


"""simple docstring"""


import os

_snake_case          =							{"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1000}



def   snake_case						(				_a:     str							)->		int:
      '''simple docstring'''


      lowerCamelCase__           =		0

      lowerCamelCase__           =		0
      while index < len(_a							) - 1:
            lowerCamelCase__           =		SYMBOLS[numerals[index]]
            lowerCamelCase__           =		SYMBOLS[numerals[index + 1]]
            if current_value < next_value:
                  total_value -= current_value
            else:
                  total_value += current_value
            index += 1
      total_value += SYMBOLS[numerals[index]]

      return total_value



def   snake_case						(				_a:     int							)->		str:
      '''simple docstring'''


      lowerCamelCase__           =		''

      lowerCamelCase__           =		num // 1000
      numerals += m_count * "M"
      num %= 1000

      lowerCamelCase__           =		num // 100
      if c_count == 9:
            numerals += "CM"
            c_count -= 9
      elif c_count == 4:
            numerals += "CD"
            c_count -= 4
      if c_count >= 5:
            numerals += "D"
            c_count -= 5
      numerals += c_count * "C"
      num %= 100

      lowerCamelCase__           =		num // 10
      if x_count == 9:
            numerals += "XC"
            x_count -= 9
      elif x_count == 4:
            numerals += "XL"
            x_count -= 4
      if x_count >= 5:
            numerals += "L"
            x_count -= 5
      numerals += x_count * "X"
      num %= 10

      if num == 9:
            numerals += "IX"
            num -= 9
      elif num == 4:
            numerals += "IV"
            num -= 4
      if num >= 5:
            numerals += "V"
            num -= 5
      numerals += num * "I"

      return numerals



def   snake_case						(				_a:     str = "/p089_roman.txt"							)->		int:
      '''simple docstring'''


      lowerCamelCase__           =		0

      with open(os.path.dirname(_a							) + roman_numerals_filename							) as filea:
            lowerCamelCase__           =		filea.readlines()

      for line in lines:
            lowerCamelCase__           =		line.strip()
            lowerCamelCase__           =		parse_roman_numerals(_a							)
            lowerCamelCase__           =		generate_roman_numerals(_a							)
            savings += len(_a							) - len(_a							)

      return savings


if __name__ == "__main__":
   print(f"""{solution() = }""")







"""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_nllb import NllbTokenizer
else:
   _snake_case          =							None


_snake_case          =							logging.get_logger(__name__)


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

_snake_case          =							{
    "vocab_file": {
        "facebook/nllb-200-distilled-600M": (
            "https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/nllb-200-distilled-600M": (
            "https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/tokenizer.json"
        ),
    },
}

_snake_case          =							{
    "facebook/nllb-large-en-ro": 1024,
    "facebook/nllb-200-distilled-600M": 1024,
}

