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MAINT: Migrate from EC2 backend to GA backend (#285)
* MAINT: Migrate from EC2 backend to GA backend * update machine details to github actions
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‎.github/workflows/cache.yml‎

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branches:
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- main
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jobs:
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deploy-runner:
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runs-on: ubuntu-latest
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steps:
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- uses: iterative/setup-cml@v1
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- uses: actions/checkout@v3
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with:
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ref: ${{ github.event.pull_request.head.sha }}
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- name: Deploy runner on EC2
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env:
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REPO_TOKEN: ${{ secrets.QUANTECON_SERVICES_PAT }}
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AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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run: |
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cml runner launch \
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--cloud=aws \
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--cloud-region=us-west-2 \
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--cloud-type=p3.2xlarge \
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--labels=cml-gpu \
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--cloud-hdd-size=40
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cache:
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needs: deploy-runner
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runs-on: [self-hosted, cml-gpu]
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container:
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image: docker://mmcky/quantecon-lecture-python:cuda-12.1.0-anaconda-2023-03-py310
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options: --gpus all
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Setup Anaconda
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uses: conda-incubator/setup-miniconda@v2
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with:
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ref: ${{ github.event.pull_request.head.sha }}
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# Install Hardware Dependant Libraries
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- name: Check nvidia drivers
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shell: bash -l {0}
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run: |
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nvidia-smi
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auto-update-conda: true
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auto-activate-base: true
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miniconda-version: 'latest'
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python-version: "3.10"
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environment-file: environment.yml
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activate-environment: quantecon
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- name: Build HTML
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shell: bash -l {0}
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run: |

‎.github/workflows/ci.yml‎

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name: Build Project [using jupyter-book]
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on: [pull_request]
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jobs:
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deploy-runner:
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runs-on: ubuntu-latest
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steps:
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- uses: iterative/setup-cml@v1
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- uses: actions/checkout@v3
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with:
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ref: ${{ github.event.pull_request.head.sha }}
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- name: Deploy runner on EC2
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env:
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REPO_TOKEN: ${{ secrets.QUANTECON_SERVICES_PAT }}
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AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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run: |
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cml runner launch \
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--cloud=aws \
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--cloud-region=us-west-2 \
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--cloud-type=p3.2xlarge \
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--labels=cml-gpu \
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--cloud-hdd-size=40
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preview:
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needs: deploy-runner
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runs-on: [self-hosted, cml-gpu]
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container:
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image: docker://mmcky/quantecon-lecture-python:cuda-12.1.0-anaconda-2023-03-py310
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options: --gpus all
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Setup Anaconda
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uses: conda-incubator/setup-miniconda@v2
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with:
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ref: ${{ github.event.pull_request.head.sha }}
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# Install Hardware Dependant Libraries
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- name: Check nvidia drivers
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shell: bash -l {0}
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auto-update-conda: true
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auto-activate-base: true
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miniconda-version: 'latest'
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python-version: "3.10"
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environment-file: environment.yml
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activate-environment: quantecon
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- name: Install latex dependencies
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run: |
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nvidia-smi
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sudo apt-get -qq update
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sudo apt-get install -y \
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texlive-latex-recommended \
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texlive-latex-extra \
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texlive-fonts-recommended \
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texlive-fonts-extra \
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texlive-xetex \
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latexmk \
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xindy \
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dvipng \
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cm-super
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- name: Display Conda Environment Versions
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shell: bash -l {0}
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run: conda list

‎.github/workflows/linkcheck.yml‎

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fail-fast: false
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matrix:
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os: ["ubuntu-latest"]
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python-version: ["3.9"]
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python-version: ["3.10"]
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steps:
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- name: Checkout
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uses: actions/checkout@v2
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uses: actions/checkout@v3
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- name: Setup Anaconda
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uses: conda-incubator/setup-miniconda@v2
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with:

‎.github/workflows/publish.yml‎

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tags:
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- 'publish*'
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jobs:
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deploy-runner:
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runs-on: ubuntu-latest
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steps:
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- uses: iterative/setup-cml@v1
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- uses: actions/checkout@v3
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with:
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ref: ${{ github.event.pull_request.head.sha }}
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- name: Deploy runner on EC2
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env:
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REPO_TOKEN: ${{ secrets.QUANTECON_SERVICES_PAT }}
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AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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run: |
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cml runner launch \
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--cloud=aws \
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--cloud-region=us-west-2 \
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--cloud-type=p3.2xlarge \
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--labels=cml-gpu \
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--cloud-hdd-size=40
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publish:
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if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags')
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needs: deploy-runner
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runs-on: [self-hosted, cml-gpu]
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container:
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image: docker://mmcky/quantecon-lecture-python:cuda-12.1.0-anaconda-2023-03-py310
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options: --gpus all
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v3
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# Install Hardware Dependant Libraries
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- name: Check nvidia drivers
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shell: bash -l {0}
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- name: Setup Anaconda
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uses: conda-incubator/setup-miniconda@v2
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with:
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auto-update-conda: true
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auto-activate-base: true
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miniconda-version: 'latest'
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python-version: "3.10"
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environment-file: environment.yml
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activate-environment: quantecon
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- name: Install latex dependencies
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run: |
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nvidia-smi
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sudo apt-get -qq update
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sudo apt-get install -y \
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texlive-latex-recommended \
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texlive-latex-extra \
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texlive-fonts-recommended \
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texlive-fonts-extra \
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texlive-xetex \
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latexmk \
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xindy \
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dvipng \
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cm-super
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- name: Display Conda Environment Versions
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shell: bash -l {0}
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run: conda list

‎lectures/status.md‎

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(status:machine-details)=
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These lectures are built on `linux` instances through `github actions` and `amazon web services (aws)` to
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enable access to a `gpu`. These lectures are built on a [p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/)
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that has access to `8 vcpu's`, a `V100 NVIDIA Tesla GPU`, and `61 Gb` of memory.
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These lectures are built on `linux` instances through `github actions`.

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