9
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python-version: '3.10'
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# install dependencies with conda
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- name: Install dependencies with conda

.scripts/conda_upload.sh

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$CONDA/bin/conda install conda-build
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$CONDA/bin/conda install -c conda-forge anaconda-client
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$CONDA/bin/conda build . -c conda-forge -c httomo -c rapidsai --no-test
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$CONDA/bin/conda build . -c conda-forge -c httomo --no-test
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# upload packages to conda
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find $CONDA_BLD_PATH/$OS -name *.tar.bz2 | while read file

LICENSE

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HTTomoLibGPU is dual licenced under the Apache V2 and GPL V3 licences both of
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which appear bellow. The following section from the apache website
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details the compatability of ApacheV2 with GPLV3 and explains the
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HTTomoLibGPU is dual licenced under the Apache V2 and GPL V3 licences both of
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which appear below. The following section from the apache website
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details the compatibility of ApacheV2 with GPLV3 and explains the
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requirement for the dual licence.
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From http://www.apache.org/licenses/GPL-compatibility.html
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The Free Software Foundation considers the Apache License, Version
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The Free Software Foundation considers the Apache License, Version
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2.0 to be a free software license, compatible with version 3 of the GPL.
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The Software Freedom Law Center provides practical advice for developers
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The Software Freedom Law Center provides practical advice for developers
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about including permissively licensed source.
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Apache 2 software can therefore be included in GPLv3 projects, because
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the GPLv3 license accepts our software into GPLv3 works. However, GPLv3
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software cannot be included in Apache projects. The licenses are incompatible
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in one direction only, and it is a result of ASF's licensing philosophy and
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Apache 2 software can therefore be included in GPLv3 projects, because
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the GPLv3 license accepts our software into GPLv3 works. However, GPLv3
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software cannot be included in Apache projects. The licenses are incompatible
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in one direction only, and it is a result of ASF's licensing philosophy and
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the GPLv3 authors' interpretation of copyright law.
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This licensing incompatibility applies only when some Apache project software
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becomes a derivative work of some GPLv3 software, because then the Apache
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software would have to be distributed under GPLv3. This would be incompatible
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with ASF's requirement that all Apache software must be distributed under the
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This licensing incompatibility applies only when some Apache project software
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becomes a derivative work of some GPLv3 software, because then the Apache
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software would have to be distributed under GPLv3. This would be incompatible
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with ASF's requirement that all Apache software must be distributed under the
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Apache License 2.0.
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We avoid GPLv3 software because merely linking to it is considered by the GPLv3
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authors to create a derivative work. We want to honor their license. Unless GPLv3
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licensors relax this interpretation of their own license regarding linking, our
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licensing philosophies are fundamentally incompatible. This is an identical issue
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We avoid GPLv3 software because merely linking to it is considered by the GPLv3
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authors to create a derivative work. We want to honor their license. Unless GPLv3
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licensors relax this interpretation of their own license regarding linking, our
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licensing philosophies are fundamentally incompatible. This is an identical issue
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for both GPLv2 and GPLv3.
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HTTomoLibGPU makes use of some GPLv3 libraries in the following packages:
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ToMoBAR (depends on ASTRA-Toolbox)
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If your use of the code makes use of these imports, then the software is licenced under
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If your use of the code makes use of these imports, then the software is licenced under
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GPLV3 as required by the licence. However if you do not use or redistribute the plugins
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containing these imports, the software may be considered licenced under the Apache V2
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containing these imports, the software may be considered licenced under the Apache V2
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licence, Specifically all of the core functionality of HTTomoLibGPU.
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Both licences now follow.

README.rst

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$ conda create --name httomolibgpu # create a fresh conda environment
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$ conda activate httomolibgpu # activate the environment
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$ conda install -c httomo httomolibgpu -c rapidsai -c conda-forge # for linux users
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$ conda install -c httomo httomolibgpu -c jplumail -c conda-forge # for windows users
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$ conda install -c httomo httomolibgpu -c conda-forge # for linux users
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Setup the development environment:
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==================================
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.. code-block:: console
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$ conda build conda/recipe/ -c conda-forge -c httomo -c rapidsai
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$ conda build conda/recipe/ -c conda-forge -c httomo
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conda/environment.yml

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channels:
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- conda-forge
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- httomo
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- rapidsai
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dependencies:
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- conda-forge::cupy=12.3.0
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- conda-forge::numpy<=1.25
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- conda-forge::h5py
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- conda-forge::astra-toolbox
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- httomo::tomobar
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- rapidsai::cucim
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- conda-forge::scikit-image

conda/recipe/meta.yaml

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- python
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- numpy>= 1.20, <= 1.25
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- cupy=12.3.0
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- cucim
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- astra-toolbox
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- nvtx
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- tomobar

docs/source/conf.py

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for mod_name in MOCK_MODULES:
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sys.modules[mod_name] = mock.Mock()
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class CustomMock(mock.Mock):
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def __repr__(self):
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return "<cp.ndarray>"
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sys.modules["cupy"] = CustomMock()
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sys.modules["numpy"] = CustomMock()
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html_static_path = ["_static"]
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html_use_smartypants = True
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"""
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html_theme_options = {
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"logo_only": True,
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"display_version": False,
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"githuburl": "https://github.com/DiamondLightSource/httomolibgpu",
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}
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"""
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html_theme_options = {
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"show_toc_level": 1,
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"navbar_align": "left", # [left, content, right] For testing that the navbar items align properly

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