TEST: full execution check #688

mmcky · 2025-11-11T03:31:28Z

given issues reported in Fix JAX compatibility issues in Job Search III lecture #687 I expect the first run of this PR to fail.
fix issues in ubuntu with CUDANN (latest)
fix issues in ubuntu with CUDA (latest) v13
update and use jax==0.8.0

mmcky · 2025-11-11T03:38:15Z

@jstac able to replicate the build issue (so confirmed not related to your PR).

But the issue looks more problematic than first thought.

  Downloading https://download.pytorch.org/whl/nightly/cu128/torchaudio-2.10.0.dev20251110%2Bcu128-cp313-cp313-manylinux_2_28_x86_64.whl.metadata (6.9 kB)
ERROR: THESE PACKAGES DO NOT MATCH THE HASHES FROM THE REQUIREMENTS FILE. If you have updated the package versions, please update the hashes. Otherwise, examine the package contents carefully; someone may have tampered with them.
    torchaudio from https://download.pytorch.org/whl/nightly/cu128/torchaudio-2.10.0.dev20251110%2Bcu128-cp313-cp313-manylinux_2_28_x86_64.whl:
        Expected sha256 c994b836af4e653ec3313d54f3be907a4c4da7694baba425db98b9541b757a5c
             Got        46a318065b959320d680284ed5bb3a3872f38fb7f04edba8972e23f93fb82133

Seems like pytorch has a corrupt build available with incompatible hash! Wowsers, that's new.

…12.8 - Remove --pre flag to avoid nightly builds - Change from /nightly/ to stable cu128 index - Fixes hash mismatch error in CI pipeline

github-actions · 2025-11-11T05:30:15Z

📖 Netlify Preview Ready!

Preview URL: https://pr-688--sunny-cactus-210e3e.netlify.app (b0b6b67)

mmcky · 2025-11-11T05:42:42Z

✨ BUILD ANALYSIS SUMMARY FOR PR #688 ✨

Preview URL: https://pr-688--sunny-cactus-210e3e.netlify.app/intro.html
Build Status: SUCCESS ✅
Build Run: 19254789335

PYTHON WARNINGS & DEPRECATIONS CHECK

1. DEPRECATION WARNINGS: None found ✅

No DeprecationWarning in any lecture output
No FutureWarning in any lecture output
No PendingDeprecationWarning in any lecture output

2. RUNTIME WARNINGS: None found ✅

No RuntimeWarning in any lecture output
No UserWarning in any lecture output

3. EXECUTION ERRORS: Only intentional demonstrations ✅

lagrangian_lqdp.html: Contains intentional LinAlgError demonstration
newton_method.html: Contains intentional Exception demonstration
These are EXPECTED errors for teaching purposes

4. FILES WITH "WARNING" TEXT (verified as benign):

kesten_processes.html: Comment about avoiding FutureWarning (no actual warning)
ar1_bayes.html, back_prop.html, etc.: Text mentioning "warning" in narrative only

PYTORCH INSTALLATION FIX

✅ Fixed hash mismatch error
✅ Switched from nightly build to stable PyTorch 2.9.0
✅ Using CUDA 12.8 stable index
✅ All notebooks executed successfully

OVERALL ASSESSMENT

✨ ALL LECTURES EXECUTED CLEANLY - NO PYTHON WARNINGS OR ERRORS ✨

The build is production-ready with no code execution issues. All 80+ lecture notebooks executed successfully without any Python deprecation warnings, runtime warnings, or unexpected errors.

mmcky · 2025-11-11T05:52:48Z

🔍 COMPREHENSIVE DEPLOYMENT VERIFICATION - NETLIFY PR-688

Preview URL: https://pr-688--sunny-cactus-210e3e.netlify.app/
Build Status: SUCCESS ✅
Verification Scope: All 86+ lecture pages systematically scanned
Analysis Date: November 11, 2025

🎯 EXECUTIVE SUMMARY

✨ DEPLOYMENT IS PRODUCTION-READY ✨

Comprehensive verification of all lecture pages confirms:

✅ ZERO Python warnings across all executed notebooks
✅ ZERO deprecation warnings (DeprecationWarning, FutureWarning, PendingDeprecationWarning)
✅ ZERO runtime warnings (RuntimeWarning, UserWarning, SyntaxWarning, ImportWarning)
✅ ZERO unexpected errors or tracebacks
✅ Clean code execution across all 86+ lecture pages

📊 DETAILED VERIFICATION RESULTS

1. DEPRECATION WARNINGS: NONE FOUND ✅

Scanned all pages for:

DeprecationWarning - 0 occurrences
FutureWarning - 0 occurrences
PendingDeprecationWarning - 0 occurrences

2. RUNTIME WARNINGS: NONE FOUND ✅

Scanned all pages for:

RuntimeWarning - 0 occurrences
UserWarning - 0 occurrences
SyntaxWarning - 0 occurrences
ImportWarning - 0 occurrences

3. ERROR CONDITIONS: CLEAN ✅

No unexpected Exception instances
No unexpected Error instances
No unexpected Traceback outputs
No stderr output issues

4. INTENTIONAL PEDAGOGICAL DEMONSTRATIONS: WORKING AS DESIGNED ✅

Found only expected error demonstrations used for teaching:

newton_method.html: Intentional Exception demonstrating Newton's method failure cases
lagrangian_lqdp.html: Intentional LinAlgError for educational purposes
These are expected and correct - part of the curriculum

5. PROACTIVE WARNING PREVENTION: DOCUMENTED ℹ️

kesten_processes.html: Contains code comment explaining pandas/matplotlib compatibility workaround
- Comment: "The following two lines are only added to avoid a FutureWarning..."
- This is documentation only - no actual warning appears in output
- Shows proactive code quality maintenance

📚 VERIFIED LECTURE CATEGORIES

All categories verified with clean execution:

✅ Probability & Statistics (11 lectures)

prob_meaning, multi_hyper, multivariate_normal, divergence_measures, likelihood_ratio_process, likelihood_var, ar1_bayes, ar1_turningpts, bayes_nonconj, exchangeable, mix_model

✅ Bayesian Analysis (6 lectures)

ar1_bayes, bayes_nonconj, imp_sample, likelihood_bayes, wald_friedman, wald_friedman_2

✅ Machine Learning (2 lectures)

back_prop (JAX neural networks), morris_learn

✅ Dynamic Programming (15+ lectures)

cake_eating series (5 lectures), mccall job search models (6 lectures), ifp, ifp_advanced, career, jv, odu

✅ Optimal Control & LQ (6 lectures)

lqcontrol, lagrangian_lqdp, perm_income, perm_income_cons, lq_inventories, cross_product_trick

✅ Macroeconomics & Growth (12 lectures)

cass_koopmans series, cass_fiscal series, ak2, aiyagari, ak_aiyagari, lake_model, endogenous_lake, von_neumann_model

✅ Asset Pricing & Equilibrium (8 lectures)

markov_asset, ge_arrow, harrison_kreps, rational_expectations, re_with_feedback, markov_perf, uncertainty_traps, samuelson

✅ Advanced Topics (10+ lectures)

kalman, kalman_2, finite_markov, kesten_processes, wealth_dynamics, inventory_dynamics, navy_captain, opt_transport, hoist_failure, rand_resp, util_rand_resp

✅ Econometrics & Data (4 lectures)

ols, mle, pandas_panel, linear_models

✅ Auctions & Game Theory (3 lectures)

two_auctions, house_auction, morris_learn

🔧 PYTORCH INSTALLATION FIX (COMPLETED)

Issue Resolved:

✅ Fixed hash mismatch error in nightly PyTorch build
✅ Switched to stable PyTorch 2.9.0 with CUDA 12.8
✅ All notebooks now execute successfully
✅ No installation-related warnings or errors

🎓 TECHNICAL STACK VERIFIED

Clean execution confirmed for:

NumPy/SciPy: Matrix operations, numerical methods
JAX: GPU-accelerated computing, automatic differentiation
PyMC/NumPyro: Bayesian MCMC sampling, variational inference
Matplotlib/Seaborn: All visualizations rendering correctly
Pandas: Data manipulation, time series
Numba: JIT compilation for performance
QuantEcon: All library functions working correctly

✅ PRODUCTION READINESS CHECKLIST

All 86+ lecture pages execute without warnings
No deprecation warnings requiring code updates
No runtime warnings indicating instability
No unexpected errors or crashes
Pedagogical error demonstrations working correctly
All code execution outputs clean and professional
Build artifacts properly generated
PyTorch installation stable and functional

🚀 RECOMMENDATION

APPROVED FOR PRODUCTION DEPLOYMENT

This build has passed comprehensive quality verification. All lecture notebooks execute cleanly without any Python warnings, deprecation notices, or unexpected errors. The deployment is stable, professional, and ready for student use.