# fmt: off
_snake_case          =							["ace_Arab", "ace_Latn", "acm_Arab", "acq_Arab", "aeb_Arab", "afr_Latn", "ajp_Arab", "aka_Latn", "amh_Ethi", "apc_Arab", "arb_Arab", "ars_Arab", "ary_Arab", "arz_Arab", "asm_Beng", "ast_Latn", "awa_Deva", "ayr_Latn", "azb_Arab", "azj_Latn", "bak_Cyrl", "bam_Latn", "ban_Latn", "bel_Cyrl", "bem_Latn", "ben_Beng", "bho_Deva", "bjn_Arab", "bjn_Latn", "bod_Tibt", "bos_Latn", "bug_Latn", "bul_Cyrl", "cat_Latn", "ceb_Latn", "ces_Latn", "cjk_Latn", "ckb_Arab", "crh_Latn", "cym_Latn", "dan_Latn", "deu_Latn", "dik_Latn", "dyu_Latn", "dzo_Tibt", "ell_Grek", "eng_Latn", "epo_Latn", "est_Latn", "eus_Latn", "ewe_Latn", "fao_Latn", "pes_Arab", "fij_Latn", "fin_Latn", "fon_Latn", "fra_Latn", "fur_Latn", "fuv_Latn", "gla_Latn", "gle_Latn", "glg_Latn", "grn_Latn", "guj_Gujr", "hat_Latn", "hau_Latn", "heb_Hebr", "hin_Deva", "hne_Deva", "hrv_Latn", "hun_Latn", "hye_Armn", "ibo_Latn", "ilo_Latn", "ind_Latn", "isl_Latn", "ita_Latn", "jav_Latn", "jpn_Jpan", "kab_Latn", "kac_Latn", "kam_Latn", "kan_Knda", "kas_Arab", "kas_Deva", "kat_Geor", "knc_Arab", "knc_Latn", "kaz_Cyrl", "kbp_Latn", "kea_Latn", "khm_Khmr", "kik_Latn", "kin_Latn", "kir_Cyrl", "kmb_Latn", "kon_Latn", "kor_Hang", "kmr_Latn", "lao_Laoo", "lvs_Latn", "lij_Latn", "lim_Latn", "lin_Latn", "lit_Latn", "lmo_Latn", "ltg_Latn", "ltz_Latn", "lua_Latn", "lug_Latn", "luo_Latn", "lus_Latn", "mag_Deva", "mai_Deva", "mal_Mlym", "mar_Deva", "min_Latn", "mkd_Cyrl", "plt_Latn", "mlt_Latn", "mni_Beng", "khk_Cyrl", "mos_Latn", "mri_Latn", "zsm_Latn", "mya_Mymr", "nld_Latn", "nno_Latn", "nob_Latn", "npi_Deva", "nso_Latn", "nus_Latn", "nya_Latn", "oci_Latn", "gaz_Latn", "ory_Orya", "pag_Latn", "pan_Guru", "pap_Latn", "pol_Latn", "por_Latn", "prs_Arab", "pbt_Arab", "quy_Latn", "ron_Latn", "run_Latn", "rus_Cyrl", "sag_Latn", "san_Deva", "sat_Beng", "scn_Latn", "shn_Mymr", "sin_Sinh", "slk_Latn", "slv_Latn", "smo_Latn", "sna_Latn", "snd_Arab", "som_Latn", "sot_Latn", "spa_Latn", "als_Latn", "srd_Latn", "srp_Cyrl", "ssw_Latn", "sun_Latn", "swe_Latn", "swh_Latn", "szl_Latn", "tam_Taml", "tat_Cyrl", "tel_Telu", "tgk_Cyrl", "tgl_Latn", "tha_Thai", "tir_Ethi", "taq_Latn", "taq_Tfng", "tpi_Latn", "tsn_Latn", "tso_Latn", "tuk_Latn", "tum_Latn", "tur_Latn", "twi_Latn", "tzm_Tfng", "uig_Arab", "ukr_Cyrl", "umb_Latn", "urd_Arab", "uzn_Latn", "vec_Latn", "vie_Latn", "war_Latn", "wol_Latn", "xho_Latn", "ydd_Hebr", "yor_Latn", "yue_Hant", "zho_Hans", "zho_Hant", "zul_Latn"]



class   _a      (      SCREAMING_SNAKE_CASE_ ):
    a_    :				Any             =    VOCAB_FILES_NAMES
    a_    :				Optional[Any]             =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a_    :				Optional[Any]             =    PRETRAINED_VOCAB_FILES_MAP
    a_    :				List[str]             =    ['input_ids', 'attention_mask']
    a_    :				Union[str, Any]             =    NllbTokenizer

    a_    :				List[int]             =    []
    a_    :				List[int]             =    []
    def __init__( self							:					int							,					SCREAMING_SNAKE_CASE__							:					List[Any]=None							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=None							,					SCREAMING_SNAKE_CASE__							:					List[Any]="<s>"							,					SCREAMING_SNAKE_CASE__							:					List[str]="</s>"							,					SCREAMING_SNAKE_CASE__							:					Any="</s>"							,					SCREAMING_SNAKE_CASE__							:					List[str]="<s>"							,					SCREAMING_SNAKE_CASE__							:					Tuple="<unk>"							,					SCREAMING_SNAKE_CASE__							:					Optional[int]="<pad>"							,					SCREAMING_SNAKE_CASE__							:					Any="<mask>"							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=None							,					SCREAMING_SNAKE_CASE__							:					int=None							,					SCREAMING_SNAKE_CASE__							:					Dict=None							,					SCREAMING_SNAKE_CASE__							:					Tuple=False							,					**SCREAMING_SNAKE_CASE__							:					str							,					):
          # Mask token behave like a normal word, i.e. include the space before it
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else mask_token
          lowerCamelCase__           =		legacy_behaviour
          super().__init__(
              vocab_file=SCREAMING_SNAKE_CASE__							,					tokenizer_file=SCREAMING_SNAKE_CASE__							,					bos_token=SCREAMING_SNAKE_CASE__							,					eos_token=SCREAMING_SNAKE_CASE__							,					sep_token=SCREAMING_SNAKE_CASE__							,					cls_token=SCREAMING_SNAKE_CASE__							,					unk_token=SCREAMING_SNAKE_CASE__							,					pad_token=SCREAMING_SNAKE_CASE__							,					mask_token=SCREAMING_SNAKE_CASE__							,					src_lang=SCREAMING_SNAKE_CASE__							,					tgt_lang=SCREAMING_SNAKE_CASE__							,					additional_special_tokens=SCREAMING_SNAKE_CASE__							,					legacy_behaviour=SCREAMING_SNAKE_CASE__							,					**SCREAMING_SNAKE_CASE__							,					)

