MAINT: remove ec2 and run on GitHub Actions quantecon-gpu

.github/workflows/cache.yml

@@ -1,21 +1,31 @@
 name: Build Cache [using jupyter-book]
 on:
-  push:
-    branches:
-      - main
   schedule:
     # Execute cache weekly at 3am on Monday
     - cron:  '0 3 * * 1'
+  workflow_dispatch:
 jobs:
   cache:
-    runs-on: quantecon-gpu
-    container:
-      image: ghcr.io/quantecon/lecture-python-container:cuda-12.6.0-anaconda-2024-10-py312-b
-      options: --gpus all
+    runs-on: "runs-on=${{ github.run_id }}/family=g4dn.2xlarge/image=quantecon_ubuntu2404/disk=large"
     steps:
       - uses: actions/checkout@v4
         with:
           ref: ${{ github.event.pull_request.head.sha }}
+      - name: Setup Anaconda
+        uses: conda-incubator/setup-miniconda@v3
+        with:
+          auto-update-conda: true
+          auto-activate-base: true
+          miniconda-version: 'latest'
+          python-version: "3.12"
+          environment-file: environment.yml
+          activate-environment: quantecon
+      - name: Install JAX, Numpyro
+        shell: bash -l {0}
+        run: |
+          pip install --upgrade "jax[cuda12-local]"
+          pip install numpyro  
+          python scripts/test-jax-install.py
       - name: Check nvidia drivers
         shell: bash -l {0}
         run: |

.github/workflows/ci.yml

@@ -1,36 +1,30 @@
 name: Build Project [using jupyter-book]
 on: [pull_request]
 jobs:
-  deploy-runner:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: iterative/setup-cml@v3
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ github.event.pull_request.head.sha }}
-      - name: Deploy runner on EC2
-        env:
-          REPO_TOKEN: ${{ secrets.QUANTECON_SERVICES_PAT }}
-          AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
-          AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-        run: |
-          cml runner launch \
-              --cloud=aws \
-              --cloud-region=us-west-2 \
-              --cloud-type=p3.2xlarge \
-              --labels=cml-gpu \
-              --cloud-hdd-size=50
   preview:
-    needs: deploy-runner
-    runs-on: [self-hosted, cml-gpu]
-    container:
-      image: docker://mmcky/quantecon-lecture-python:cuda-12.3.1-anaconda-2024-02-py311
-      options: --gpus all
+    runs-on: "runs-on=${{ github.run_id }}/family=g4dn.2xlarge/image=quantecon_ubuntu2404/disk=large"
     steps:
       - uses: actions/checkout@v4
         with:
           ref: ${{ github.event.pull_request.head.sha }}
-      # Check nvidia drivers
+      - name: Setup Anaconda
+        uses: conda-incubator/setup-miniconda@v3
+        with:
+          auto-update-conda: true
+          auto-activate-base: true
+          miniconda-version: 'latest'
+          python-version: "3.12"
+          environment-file: environment.yml
+          activate-environment: quantecon
+      - name: Install JAX, Numpyro
+        shell: bash -l {0}
+        run: |
+          pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
+          pip install pyro-ppl
+          pip install --upgrade "jax[cuda12-local]"
+          pip install numpyro  
+          python scripts/test-jax-install.py
+        # Check nvidia drivers
       - name: nvidia Drivers
         shell: bash -l {0}
         run: nvidia-smi

