Fix seed parameter TypeError in BaseDRLearner bootstrap CI (#857)#879
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mohsinm-dev wants to merge 1 commit intouber:masterfrom
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Fix seed parameter TypeError in BaseDRLearner bootstrap CI (#857)#879mohsinm-dev wants to merge 1 commit intouber:masterfrom
mohsinm-dev wants to merge 1 commit intouber:masterfrom
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Remove stray seed=seed argument passed to bootstrap() which did not accept it, causing TypeError when bootstrap_ci=True. Add local RNG-based seeding for reproducible bootstrap CI in both estimate_ate() and fit_predict() without mutating global numpy state. Override bootstrap() in BaseDRLearner to thread per-iteration seeds into fit() for deterministic cross-fitting.
jeongyoonlee
requested changes
Feb 24, 2026
| bootstrap_ci=True, | ||
| n_bootstraps=10, | ||
| bootstrap_size=200, | ||
| seed=42, |
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Let's use from .const import RANDOM_SEED instead.
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Fixes #857
BaseDRLearner.estimate_ate()passedseed=seedtoself.bootstrap(), which doesn't accept that parameter — raisingTypeErrorwheneverbootstrap_ci=True.Changes:
seed=seedfrom bootstrap callseedcontrols bootstrap reproducibility without mutating global numpy statebootstrap()inBaseDRLearnerto pass per-iteration seeds intofit()for deterministic cross-fittingfit_predict(return_ci=True)pathTests:
TypeError