U -e@sddlZddZdddZdS)Nc Cs|||}t|}t||}|dkr||}tt|ddd}|D]V}t||k\} tt| |} |j | | dd} || d7<|| 8}|dkrXqqX| tj S)aComputes approximate mode of multivariate hypergeometric. This is an approximation to the mode of the multivariate hypergeometric given by class_counts and n_draws. It shouldn't be off by more than one. It is the mostly likely outcome of drawing n_draws many samples from the population given by class_counts. Args ---------- class_counts : ndarray of int Population per class. n_draws : int Number of draws (samples to draw) from the overall population. rng : random state Used to break ties. Returns ------- sampled_classes : ndarray of int Number of samples drawn from each class. np.sum(sampled_classes) == n_draws rNF)sizereplace) sumnpfloorintsortuniquewhereminlenchoiceZastypeZint64) class_countsZn_drawsrngZ continuousZflooredZ need_to_add remaindervaluesvalueZindsZadd_nowrX/var/www/html/Darija-Ai-Train/env/lib/python3.8/site-packages/datasets/utils/stratify.pyapproximate_modes r c csNtj|dd\}}|jd}t|}t|dkrs2