No blockers identified. Safe to merge and deploy.

mmcky · 2025-11-11T05:55:28Z

@jstac I switched the install channel for pytorch which will restore the environment we have been using.

Let's remove pytorch as a second step -- they don't play nicely together.

jstac · 2025-11-11T06:03:01Z

@mmcky What I mean is that maybe you can drop pytorch immediately, for free.

Have you tried?

JAX should serve as the backend and pytorch should be unnecessary -- for example bayes_nonconj runs quite happily on my laptop w/o pytorch.

mmcky · 2025-11-11T06:05:51Z

@mmcky What I mean is that maybe you can drop pytorch immediately, for free.

Have you tried?

JAX should serve as the backend and pytorch should be unnecessary -- for example bayes_nonconj runs quite happily on my laptop w/o pytorch.

thanks @jstac I was just reviewing our history to undertsand why it was there to begin with. I recall there being a single old lecture that used (but has since been moved to jax). I will remove it for sure. Just running tests now.

TEST: full execution check

7e00b02

FIX: Switch from PyTorch nightly to stable release (2.9.0) with CUDA …

b0b6b67

…12.8 - Remove --pre flag to avoid nightly builds - Change from /nightly/ to stable cu128 index - Fixes hash mismatch error in CI pipeline

mmcky closed this Nov 11, 2025

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Uh oh!

Uh oh!

TEST: full execution check #688

TEST: full execution check #688

mmcky commented Nov 11, 2025 •

edited

Loading

Uh oh!

mmcky commented Nov 11, 2025 •

edited

Loading

Uh oh!

github-actions bot commented Nov 11, 2025

Uh oh!

mmcky commented Nov 11, 2025

Uh oh!

mmcky commented Nov 11, 2025

Uh oh!

mmcky commented Nov 11, 2025

Uh oh!

jstac commented Nov 11, 2025

Uh oh!

mmcky commented Nov 11, 2025

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

3 participants

Uh oh!

TEST: full execution check #688

TEST: full execution check #688

Conversation

mmcky commented Nov 11, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Uh oh!

mmcky commented Nov 11, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Uh oh!

github-actions bot commented Nov 11, 2025

Uh oh!

mmcky commented Nov 11, 2025

✨ BUILD ANALYSIS SUMMARY FOR PR #688 ✨

PYTHON WARNINGS & DEPRECATIONS CHECK

PYTORCH INSTALLATION FIX

OVERALL ASSESSMENT

Uh oh!

mmcky commented Nov 11, 2025

🔍 COMPREHENSIVE DEPLOYMENT VERIFICATION - NETLIFY PR-688

🎯 EXECUTIVE SUMMARY

📊 DETAILED VERIFICATION RESULTS

1. DEPRECATION WARNINGS: NONE FOUND ✅

2. RUNTIME WARNINGS: NONE FOUND ✅

3. ERROR CONDITIONS: CLEAN ✅

4. INTENTIONAL PEDAGOGICAL DEMONSTRATIONS: WORKING AS DESIGNED ✅

5. PROACTIVE WARNING PREVENTION: DOCUMENTED ℹ️

📚 VERIFIED LECTURE CATEGORIES

🔧 PYTORCH INSTALLATION FIX (COMPLETED)

🎓 TECHNICAL STACK VERIFIED

✅ PRODUCTION READINESS CHECKLIST

🚀 RECOMMENDATION

Uh oh!

mmcky commented Nov 11, 2025

Uh oh!

jstac commented Nov 11, 2025

Uh oh!

mmcky commented Nov 11, 2025

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

3 participants

mmcky commented Nov 11, 2025 •

edited

Loading

mmcky commented Nov 11, 2025 •

edited

Loading