

'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCamelCase			:				Optional[Any] 			=					logging.get_logger(__name__)


lowerCamelCase			:				Any 			=					{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCamelCase			:				List[Any] 			=					{
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
}

lowerCamelCase			:				Union[str, Any] 			=					{
    'facebook/bart-base': 1_0_2_4,
    'facebook/bart-large': 1_0_2_4,
    'facebook/bart-large-mnli': 1_0_2_4,
    'facebook/bart-large-cnn': 1_0_2_4,
    'facebook/bart-large-xsum': 1_0_2_4,
    'yjernite/bart_eli5': 1_0_2_4,
}


@lru_cache()
def 	_lowerCAmelCase (						)				->      Optional[Any]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   =(
         list(range(ord('!'    )							,			ord('~'    ) + 1    )    ) + list(range(ord('¡'    )							,			ord('¬'    ) + 1    )    ) + list(range(ord('®'    )							,			ord('ÿ'    ) + 1    )    )
     )
     _SCREAMING_SNAKE_CASE							   =bs[:]
     _SCREAMING_SNAKE_CASE							   =0
     for b in range(2**8    ):
          if b not in bs:
               bs.append(UpperCAmelCase_    )
               cs.append(2**8 + n    )
               n += 1
     _SCREAMING_SNAKE_CASE							   =[chr(UpperCAmelCase_    ) for n in cs]
     return dict(zip(UpperCAmelCase_							,			UpperCAmelCase_    )    )


def 	_lowerCAmelCase (						_UpperCamelCase						:					Optional[int]    )				->      List[Any]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   =set()
     _SCREAMING_SNAKE_CASE							   =word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)    )
          _SCREAMING_SNAKE_CASE							   =char
     return pairs







class 							A__   (	_lowerCamelCase  ):
  A__					=    VOCAB_FILES_NAMES
  A__					=    PRETRAINED_VOCAB_FILES_MAP
  A__					=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A__					=    ['input_ids', 'attention_mask']





  def __init__(		self				:     List[Any]							, _a				:     List[Any]							, _a				:     List[str]							, _a				:     str="replace"							, _a				:     Optional[Any]="<s>"							, _a				:     Tuple="</s>"							, _a				:     int="</s>"							, _a				:     Any="<s>"							, _a				:     List[str]="<unk>"							, _a				:     Dict="<pad>"							, _a				:     Optional[Any]="<mask>"							, _a				:     List[Any]=False							, **_a				:     Optional[int]							, )     ->   Optional[Any]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							   =AddedToken(_a							, lstrip=_a							, rstrip=_a			) if isinstance(_a							, _a			) else bos_token
       _SCREAMING_SNAKE_CASE							   =AddedToken(_a							, lstrip=_a							, rstrip=_a			) if isinstance(_a							, _a			) else eos_token
       _SCREAMING_SNAKE_CASE							   =AddedToken(_a							, lstrip=_a							, rstrip=_a			) if isinstance(_a							, _a			) else sep_token
       _SCREAMING_SNAKE_CASE							   =AddedToken(_a							, lstrip=_a							, rstrip=_a			) if isinstance(_a							, _a			) else cls_token
       _SCREAMING_SNAKE_CASE							   =AddedToken(_a							, lstrip=_a							, rstrip=_a			) if isinstance(_a							, _a			) else unk_token
       _SCREAMING_SNAKE_CASE							   =AddedToken(_a							, lstrip=_a							, rstrip=_a			) if isinstance(_a							, _a			) else pad_token

       # Mask token behave like a normal word, i.e. include the space before it
       _SCREAMING_SNAKE_CASE							   =AddedToken(_a							, lstrip=_a							, rstrip=_a			) if isinstance(_a							, _a			) else mask_token

       super().__init__(
           errors=_a							, bos_token=_a							, eos_token=_a							, unk_token=_a							, sep_token=_a							, cls_token=_a							, pad_token=_a							, mask_token=_a							, add_prefix_space=_a							, **_a							, )

       with open(_a							, encoding='utf-8'			) as vocab_handle:
            _SCREAMING_SNAKE_CASE							   =json.load(_a			)
       _SCREAMING_SNAKE_CASE							   ={v: k for k, v in self.encoder.items()}
       _SCREAMING_SNAKE_CASE							   =errors  # how to handle errors in decoding
       _SCREAMING_SNAKE_CASE							   =bytes_to_unicode()
       _SCREAMING_SNAKE_CASE							   ={v: k for k, v in self.byte_encoder.items()}
       with open(_a							, encoding='utf-8'			) as merges_handle:
            _SCREAMING_SNAKE_CASE							   =merges_handle.read().split('\n'			)[1:-1]
       _SCREAMING_SNAKE_CASE							   =[tuple(merge.split()			) for merge in bpe_merges]
       _SCREAMING_SNAKE_CASE							   =dict(zip(_a							, range(len(_a			)			)			)			)
       _SCREAMING_SNAKE_CASE							   ={}
       _SCREAMING_SNAKE_CASE							   =add_prefix_space

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       _SCREAMING_SNAKE_CASE							   =re.compile(r'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'			)





  @property
  def 						A  (		self				:     int			)     ->   Dict:





       '''simple docstring'''






       return len(self.encoder			)





  def 						A  (		self				:     Tuple			)     ->   Optional[int]:





       '''simple docstring'''






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





  def 						A  (		self				:     str							, _a				:     Union[str, Any]			)     ->   Union[str, Any]:





       '''simple docstring'''






       if token in self.cache:
            return self.cache[token]
       _SCREAMING_SNAKE_CASE							   =tuple(_a			)
       _SCREAMING_SNAKE_CASE							   =get_pairs(_a			)

       if not pairs:
            return token

       while True:
            _SCREAMING_SNAKE_CASE							   =min(_a							, key=lambda _a			: self.bpe_ranks.get(_a							, float('inf'			)			)			)
            if bigram not in self.bpe_ranks:
                 break
            _SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE							   =bigram
            _SCREAMING_SNAKE_CASE							   =[]
            _SCREAMING_SNAKE_CASE							   =0
            while i < len(_a			):
                 try:
                      _SCREAMING_SNAKE_CASE							   =word.index(_a							, _a			)
                 except ValueError:
                      new_word.extend(word[i:]			)
                      break
                 else:
                      new_word.extend(word[i:j]			)
                      _SCREAMING_SNAKE_CASE							   =j

                 if word[i] == first and i < len(_a			) - 1 and word[i + 1] == second:
                      new_word.append(first + second			)
                      i += 2
                 else:
                      new_word.append(word[i]			)
                      i += 1
            _SCREAMING_SNAKE_CASE							   =tuple(_a			)
            _SCREAMING_SNAKE_CASE							   =new_word
            if len(_a			) == 1:
                 break
            else:
                 _SCREAMING_SNAKE_CASE							   =get_pairs(_a			)
       _SCREAMING_SNAKE_CASE							   =' '.join(_a			)
       _SCREAMING_SNAKE_CASE							   =word
       return word





  def 						A  (		self				:     Tuple							, _a				:     int			)     ->   Dict:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							   =[]
       for token in re.findall(self.pat							, _a			):
            _SCREAMING_SNAKE_CASE							   =''.join(
                self.byte_encoder[b] for b in token.encode('utf-8'			)			)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
            bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_a			).split(' '			)			)
       return bpe_tokens





  def 						A  (		self				:     Dict							, _a				:     Optional[int]			)     ->   List[str]:





       '''simple docstring'''






       return self.encoder.get(_a							, self.encoder.get(self.unk_token			)			)





  def 						A  (		self				:     List[Any]							, _a				:     List[Any]			)     ->   List[str]:





       '''simple docstring'''






       return self.decoder.get(_a			)





  def 						A  (		self				:     Optional[Any]							, _a				:     Tuple			)     ->   Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							   =''.join(_a			)
       _SCREAMING_SNAKE_CASE							   =bytearray([self.byte_decoder[c] for c in text]			).decode('utf-8'							, errors=self.errors			)
       return text





  def 						A  (		self				:     List[str]							, _a				:     str							, _a				:     Optional[str] = None			)     ->   Union[str, Any]:





       '''simple docstring'''






       if not os.path.isdir(_a			):
            logger.error(f"Vocabulary path ({save_directory}) should be a directory"			)
            return
       _SCREAMING_SNAKE_CASE							   =os.path.join(
           _a							, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)
       _SCREAMING_SNAKE_CASE							   =os.path.join(
           _a							, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']			)

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

       _SCREAMING_SNAKE_CASE							   =0
       with open(_a							, 'w'							, encoding='utf-8'			) as writer:
            writer.write('#version: 0.2\n'			)
            for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							, key=lambda _a			: kv[1]			):
                 if index != token_index:
                      logger.warning(
                          f"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
                          ' Please check that the tokenizer is not corrupted!'			)
                      _SCREAMING_SNAKE_CASE							   =token_index
                 writer.write(' '.join(_a			) + '\n'			)
                 index += 1

       return vocab_file, merge_file





  def 						A  (		self				:     Union[str, Any]							, _a				:     List[int]							, _a				:     Optional[List[int]] = None			)     ->   Tuple:





       '''simple docstring'''






       if token_ids_a is None:
            return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       _SCREAMING_SNAKE_CASE							   =[self.cls_token_id]
       _SCREAMING_SNAKE_CASE							   =[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep





  def 						A  (		self				:     List[str]							, _a				:     List[int]							, _a				:     Optional[List[int]] = None							, _a				:     bool = False			)     ->   Tuple:





       '''simple docstring'''






       if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=_a							, token_ids_a=_a							, already_has_special_tokens=_a			)

       if token_ids_a is None:
            return [1] + ([0] * len(_a			)) + [1]
       return [1] + ([0] * len(_a			)) + [1, 1] + ([0] * len(_a			)) + [1]





  def 						A  (		self				:     Dict							, _a				:     List[int]							, _a				:     Optional[List[int]] = None			)     ->   int:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							   =[self.sep_token_id]
       _SCREAMING_SNAKE_CASE							   =[self.cls_token_id]

       if token_ids_a is None:
            return len(cls + token_ids_a + sep			) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep			) * [0]





  def 						A  (		self				:     List[str]							, _a				:     Optional[int]							, _a				:     Tuple=False							, **_a				:     List[Any]			)     ->   Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							   =kwargs.pop('add_prefix_space'							, self.add_prefix_space			)
       if (is_split_into_words or add_prefix_space) and (len(_a			) > 0 and not text[0].isspace()):
            _SCREAMING_SNAKE_CASE							   =' ' + text
       return (text, kwargs)



'''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
)
lowerCamelCase			:				int 			=					logging.getLogger(__name__)

if __name__ == "__main__":
     lowerCamelCase			:				Optional[Any] 			=					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_0_5_2_2, type=int)
     lowerCamelCase			:				Optional[Any] 			=					parser.parse_args()

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

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