Build Cache [using jupyter-book] #206

	name: Build Cache [using jupyter-book]
	on:
	schedule:
	# Execute cache weekly at 3am on Monday
	- cron: '0 3 * * 1'
	workflow_dispatch:
	jobs:
	cache:
	runs-on: "runs-on=${{ github.run_id }}/family=g4dn.2xlarge/image=quantecon_ubuntu2404/volume=80gb/spot=false"
	steps:
	- uses: actions/checkout@v7
	- name: Setup Anaconda
	uses: conda-incubator/setup-miniconda@v4
	with:
	auto-update-conda: true
	auto-activate-base: true
	miniconda-version: 'latest'
	python-version: "3.13"
	environment-file: environment.yml
	activate-environment: quantecon
	- name: Install JAX and Numpyro
	shell: bash -l {0}
	run: \|
	# Pinned: jax 0.11.1 (2026-08-17) hangs numpy_vs_numba_vs_jax's
	# lax.fori_loop cells -- they jit with device=cpu, so the CPU-path
	# regression bites even on these GPU runners. Context is recorded in
	# QuantEcon/workspace-lectures#49. With jax already present, the
	# lecture's unpinned `!pip install quantecon jax` cell is satisfied
	# and does not upgrade.
	pip install "jax[cuda13]==0.11.0"
	pip install numpyro
	python scripts/test-jax-install.py
	- name: Check nvidia drivers
	shell: bash -l {0}
	run: \|
	nvidia-smi
	- name: Build HTML
	shell: bash -l {0}
	run: \|
	jb build lectures --path-output ./ -W --keep-going
	- name: Upload Execution Reports
	uses: actions/upload-artifact@v7
	if: failure()
	with:
	name: execution-reports
	path: _build/html/reports
	- name: Upload "_build" folder (cache)
	uses: actions/upload-artifact@v7
	with:
	name: build-cache
	path: _build
	include-hidden-files: true

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