

"""simple docstring"""





from __future__ import annotations

def   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	if partitions <= 0:
		raise ValueError('''partitions must be a positive number!''' )
	if partitions > number_of_bytes:
		raise ValueError('''partitions can not > number_of_bytes!''' )
	lowerCAmelCase__	:						Optional[Any]  				=	number_of_bytes // partitions
	lowerCAmelCase__	:						Union[str, Any]  				=	[]
	for i in range(A_ ):
		lowerCAmelCase__	:						int  				=	i * bytes_per_partition + 1
		lowerCAmelCase__	:						Optional[Any]  				=	(
		    number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
		)
		allocation_list.append(f'{start_bytes}-{end_bytes}' )
	return allocation_list


if __name__ == "__main__":
							import doctest

							doctest.testmod()







"""simple docstring"""





import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
__UpperCamelCase  :      Any							      =		logging.getLogger(__name__)

if __name__ == "__main__":
							__UpperCamelCase  :      Union[str, Any]							      =		argparse.ArgumentParser(
							    description='''Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)'''
							)
							parser.add_argument(
							    '''--data_file''', type=str, default='''data/dump.bert-base-uncased.pickle''', help='''The binarized dataset.'''
							)
							parser.add_argument(
							    '''--token_counts_dump''', type=str, default='''data/token_counts.bert-base-uncased.pickle''', help='''The dump file.'''
							)
							parser.add_argument('''--vocab_size''', default=3_0_5_2_2, type=int)
							__UpperCamelCase  :      Any							      =		parser.parse_args()

							logger.info(F'''Loading data from {args.data_file}''')
							with open(args.data_file, '''rb''') as fp:
														__UpperCamelCase  :      List[Any]							      =		pickle.load(fp)

							logger.info('''Counting occurrences for MLM.''')
							__UpperCamelCase  :      Dict							      =		Counter()
							for tk_ids in data:
														counter.update(tk_ids)
							__UpperCamelCase  :      Optional[Any]							      =		[0] * args.vocab_size
							for k, v in counter.items():
														__UpperCamelCase  :      Dict							      =		v

							logger.info(F'''Dump to {args.token_counts_dump}''')
							with open(args.token_counts_dump, '''wb''') as handle:
														pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)




