Make HOURS_VALUES a host array to avoid import-time GPU preallocation#13
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hmgaudecker wants to merge 3 commits into
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Make HOURS_VALUES a host array to avoid import-time GPU preallocation#13hmgaudecker wants to merge 3 commits into
hmgaudecker wants to merge 3 commits into
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The module-level `HOURS_VALUES = jnp.array(...)` materialized on the default device at import. With XLA_PYTHON_CLIENT_PREALLOCATE=true that first array op reserves 95% of device 0 in every process that imports the model — including the MSM estimation's pytask orchestrator, which only `srun`s GPU ranks and must leave the devices free for them. The orchestrator thus starved the rank's pool reservation, surfacing as the device-0 OOM. Make HOURS_VALUES a host (NumPy) array, converted to JAX at the indexing sites where the value folds into the surrounding compiled function. No numerical change. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
…ery state The three leisure functions returned a raw `time_endowment - losses` with no floor, so once work costs reached the endowment leisure went to zero or negative and fed a non-positive base into the CRRA aggregator (NaN utility), and the kink made the MSM objective non-smooth for the derivative-free optimizer. A shared `_smooth_leisure_floor` helper applies a scaled softplus (`smoothing * logaddexp(0, available / smoothing)`, smoothing = 1% of the endowment) so leisure bends smoothly to 0+ instead. It reduces to `available` in the bulk, so existing estimates are preserved; the fixed-cost/reentry parameters stay identified when the optimizer drives them high. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The softplus leisure floor keeps leisure strictly positive in every state-action cell, so the `positive_leisure` feasibility constraint never binds. Remove it from the canwork retiree/nongroup/tied regime builders and delete the unused `positive_leisure` helper; feasibility is now carried by the smooth floor in the leisure functions themselves. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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HOURS_VALUES = jnp.array(...)was a module-level JAX array: importing the model materialized it on the default device, and underXLA_PYTHON_CLIENT_PREALLOCATE=truethat first array op reserved 95% of device 0 in every importing process — including the MSM estimation's pytask orchestrator, which onlysruns GPU ranks and must leave the devices free. The orchestrator thus starved the rank's pool reservation (the device-0 OOM). Made it a host (NumPy) array, converted to JAX at the indexing sites. No numerical change.🤖 Generated with Claude Code