
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
)
_snake_case      = logging.getLogger(__name__)

if __name__ == "__main__":
 _snake_case      = 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=30_522, type=int)
 _snake_case      = parser.parse_args()

 logger.info(F"Loading data from {args.data_file}")
 with open(args.data_file, '''rb''') as fp:
  _snake_case      = pickle.load(fp)

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




from __future__ import annotations

from collections import Counter
from random import random
class       _lowerCAmelCase  :

 """simple docstring"""

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






      """simple docstring"""



      UpperCamelCase						    =					{}

 def      __lowerCAmelCase  (						self			:			Tuple					, SCREAMING_SNAKE_CASE__			:			str   ):






      """simple docstring"""



      UpperCamelCase						    =					{}

 def      __lowerCAmelCase  (						self			:			Optional[Any]					, SCREAMING_SNAKE_CASE__			:			str					, SCREAMING_SNAKE_CASE__			:			str					, SCREAMING_SNAKE_CASE__			:			float   ):






      """simple docstring"""



      if nodea not in self.connections:
           self.add_node(SCREAMING_SNAKE_CASE__   )
      if nodea not in self.connections:
           self.add_node(SCREAMING_SNAKE_CASE__   )
      UpperCamelCase						    =					probability

 def      __lowerCAmelCase  (						self			:			str   ):






      """simple docstring"""



      return list(self.connections   )






 def      __lowerCAmelCase  (						self			:			Any					, SCREAMING_SNAKE_CASE__			:			str   ):






      """simple docstring"""



      UpperCamelCase						    =					0
      UpperCamelCase						    =					random()

      for dest in self.connections[node]:
           current_probability += self.connections[node][dest]
           if current_probability > random_value:
                return dest
      return ""




def  __lowerCamelCase					( _lowercase						,     _lowercase						,     _lowercase			)       ->      dict[str, int]:
     UpperCamelCase						    =					MarkovChainGraphUndirectedUnweighted()

     for nodea, nodea, probability in transitions:
          graph.add_transition_probability(_lowercase						,     _lowercase						,     _lowercase			)

     UpperCamelCase						    =					Counter(graph.get_nodes()			)
     UpperCamelCase						    =					start

     for _ in range(_lowercase			):
          UpperCamelCase						    =					graph.transition(_lowercase			)
          visited[node] += 1

     return visited


if __name__ == "__main__":
 import doctest

 doctest.testmod()


