





"""simple docstring"""


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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_mbart import MBartTokenizer
else:
		__magic_name__       :					List[Any]						=			None


__magic_name__       :					Optional[int]						=			logging.get_logger(__name__)


__magic_name__       :					Dict						=			{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

__magic_name__       :					Tuple						=			{
    """vocab_file""": {
        """facebook/mbart-large-en-ro""": (
            """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"""
        ),
        """facebook/mbart-large-cc25""": (
            """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """facebook/mbart-large-en-ro""": """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json""",
        """facebook/mbart-large-cc25""": """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json""",
    },
}

__magic_name__       :					Optional[int]						=			{
    """facebook/mbart-large-en-ro""": 1_0_2_4,
    """facebook/mbart-large-cc25""": 1_0_2_4,
}

# fmt: off
__magic_name__       :					int						=			["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN"""]






class 							lowercase__			(   __lowerCAmelCase	):

			"""simple docstring"""
			__lowerCAmelCase     :				int										=  VOCAB_FILES_NAMES
			__lowerCAmelCase     :				Any										=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__lowerCAmelCase     :				Union[str, Any]										=  PRETRAINED_VOCAB_FILES_MAP
			__lowerCAmelCase     :				List[str]										=  ['''input_ids''', '''attention_mask''']
			__lowerCAmelCase     :				Tuple										=  MBartTokenizer

			__lowerCAmelCase     :				List[int]										=  []
			__lowerCAmelCase     :				List[int]										=  []







			def __init__(      self						,   _A=None						,   _A=None						,   _A="<s>"						,   _A="</s>"						,   _A="</s>"						,   _A="<s>"						,   _A="<unk>"						,   _A="<pad>"						,   _A="<mask>"						,   _A=None						,   _A=None						,   _A=None						,   **_A						,   ):






									'''simple docstring'''







									UpperCamelCase				:		List[Any]				   =			AddedToken(_UpperCAmelCase						,   lstrip=_UpperCAmelCase						,   rstrip=_UpperCAmelCase    ) if isinstance(_UpperCAmelCase						,   _UpperCAmelCase    ) else mask_token

									super().__init__(
									    vocab_file=_UpperCAmelCase						,   tokenizer_file=_UpperCAmelCase						,   bos_token=_UpperCAmelCase						,   eos_token=_UpperCAmelCase						,   sep_token=_UpperCAmelCase						,   cls_token=_UpperCAmelCase						,   unk_token=_UpperCAmelCase						,   pad_token=_UpperCAmelCase						,   mask_token=_UpperCAmelCase						,   src_lang=_UpperCAmelCase						,   tgt_lang=_UpperCAmelCase						,   additional_special_tokens=_UpperCAmelCase						,   **_UpperCAmelCase						,   )

									UpperCamelCase				:		List[Any]				   =			vocab_file
									UpperCamelCase				:		str				   =			False if not self.vocab_file else True

									UpperCamelCase				:		Dict				   =			FAIRSEQ_LANGUAGE_CODES.copy()

									if additional_special_tokens is not None:
															# Only add those special tokens if they are not already there.
															_additional_special_tokens.extend(
															    [t for t in additional_special_tokens if t not in _additional_special_tokens]    )

									self.add_special_tokens({"""additional_special_tokens""": _additional_special_tokens}    )
									UpperCamelCase				:		List[Any]				   =			{
									    lang_code: self.convert_tokens_to_ids(_UpperCAmelCase    ) for lang_code in FAIRSEQ_LANGUAGE_CODES
									}

									UpperCamelCase				:		Tuple				   =			src_lang if src_lang is not None else """en_XX"""
									UpperCamelCase				:		Dict				   =			self.convert_tokens_to_ids(self._src_lang    )
									UpperCamelCase				:		Tuple				   =			tgt_lang
									self.set_src_lang_special_tokens(self._src_lang    )







			@property
			def   _a      (      self    ):






									'''simple docstring'''







									return self._src_lang







			@src_lang.setter
			def   _a      (      self						,   _A    ):






									'''simple docstring'''







									UpperCamelCase				:		Tuple				   =			new_src_lang
									self.set_src_lang_special_tokens(self._src_lang    )







			def   _a      (      self						,   _A						,   _A = None    ):






									'''simple docstring'''







									if token_ids_a is None:
															return self.prefix_tokens + token_ids_a + self.suffix_tokens
									# We don't expect to process pairs, but leave the pair logic for API consistency
									return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens







			def   _a      (      self						,   _A						,   _A = None    ):