          lowerCamelCase__           =		vocab_file
          lowerCamelCase__           =		False if not self.vocab_file else True

          lowerCamelCase__           =		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}				)
          lowerCamelCase__           =		{
              lang_code: self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__				) for lang_code in FAIRSEQ_LANGUAGE_CODES
          }

          lowerCamelCase__           =		src_lang if src_lang is not None else 'eng_Latn'
          lowerCamelCase__           =		self.convert_tokens_to_ids(self._src_lang				)
          lowerCamelCase__           =		tgt_lang
          self.set_src_lang_special_tokens(self._src_lang				)
    @property
    def      _UpperCamelCase       ( self							:					str				):
          return self._src_lang
    @src_lang.setter
    def      _UpperCamelCase       ( self							:					int							,					SCREAMING_SNAKE_CASE__							:					str				):
          lowerCamelCase__           =		new_src_lang
          self.set_src_lang_special_tokens(self._src_lang				)
    def      _UpperCamelCase       ( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None				):
          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      _UpperCamelCase       ( self							:					Optional[Any]							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None				):
          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]
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					str							,					SCREAMING_SNAKE_CASE__							:					str							,					SCREAMING_SNAKE_CASE__							:					Optional[str]							,					SCREAMING_SNAKE_CASE__							:					Optional[str]							,					**SCREAMING_SNAKE_CASE__							:					Optional[int]				):
          if src_lang is None or tgt_lang is None:
                raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'				)
          lowerCamelCase__           =		src_lang
          lowerCamelCase__           =		self(SCREAMING_SNAKE_CASE__							,					add_special_tokens=SCREAMING_SNAKE_CASE__							,					return_tensors=SCREAMING_SNAKE_CASE__							,					**SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		tgt_lang_id
          return inputs
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					str = "eng_Latn"							,					SCREAMING_SNAKE_CASE__							:					Optional[List[str]] = None							,					SCREAMING_SNAKE_CASE__							:					str = "fra_Latn"							,					**SCREAMING_SNAKE_CASE__							:					Dict							,					):
          lowerCamelCase__           =		src_lang
          lowerCamelCase__           =		tgt_lang
          return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__							,					**SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					List[str]				):
          return self.set_src_lang_special_tokens(self.src_lang				)
    def      _UpperCamelCase       ( self							:					List[Any]				):
          return self.set_tgt_lang_special_tokens(self.tgt_lang				)
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]				):
          lowerCamelCase__           =		self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__				)

          if self.legacy_behaviour:
                lowerCamelCase__           =		[]
                lowerCamelCase__           =		[self.eos_token_id, self.cur_lang_code]
          else:
                lowerCamelCase__           =		[self.cur_lang_code]
                lowerCamelCase__           =		[self.eos_token_id]

          lowerCamelCase__           =		self.convert_ids_to_tokens(self.prefix_tokens				)
          lowerCamelCase__           =		self.convert_ids_to_tokens(self.suffix_tokens				)

          lowerCamelCase__           =		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      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					str				):
          lowerCamelCase__           =		self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__				)
          if self.legacy_behaviour:
                lowerCamelCase__           =		[]
                lowerCamelCase__           =		[self.eos_token_id, self.cur_lang_code]
          else:
                lowerCamelCase__           =		[self.cur_lang_code]
                lowerCamelCase__           =		[self.eos_token_id]

          lowerCamelCase__           =		self.convert_ids_to_tokens(self.prefix_tokens				)
          lowerCamelCase__           =		self.convert_ids_to_tokens(self.suffix_tokens				)

          lowerCamelCase__           =		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      _UpperCamelCase       ( self							:					Dict							,					SCREAMING_SNAKE_CASE__							:					str							,					SCREAMING_SNAKE_CASE__							:					Optional[str] = None				):
          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(SCREAMING_SNAKE_CASE__				):
                logger.error(F'Vocabulary path ({save_directory}) should be a directory.'				)
                return
          lowerCamelCase__           =		os.path.join(
              SCREAMING_SNAKE_CASE__							,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

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

          return (out_vocab_file,)