.github/workflows/collab.yml

@@ -0,0 +1,56 @@
+name: Build Project on Google Collab (Execution)
+on: [pull_request]
+jobs:
+  execution-checks:
+    runs-on: "runs-on=${{ github.run_id }}/family=g4dn.2xlarge/image=ubuntu24-gpu-x64/disk=large"
+    container:
+      image: docker://us-docker.pkg.dev/colab-images/public/runtime
+      options: --gpus all
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          ref: ${{ github.event.pull_request.head.sha }}
+      - name: Check nvidia drivers
+        shell: bash -l {0}
+        run: |
+          nvidia-smi
+      - name: Check python version
+        shell: bash -l {0}
+        run: |
+          python --version
+      - name: Display Pip Versions
+        shell: bash -l {0}
+        run: pip list
+      - name: Download "build" folder (cache)
+        uses: dawidd6/action-download-artifact@v3
+        with:
+          workflow: cache.yml
+          branch: main
+          name: build-cache
+          path: _build
+      # Install build software
+      - name: Install Build Software
+        shell: bash -l {0}
+        run: |
+          pip install jupyter-book==1.0.3 quantecon-book-theme==0.8.2 sphinx-tojupyter==0.3.0 sphinxext-rediraffe==0.2.7 sphinxcontrib-youtube==1.3.0 sphinx-togglebutton==0.3.2 arviz sphinx-proof sphinx-exercise sphinx-reredirects
+      # Build of HTML (Execution Testing)
+      - name: Build HTML
+        shell: bash -l {0}
+        run: |
+          jb build lectures --path-output ./ -n -W --keep-going
+      - name: Upload Execution Reports
+        uses: actions/upload-artifact@v4
+        if: failure()
+        with:
+          name: execution-reports
+          path: _build/html/reports
+      - name: Preview Deploy to Netlify
+        uses: nwtgck/actions-netlify@v2
+        with:
+          publish-dir: '_build/html/'
+          production-branch: main
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          deploy-message: "Preview Deploy from GitHub Actions"
+        env:
+          NETLIFY_AUTH_TOKEN: ${{ secrets.NETLIFY_AUTH_TOKEN }}
+          NETLIFY_SITE_ID: ${{ secrets.NETLIFY_SITE_ID }}

.github/workflows/linkcheck.yml

@@ -13,7 +13,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ["ubuntu-latest"]
-        python-version: ["3.11"]
+        python-version: ["3.12"]
     steps:
       - name: Checkout
         uses: actions/checkout@v4
@@ -23,7 +23,7 @@ jobs:
           auto-update-conda: true
           auto-activate-base: true
           miniconda-version: 'latest'
-          python-version: '3.11'
+          python-version: '3.12'
           environment-file: environment.yml
           activate-environment: quantecon
       - name: Download "build" folder (cache)

.github/workflows/publish.yml

@@ -4,38 +4,27 @@ on:
     tags:
       - 'publish*'
 jobs:
-  deploy-runner:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: iterative/setup-cml@v3
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ github.event.pull_request.head.sha }}
-      - name: Deploy runner on EC2
-        env:
-          REPO_TOKEN: ${{ secrets.QUANTECON_SERVICES_PAT }}
-          AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
-          AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-        run: |
-          cml runner launch \
-              --cloud=aws \
-              --cloud-region=us-west-2 \
-              --cloud-type=p3.2xlarge \
-              --labels=cml-gpu \
-              --cloud-hdd-size=50
   publish:
     if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags')
-    needs: deploy-runner
-    runs-on: [self-hosted, cml-gpu]
-    container:
-      image: docker://mmcky/quantecon-lecture-python:cuda-12.3.1-anaconda-2024-02-py311
-      options: --gpus all
+    runs-on: "runs-on=${{ github.run_id }}/family=g4dn.2xlarge/image=quantecon_ubuntu2404/disk=large"
     steps:
       - name: Checkout
         uses: actions/checkout@v4
-      - name: Install Git (required to commit notebooks)
+      - name: Setup Anaconda
+        uses: conda-incubator/setup-miniconda@v3
+        with:
+          auto-update-conda: true
+          auto-activate-base: true
+          miniconda-version: 'latest'
+          python-version: "3.12"
+          environment-file: environment.yml
+          activate-environment: quantecon
+      - name: Install JAX, Numpyro
         shell: bash -l {0}
-        run: apt-get install -y git
+        run: |
+          pip install --upgrade "jax[cuda12-local]"
+          pip install numpyro  
+          python scripts/test-jax-install.py
       - name: Check nvidia drivers
         shell: bash -l {0}
         run: |

