


"""simple docstring"""



import json
import os
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__snake_case             =   logging.get_logger(__name__)

__snake_case             =   {"""vocab_file""": """vocab.json"""}

__snake_case             =   {
    """vocab_file""": {
        """mgp-str""": """https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json""",
    }
}

__snake_case             =   {"""mgp-str""": 27}







class _lowerCAmelCase    (				__UpperCamelCase     ):
   __UpperCAmelCase			:	Optional[Any]							  =  VOCAB_FILES_NAMES
   __UpperCAmelCase			:	str							  =  PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase			:	Union[str, Any]							  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES







   def __init__(     self						,     UpperCamelCase__						,     UpperCamelCase__="[GO]"						,     UpperCamelCase__="[GO]"						,     UpperCamelCase__="[s]"						,     UpperCamelCase__="[GO]"						,     **UpperCamelCase__						)     ->		int:

          '''simple docstring'''




          super().__init__(
              unk_token=_lowerCAmelCase						,     bos_token=_lowerCAmelCase						,     eos_token=_lowerCAmelCase						,     pad_token=_lowerCAmelCase						,     **_lowerCAmelCase						,     )

          with open(_lowerCAmelCase						,     encoding="utf-8"						) as vocab_handle:
                 snake_case   :				str				 =   json.load(_lowerCAmelCase						)
          snake_case   :				Dict				 =   {v: k for k, v in self.vocab.items()}







   @property
   def 			lowerCamelCase		(     self						)     ->		Optional[int]:

          '''simple docstring'''




          return len(self.vocab						)







   def 			lowerCamelCase		(     self						)     ->		Tuple:

          '''simple docstring'''




          return dict(self.vocab						,     **self.added_tokens_encoder						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		Optional[int]:

          '''simple docstring'''




          snake_case   :				List[Any]				 =   []
          for s in text:
                 char_tokens.extend(_lowerCAmelCase						)
          return char_tokens







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		Dict:

          '''simple docstring'''




          return self.vocab.get(_lowerCAmelCase						,     self.vocab.get(self.unk_token						)						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		Dict:

          '''simple docstring'''




          return self.decoder.get(_lowerCAmelCase						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						,     UpperCamelCase__ = None						)     ->		Dict:

          '''simple docstring'''




          if not os.path.isdir(_lowerCAmelCase						):
                 logger.error("Vocabulary path ({}) should be a directory".format(_lowerCAmelCase						)						)
                 return
          snake_case   :				Union[str, Any]				 =   os.path.join(
              _lowerCAmelCase						,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

          with open(_lowerCAmelCase						,     "w"						,     encoding="utf-8"						) as f:
                 f.write(json.dumps(self.vocab						,     indent=2						,     sort_keys=_lowerCAmelCase						,     ensure_ascii=_lowerCAmelCase						) + "\n"						)

          return (vocab_file,)









"""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
)
__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=30522, 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)