									'''simple docstring'''







									UpperCamelCase				:		Any				   =			[self.sep_token_id]
									UpperCamelCase				:		Dict				   =			[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						,   _A						,   _A						,   _A						,   _A						,   **_A    ):






									'''simple docstring'''







									if src_lang is None or tgt_lang is None:
															raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""    )
									UpperCamelCase				:		str				   =			src_lang
									UpperCamelCase				:		str				   =			self(_UpperCAmelCase						,   add_special_tokens=_UpperCAmelCase						,   return_tensors=_UpperCAmelCase						,   **_UpperCAmelCase    )
									UpperCamelCase				:		Optional[Any]				   =			self.convert_tokens_to_ids(_UpperCAmelCase    )
									UpperCamelCase				:		Optional[int]				   =			tgt_lang_id
									return inputs







			def   _a      (      self						,   _A						,   _A = "en_XX"						,   _A = None						,   _A = "ro_RO"						,   **_A						,   ):






									'''simple docstring'''







									UpperCamelCase				:		str				   =			src_lang
									UpperCamelCase				:		Dict				   =			tgt_lang
									return super().prepare_seqaseq_batch(_UpperCAmelCase						,   _UpperCAmelCase						,   **_UpperCAmelCase    )







			def   _a      (      self    ):






									'''simple docstring'''







									return self.set_src_lang_special_tokens(self.src_lang    )







			def   _a      (      self    ):






									'''simple docstring'''







									return self.set_tgt_lang_special_tokens(self.tgt_lang    )







			def   _a      (      self						,   _A    ):






									'''simple docstring'''







									UpperCamelCase				:		Optional[int]				   =			self.convert_tokens_to_ids(_UpperCAmelCase    )
									UpperCamelCase				:		int				   =			[]
									UpperCamelCase				:		List[str]				   =			[self.eos_token_id, self.cur_lang_code]

									UpperCamelCase				:		int				   =			self.convert_ids_to_tokens(self.prefix_tokens    )
									UpperCamelCase				:		Dict				   =			self.convert_ids_to_tokens(self.suffix_tokens    )

									UpperCamelCase				:		Dict				   =			processors.TemplateProcessing(
									    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str						,   pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str						,   special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str						,   self.prefix_tokens + self.suffix_tokens    )    )						,   )







			def   _a      (      self						,   _A    ):






									'''simple docstring'''







									UpperCamelCase				:		Tuple				   =			self.convert_tokens_to_ids(_UpperCAmelCase    )
									UpperCamelCase				:		List[str]				   =			[]
									UpperCamelCase				:		Any				   =			[self.eos_token_id, self.cur_lang_code]

									UpperCamelCase				:		Optional[Any]				   =			self.convert_ids_to_tokens(self.prefix_tokens    )
									UpperCamelCase				:		List[Any]				   =			self.convert_ids_to_tokens(self.suffix_tokens    )

									UpperCamelCase				:		Tuple				   =			processors.TemplateProcessing(
									    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str						,   pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str						,   special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str						,   self.prefix_tokens + self.suffix_tokens    )    )						,   )







			def   _a      (      self						,   _A						,   _A = None    ):






									'''simple docstring'''







									if not self.can_save_slow_tokenizer:
															raise ValueError(
															    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
															    """tokenizer."""    )

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

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

									return (out_vocab_file,)









"""simple docstring"""

import argparse


a							      =     '''docs/source/_static/js/custom.js'''






def 		_snake_case	(   _snake_case				:   Dict				)       ->   Any:






      '''simple docstring'''


      with open(_snake_case							,    encoding='utf-8'							,    newline='\n'				) as f:
            _A     =  f.readlines()
      _A     =  0

      # First let's put the right version
      while not lines[index].startswith('const stableVersion ='				):
            index += 1
      _A     =  F'''const stableVersion = "v{version}"\n'''

      # Then update the dictionary
      while not lines[index].startswith('const versionMapping = {'				):
            index += 1

      # We go until the end
      while not lines[index].startswith('}'				):
            index += 1
      # We add the new version at the end
      lines[index - 1] += F'''    "v{version}": "v{version}",\n'''

      with open(_snake_case							,    'w'							,    encoding='utf-8'							,    newline='\n'				) as f:
            f.writelines(_snake_case				)


if __name__ == "__main__":
       a							      =     argparse.ArgumentParser()
       parser.add_argument('''--version''', help='''Release version.''')
       a							      =     parser.parse_args()
       update_custom_js(args.version)

