





def 					lowerCAmelCase_			(	__a		)					->		Optional[Any]:







  """simple docstring"""





  lowerCamelCase__:				str        =[0] * len(__a		)
  lowerCamelCase__:				Dict        =[]
  lowerCamelCase__:				List[Any]        =[]
  lowerCamelCase__:				int        =0

  for values in graph.values():
    for i in values:
      indegree[i] += 1

  for i in range(len(__a		)		):
    if indegree[i] == 0:
      queue.append(__a		)

  while queue:
    lowerCamelCase__:				Optional[int]        =queue.pop(0		)
    cnt += 1
    topo.append(__a		)
    for x in graph[vertex]:
      indegree[x] -= 1
      if indegree[x] == 0:
        queue.append(__a		)

  if cnt != len(__a		):
    print("Cycle exists"		)
  else:
    print(__a		)


# Adjacency List of Graph
__A     =    {0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}






topological_sort(graph)








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
)
__A     =    logging.getLogger(__name__)

if __name__ == "__main__":
     __A     =    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_0522, type=int)
     __A     =    parser.parse_args()

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

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