environment.yml

@@ -2,21 +2,17 @@ name: quantecon
 channels:
   - default
 dependencies:
-  - python=3.11
-  - anaconda=2024.02
+  - python=3.12
+  - anaconda=2024.10
   - pip
   - pip:
-    - jupyter-book==0.15.1
-    - docutils==0.17.1
-    - quantecon-book-theme==0.7.1
-    - sphinx-reredirects==0.1.3
+    - jupyter-book==1.0.3
+    - quantecon-book-theme==0.7.6
     - sphinx-tojupyter==0.3.0
     - sphinxext-rediraffe==0.2.7
-    - sphinx-exercise==0.4.1
-    - ghp-import==2.1.0
-    - sphinxcontrib-youtube==1.2.0
+    - sphinx-reredirects==0.1.4
+    - sphinx-exercise==1.0.1
+    - sphinx-proof==0.2.0
+    - ghp-import==1.1.0
+    - sphinxcontrib-youtube==1.3.0 #Version 1.3.0 is required as quantecon-book-theme is only compatible with sphinx<=5
     - sphinx-togglebutton==0.3.2
-    - arviz==0.13.0
-    - kaleido
-    # Docker Requirements
-    - pytz

lectures/_admonition/gpu.md

@@ -0,0 +1,9 @@
+```{admonition} GPU
+:class: warning
+
+This lecture was built using a machine with the latest CUDA and CUDANN frameworks installed with access to a GPU.
+
+To run this lecture on [Google Colab](https://colab.research.google.com/), click on the "play" icon top right, select Colab, and set the runtime environment to include a GPU.
+
+To run this lecture on your own machine, you need to install the software listed following this notice.
+```

lectures/ar1_bayes.md

@@ -13,15 +13,25 @@ kernelspec:
 
 # Posterior Distributions for  AR(1) Parameters
 
-We'll begin with some Python imports.
+```{include} _admonition/gpu.md
+```
 
+```{code-cell} ipython3
+:tags: [hide-output]
+
+!pip install numpyro jax
+```
+
+In addition to what's included in base Anaconda, we need to install the following packages
 
 ```{code-cell} ipython3
 :tags: [hide-output]
 
-!pip install arviz pymc numpyro jax
+!pip install arviz pymc
 ```
 
+We'll begin with some Python imports.
+
 ```{code-cell} ipython3
 
 import arviz as az

lectures/back_prop.md

@@ -4,19 +4,36 @@ jupytext:
     extension: .md
     format_name: myst
     format_version: 0.13
-    jupytext_version: 1.11.5
+    jupytext_version: 1.16.7
 kernelspec:
-  display_name: Python 3
+  display_name: Python 3 (ipykernel)
   language: python
   name: python3
 ---
 
 # Introduction to Artificial Neural Networks
 
+```{include} _admonition/gpu.md
+```
+
+```{code-cell} ipython3
+:tags: [skip-execution]
+
+!pip install --upgrade jax
+```
+
+```{code-cell} ipython3
+import jax
+## to check that gpu is activated in environment
+print(f"JAX backend: {jax.devices()[0].platform}")
+```
+
+In addition to what's included in base Anaconda, we need to install the following packages
+
 ```{code-cell} ipython3
 :tags: [hide-output]
 
-!pip install --upgrade jax jaxlib kaleido
+!pip install kaleido
 !conda install -y -c plotly plotly plotly-orca retrying
 ```
 
@@ -593,15 +610,4 @@ Image(fig.to_image(format="png"))
 # notebook locally
 ```
 
-```{code-cell} ipython3
-## to check that gpu is activated in environment
 
-from jax.lib import xla_bridge
-print(xla_bridge.get_backend().platform)
-```
-
-```{note}
-**Cloud Environment:** This lecture site is built in a server environment that doesn't have access to a `gpu`
-If you run this lecture locally this lets you know where your code is being executed, either
-via the `cpu` or the `gpu`
-```