




import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple

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


lowerCamelCase    :		List[str]			   =       logging.get_logger(__name__)

lowerCamelCase    :		str			   =       {
    "vocab_file": "vocab.txt",
    "merges_file": "bpe.codes",
}

lowerCamelCase    :		Union[str, Any]			   =       {
    "vocab_file": {
        "vinai/phobert-base": "https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt",
        "vinai/phobert-large": "https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt",
    },
    "merges_file": {
        "vinai/phobert-base": "https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes",
        "vinai/phobert-large": "https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes",
    },
}

lowerCamelCase    :		str			   =       {
    "vinai/phobert-base": 256,
    "vinai/phobert-large": 256,
}

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	str					):


						'''simple docstring'''



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

						lowerCamelCase_							=   set(_lowerCamelCase					)
						return pairs







class   A(						__lowercase       ):



	'''simple docstring'''


	UpperCamelCase						       =						VOCAB_FILES_NAMES
	UpperCamelCase						       =						PRETRAINED_VOCAB_FILES_MAP
	UpperCamelCase						       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

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

							"""simple docstring"""






							super().__init__(
							    bos_token=A_						,							eos_token=A_						,							unk_token=A_						,							sep_token=A_						,							cls_token=A_						,							pad_token=A_						,							mask_token=A_						,							**A_						,							)

							lowerCamelCase_							=   vocab_file
							lowerCamelCase_							=   merges_file

							lowerCamelCase_							=   {}
							lowerCamelCase_							=   0
							lowerCamelCase_							=   1
							lowerCamelCase_							=   2
							lowerCamelCase_							=   3

							self.add_from_file(A_  )

							lowerCamelCase_							=   {v: k for k, v in self.encoder.items()}

							with open(A_						,							encoding='utf-8'  ) as merges_handle:
													lowerCamelCase_							=   merges_handle.read().split('\n'  )[:-1]
							lowerCamelCase_							=   [tuple(merge.split()[:-1]  ) for merge in merges]
							lowerCamelCase_							=   dict(zip(A_						,							range(len(A_  )  )  )  )
							lowerCamelCase_							=   {}

	def     a__			(    self :  str						,							A_ :  List[int]						,							A_ :  Optional[List[int]] = None  )       ->     List[int]:

							"""simple docstring"""






							if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							lowerCamelCase_							=   [self.cls_token_id]
							lowerCamelCase_							=   [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  )       ->     List[int]:

							"""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 :  Any						,							A_ :  List[int]						,							A_ :  Optional[List[int]] = None  )       ->     List[int]:

							"""simple docstring"""






							lowerCamelCase_							=   [self.sep_token_id]
							lowerCamelCase_							=   [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]

	@property
	def     a__			(    self :  List[Any]  )       ->     int:

							"""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 :  int						,							A_ :  List[Any]  )       ->     Dict:

							"""simple docstring"""






							if token in self.cache:
													return self.cache[token]
							lowerCamelCase_							=   tuple(A_  )
							lowerCamelCase_							=   tuple(list(word[:-1]  ) + [word[-1] + '</w>']  )
							lowerCamelCase_							=   get_pairs(A_  )

							if not pairs:
													return token

							while True:
													lowerCamelCase_							=   min(A_						,							key=lambda A_  : self.bpe_ranks.get(A_						,							float('inf'  )  )  )
													if bigram not in self.bpe_ranks:
																			break
													lowerCamelCase_							=   bigram
													lowerCamelCase_							=   []
													lowerCamelCase_							=   0
													while i < len(A_  ):
																			try:
																									lowerCamelCase_							=   word.index(A_						,							A_  )
																			except ValueError:
																									new_word.extend(word[i:]  )
																									break
																			else:
																									new_word.extend(word[i:j]  )
																									lowerCamelCase_							=   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
													lowerCamelCase_							=   tuple(A_  )
													lowerCamelCase_							=   new_word
													if len(A_  ) == 1:
																			break
													else:
																			lowerCamelCase_							=   get_pairs(A_  )
							lowerCamelCase_							=   """@@ """.join(A_  )
							lowerCamelCase_							=   word[:-4]
							lowerCamelCase_							=   word
							return word

	def     a__			(    self :  List[str]						,							A_ :  List[Any]  )       ->     Optional[Any]:

							"""simple docstring"""






							lowerCamelCase_							=   []

							lowerCamelCase_							=   re.findall(r'\S+\n?'						,							A_  )

							for token in words:
													split_tokens.extend(list(self.bpe(A_  ).split(' '  )  )  )
							return split_tokens

	def     a__			(    self :  str						,							A_ :  Optional[int]  )       ->     str:

							"""simple docstring"""






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

	def     a__			(    self :  Any						,							A_ :  List[Any]  )       ->     List[Any]:

							"""simple docstring"""






							return self.decoder.get(A_						,							self.unk_token  )

	def     a__			(    self :  int						,							A_ :  Optional[Any]  )       ->     List[Any]:

							"""simple docstring"""






							lowerCamelCase_							=   """ """.join(A_  ).replace('@@ '						,							''  ).strip()
							return out_string

	def     a__			(    self :  Optional[Any]						,							A_ :  str						,							A_ :  Optional[str] = None  )       ->     Tuple[str]:

							"""simple docstring"""






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

							if os.path.abspath(self.vocab_file  ) != os.path.abspath(A_  ):
													copyfile(self.vocab_file						,							A_  )

							if os.path.abspath(self.merges_file  ) != os.path.abspath(A_  ):
													copyfile(self.merges_file						,							A_  )

							return out_vocab_file, out_merge_file





	def     a__			(    self :  str						,							A_ :  Optional[int]  )       ->     Optional[int]:

							"""simple docstring"""






							if isinstance(A_						,							A_  ):
													try:
																			with open(A_						,							'r'						,							encoding='utf-8'  ) as fd:
																									self.add_from_file(A_  )
													except FileNotFoundError as fnfe:
																			raise fnfe
													except UnicodeError:
																			raise Exception(f"""Incorrect encoding detected in {f}, please rebuild the dataset"""  )
													return

							lowerCamelCase_							=   f.readlines()
							for lineTmp in lines:
													lowerCamelCase_							=   lineTmp.strip()
													lowerCamelCase_							=   line.rfind(' '  )
													if idx == -1:
																			raise ValueError('Incorrect dictionary format, expected \'<token> <cnt>\''  )
													lowerCamelCase_							=   line[:idx]
													lowerCamelCase_							=   len(self.encoder  )









import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

lowerCamelCase    :		Union[str, Any]			   =       logging.get_logger(__name__)


lowerCamelCase    :		str			   =       {name: getattr(transformers, name + "Fast") for name in SLOW_TO_FAST_CONVERTERS}

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	Any     ,							lowercase     :	str     ,							lowercase     :	int     ,							lowercase     :	List[Any]					):


      '''simple docstring'''



      if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
            raise ValueError(f"""Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys()					)}."""					)

      if tokenizer_name is None:
            lowerCamelCase_							=   TOKENIZER_CLASSES
      else:
            lowerCamelCase_							=   {tokenizer_name: getattr(lowercase     ,							tokenizer_name + 'Fast'					)}

      logger.info(f"""Loading tokenizer classes: {tokenizer_names}"""					)

      for tokenizer_name in tokenizer_names:
            lowerCamelCase_							=   TOKENIZER_CLASSES[tokenizer_name]

            lowerCamelCase_							=   True
            if checkpoint_name is None:
                  lowerCamelCase_							=   list(tokenizer_class.max_model_input_sizes.keys()					)
            else:
                  lowerCamelCase_							=   [checkpoint_name]

            logger.info(f"""For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}"""					)

            for checkpoint in checkpoint_names:
                  logger.info(f"""Loading {tokenizer_class.__class__.__name__} {checkpoint}"""					)

                  # Load tokenizer
                  lowerCamelCase_							=   tokenizer_class.from_pretrained(lowercase     ,							force_download=lowercase					)

                  # Save fast tokenizer
                  logger.info(f"""Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}"""					)

                  # For organization names we create sub-directories
                  if "/" in checkpoint:
                        lowerCamelCase_					,    lowerCamelCase_							=   checkpoint.split('/'					)
                        lowerCamelCase_							=   os.path.join(lowercase     ,							lowercase					)
                  elif add_prefix:
                        lowerCamelCase_							=   checkpoint
                        lowerCamelCase_							=   dump_path
                  else:
                        lowerCamelCase_							=   None
                        lowerCamelCase_							=   dump_path

                  logger.info(f"""=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}"""					)

                  if checkpoint in list(tokenizer.pretrained_vocab_files_map.values()					)[0]:
                        lowerCamelCase_							=   list(tokenizer.pretrained_vocab_files_map.values()					)[0][checkpoint]
                        lowerCamelCase_							=   file_path.split(lowercase					)[-1][0]
                        if next_char == "/":
                              lowerCamelCase_							=   os.path.join(lowercase     ,							lowercase					)
                              lowerCamelCase_							=   None

                        logger.info(f"""=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}"""					)

                  lowerCamelCase_							=   tokenizer.save_pretrained(
                      lowercase     ,							legacy_format=lowercase     ,							filename_prefix=lowercase					)
                  logger.info(f"""=> File names {file_names}"""					)

                  for file_name in file_names:
                        if not file_name.endswith('tokenizer.json'					):
                              os.remove(lowercase					)
                              logger.info(f"""=> removing {file_name}"""					)


if __name__ == "__main__":
 lowerCamelCase    :		Tuple			   =       argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     "--dump_path", default=None, type=str, required=True, help="Path to output generated fast tokenizer files."
 )
 parser.add_argument(
     "--tokenizer_name",
     default=None,
     type=str,
     help=(
         F"""Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will """
         "download and convert all the checkpoints from AWS."
     ),
 )
 parser.add_argument(
     "--checkpoint_name",
     default=None,
     type=str,
     help="Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.",
 )
 parser.add_argument(
     "--force_download",
     action="store_true",
     help="Re-download checkpoints.",
 )
 lowerCamelCase    :		Union[str, Any]			   =       parser.parse_args()

 convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)



