i_*SSKJr SSKJrJr SSjrg))tqdm)ProcessPoolExecutor as_completedc US:a*USUVs/sHoS(aU"S0UD6OU"U5PM nnO/nUS:Xa6U[XS5Vs/sHnU(aU"S0UD6OU"U5PM sn-$[US9nU(a%XSVs/sHoWR"U40UD6PM nnO"XSVs/sHoWRX5PM nn[U5SSSS.n [[ U540U D6Hn M SSS5 /n [[ W55H%upU R U R55 M' Xk-$s snfs snfs snfs snf!,(df  Ne=f![anU R U5 SnAMsSnAff=f) aQ A parallel version of the map function with a progress bar. Args: array (array-like): An array to iterate over. function (function): A python function to apply to the elements of array n_jobs (int, default=16): The number of cores to use use_kwargs (boolean, default=False): Whether to consider the elements of array as dictionaries of keyword arguments to function front_num (int, default=3): The number of iterations to run serially before kicking off the parallel job. Useful for catching bugs Returns: [function(array[0]), function(array[1]), ...] rN) max_workersitT)totalunit unit_scaleleave) rrsubmitlenr enumerateappendresult Exception)arrayfunctionn_jobs use_kwargs front_numafrontpoolfutureskwargsfoutifuturees q/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddleocr/ppstructure/table/table_metric/parallel.pyparallel_processr%s1}BG BS BSQZHMqMXa[ 8BS   {% +, ,(HMqMXa[ 8,    0D ;@;LM;La{{81q1;LGMG9>z9JK9JA{{8/9JGK\  l7+6v6A 7 1 C)G,-   JJv}} '. ;E  NK 1 0(  JJqMM sM D> !E8EE" E+E .EE# E E # F -FF N)Fr)rconcurrent.futuresrrr%rr$r)s@2r(