






"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


UpperCAmelCase_   : Any   			= logging.get_logger(__name__)




class 							lowerCAmelCase__				(			UpperCAmelCase__ ):






      '''simple docstring'''

      def __init__(						self     :  Union[str, Any]						,	*lowercase_     :  List[str]						,	**lowercase_     :  List[str]):




          '''simple docstring'''


          warnings.warn(
              '''The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
              ''' Please use SegformerImageProcessor instead.'''						,	lowercase_						,	)
          super().__init__(*lowercase_						,	**lowercase_)










"""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_   : Dict   			= logging.getLogger(__name__)

if __name__ == "__main__":
  UpperCAmelCase_   : List[str]   			= 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=30522, type=int)
  UpperCAmelCase_   : Optional[Any]   			= parser.parse_args()

  logger.info(f'''Loading data from {args.data_file}''')
  with open(args.data_file, """rb""") as fp:
    UpperCAmelCase_   : Union[str, Any]   			= pickle.load(fp)

  logger.info("""Counting occurrences for MLM.""")
  UpperCAmelCase_   : Any   			= Counter()
  for tk_ids in data:
    counter.update(tk_ids)
  UpperCAmelCase_   : List[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)


