Fix bugs in ifp_advanced lecture #757
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- Fix typo: jnp.block_until_ready(a_start) → a_star.block_until_ready() - Add missing functools.partial import for JAX JIT static arguments - Fix compute_asset_stationary JIT compilation with static_argnums - Remove invalid verbose parameter from solve_model calls - Refactor solve_model to use jax.lax.while_loop for better performance - Clean up code structure and improve function signatures 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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📖 Netlify Preview Ready! Preview URL: https://pr-757--sunny-cactus-210e3e.netlify.app (8a1b015) 📚 Changed Lecture Pages: ifp_advanced |
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The lecture now runs successfully from start to finish. Key fixes:
All code executes cleanly with expected output. The model solves and simulates successfully, producing Gini coefficients for different parameter values. |
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Summary
This PR fixes several bugs in the
ifp_advancedlecture that were preventing the code from running:jnp.block_until_ready(a_start)→a_star.block_until_ready()(incorrect variable name)from functools import partialimport needed for JAX JIT static argumentscompute_asset_stationaryJIT compilation by adding@partial(jax.jit, static_argnums=(3, 4, 5))to handle dynamic shape parametersverboseparameter fromsolve_modelcallssolve_modelto usejax.lax.while_loopfor better performance and proper JIT compilationTesting
Successfully ran the lecture through jupytext conversion and Python execution:
🤖 Generated with Claude Code