






"""simple docstring"""






from __future__ import annotations

from typing import Generic, TypeVar

UpperCAmelCase_   : List[str]   			= TypeVar("""T""")




class 							lowerCAmelCase__				(			Generic[T] ):






      '''simple docstring'''

      def __init__(						self     :  Tuple						,	lowercase_     :  T):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		data
          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		self
          SCREAMING_SNAKE_CASE_      :  int    						=		0




class 							lowerCAmelCase__				(			Generic[T] ):






      '''simple docstring'''

      def __init__(						self     :  Optional[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  dict[T, DisjointSetTreeNode[T]]    						=		{}
      def _SCREAMING_SNAKE_CASE (						self     :  Union[str, Any]						,	lowercase_     :  T):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  int    						=		DisjointSetTreeNode(lowercase_)
      def _SCREAMING_SNAKE_CASE (						self     :  int						,	lowercase_     :  T):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		self.map[data]
          if elem_ref != elem_ref.parent:
              SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		self.find_set(elem_ref.parent.data)
          return elem_ref.parent
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[Any]						,	lowercase_     :  DisjointSetTreeNode[T]						,	lowercase_     :  DisjointSetTreeNode[T]):




          '''simple docstring'''


          if nodea.rank > nodea.rank:
              SCREAMING_SNAKE_CASE_      :  Tuple    						=		nodea
          else:
              SCREAMING_SNAKE_CASE_      :  Any    						=		nodea
              if nodea.rank == nodea.rank:
                  nodea.rank += 1



      def _SCREAMING_SNAKE_CASE (						self     :  Dict						,	lowercase_     :  T						,	lowercase_     :  T):




          '''simple docstring'''


          self.link(self.find_set(lowercase_)						,	self.find_set(lowercase_))




class 							lowerCAmelCase__				(			Generic[T] ):






      '''simple docstring'''

      def __init__(						self     :  int):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  dict[T, dict[T, int]]    						=		{}
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[int]						,	lowercase_     :  T):




          '''simple docstring'''


          if node not in self.connections:
              SCREAMING_SNAKE_CASE_      :  Any    						=		{}
      def _SCREAMING_SNAKE_CASE (						self     :  List[Any]						,	lowercase_     :  T						,	lowercase_     :  T						,	lowercase_     :  int):




          '''simple docstring'''


          self.add_node(lowercase_)
          self.add_node(lowercase_)
          SCREAMING_SNAKE_CASE_      :  Dict    						=		weight
          SCREAMING_SNAKE_CASE_      :  Dict    						=		weight



      def _SCREAMING_SNAKE_CASE (						self     :  int):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Any    						=		[]
          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		set()
          for start in self.connections:
              for end in self.connections[start]:
                  if (start, end) not in seen:
                      seen.add((end, start))
                      edges.append((start, end, self.connections[start][end]))
          edges.sort(key=lambda lowercase_: x[2])

          # creating the disjoint set
          SCREAMING_SNAKE_CASE_      :  int    						=		DisjointSetTree[T]()
          for node in self.connections:
              disjoint_set.make_set(lowercase_)

          # MST generation
          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		0
          SCREAMING_SNAKE_CASE_      :  List[str]    						=		0
          SCREAMING_SNAKE_CASE_      :  Dict    						=		GraphUndirectedWeighted[T]()
          while num_edges < len(self.connections) - 1:
              SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		edges[index]
              index += 1
              SCREAMING_SNAKE_CASE_      :  Dict    						=		disjoint_set.find_set(lowercase_)
              SCREAMING_SNAKE_CASE_      :  List[Any]    						=		disjoint_set.find_set(lowercase_)
              if parent_u != parent_v:
                  num_edges += 1
                  graph.add_edge(lowercase_						,	lowercase_						,	lowercase_)
                  disjoint_set.union(lowercase_						,	lowercase_)
          return graph










"""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)


