"""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:
   SCREAMING_SNAKE_CASE__:List[str]			=	None


SCREAMING_SNAKE_CASE__:Dict			=	logging.get_logger(__name__)


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

SCREAMING_SNAKE_CASE__:List[Any]			=	{
    """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""",
    },
}

SCREAMING_SNAKE_CASE__:Tuple			=	{
    """facebook/mbart-large-en-ro""": 1024,
    """facebook/mbart-large-cc25""": 1024,
}

# fmt: off
SCREAMING_SNAKE_CASE__:Optional[Any]			=	["""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 				snake_case__     (   snake_case_   ):
 _snake_case   :			int           =		VOCAB_FILES_NAMES
 _snake_case   :			List[str]           =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _snake_case   :			Any           =		PRETRAINED_VOCAB_FILES_MAP
 _snake_case   :			Dict           =		["""input_ids""", """attention_mask"""]
 _snake_case   :			Optional[Any]           =		MBartTokenizer

 _snake_case   :			List[int]           =		[]
 _snake_case   :			List[int]           =		[]


 def __init__(				self  ,						lowerCamelCase=None  ,						lowerCamelCase=None  ,						lowerCamelCase="<s>"  ,						lowerCamelCase="</s>"  ,						lowerCamelCase="</s>"  ,						lowerCamelCase="<s>"  ,						lowerCamelCase="<unk>"  ,						lowerCamelCase="<pad>"  ,						lowerCamelCase="<mask>"  ,						lowerCamelCase=None  ,						lowerCamelCase=None  ,						lowerCamelCase=None  ,						**lowerCamelCase  ,						):
        # Mask token behave like a normal word, i.e. include the space before it
        __a     				=  AddedToken(lowerCamelCase  ,						lstrip=lowerCamelCase  ,						rstrip=lowerCamelCase		) if isinstance(lowerCamelCase  ,						lowerCamelCase		) else mask_token

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

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

        __a     				=  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}		)
        __a     				=  {
            lang_code: self.convert_tokens_to_ids(lowerCamelCase		) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        __a     				=  src_lang if src_lang is not None else "en_XX"
        __a     				=  self.convert_tokens_to_ids(self._src_lang		)
        __a     				=  tgt_lang
        self.set_src_lang_special_tokens(self._src_lang		)


 @property
 def 		a__ (				self		):
        return self._src_lang


 @src_lang.setter
 def 		a__ (				self  ,						lowerCamelCase		):
        __a     				=  new_src_lang
        self.set_src_lang_special_tokens(self._src_lang		)


 def 		a__ (				self  ,						lowerCamelCase  ,						lowerCamelCase = 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 		a__ (				self  ,						lowerCamelCase  ,						lowerCamelCase = None		):
        __a     				=  [self.sep_token_id]
        __a     				=  [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  ,						lowerCamelCase  ,						lowerCamelCase  ,						lowerCamelCase  ,						lowerCamelCase  ,						**lowerCamelCase		):
        if src_lang is None or tgt_lang is None:
               raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"		)
        __a     				=  src_lang
        __a     				=  self(lowerCamelCase  ,						add_special_tokens=lowerCamelCase  ,						return_tensors=lowerCamelCase  ,						**lowerCamelCase		)
        __a     				=  self.convert_tokens_to_ids(lowerCamelCase		)
        __a     				=  tgt_lang_id
        return inputs


 def 		a__ (				self  ,						lowerCamelCase  ,						lowerCamelCase = "en_XX"  ,						lowerCamelCase = None  ,						lowerCamelCase = "ro_RO"  ,						**lowerCamelCase  ,						):
        __a     				=  src_lang
        __a     				=  tgt_lang
        return super().prepare_seqaseq_batch(lowerCamelCase  ,						lowerCamelCase  ,						**lowerCamelCase		)


 def 		a__ (				self		):
        return self.set_src_lang_special_tokens(self.src_lang		)


 def 		a__ (				self		):
        return self.set_tgt_lang_special_tokens(self.tgt_lang		)


 def 		a__ (				self  ,						lowerCamelCase		):
        __a     				=  self.convert_tokens_to_ids(lowerCamelCase		)
        __a     				=  []
        __a     				=  [self.eos_token_id, self.cur_lang_code]

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

        __a     				=  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  ,						lowerCamelCase		):
        __a     				=  self.convert_tokens_to_ids(lowerCamelCase		)
        __a     				=  []
        __a     				=  [self.eos_token_id, self.cur_lang_code]

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

        __a     				=  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  ,						lowerCamelCase  ,						lowerCamelCase = 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(lowerCamelCase		):
               logger.error(F"Vocabulary path ({save_directory}) should be a directory."		)
               return
        __a     				=  os.path.join(
            lowerCamelCase  ,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)

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

        return (out_vocab_file,)

"""simple docstring"""



import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
SCREAMING_SNAKE_CASE__:Any			=	{
    """E""": 12.70,
    """T""": 9.06,
    """A""": 8.17,
    """O""": 7.51,
    """I""": 6.97,
    """N""": 6.75,
    """S""": 6.33,
    """H""": 6.09,
    """R""": 5.99,
    """D""": 4.25,
    """L""": 4.03,
    """C""": 2.78,
    """U""": 2.76,
    """M""": 2.41,
    """W""": 2.36,
    """F""": 2.23,
    """G""": 2.02,
    """Y""": 1.97,
    """P""": 1.93,
    """B""": 1.29,
    """V""": 0.98,
    """K""": 0.77,
    """J""": 0.15,
    """X""": 0.15,
    """Q""": 0.10,
    """Z""": 0.07,
}
SCREAMING_SNAKE_CASE__:Optional[int]			=	"""ETAOINSHRDLCUMWFGYPBVKJXQZ"""
SCREAMING_SNAKE_CASE__:Tuple			=	"""ABCDEFGHIJKLMNOPQRSTUVWXYZ"""



def 					_lowerCamelCase(					a							):
       __a     				=  {letter: 0 for letter in string.ascii_uppercase}
       for letter in message.upper():
              if letter in LETTERS:
                     letter_count[letter] += 1

       return letter_count



def 					_lowerCamelCase(					a							):
       return x[0]



def 					_lowerCamelCase(					a							):
       __a     				=  get_letter_count(a							)
       __a     				=  {
           freq: [] for letter, freq in letter_to_freq.items()
       }
       for letter in LETTERS:
              freq_to_letter[letter_to_freq[letter]].append(a							)

       __a     				=  {}

       for freq in freq_to_letter:
              freq_to_letter[freq].sort(key=ETAOIN.find ,  reverse=a							)
              __a     				=  "".join(freq_to_letter[freq]							)

       __a     				=  list(freq_to_letter_str.items()							)
       freq_pairs.sort(key=a ,  reverse=a							)

       __a     				=  [freq_pair[1] for freq_pair in freq_pairs]

       return "".join(a							)



def 					_lowerCamelCase(					a							):
       __a     				=  get_frequency_order(a							)
       __a     				=  0
       for common_letter in ETAOIN[:6]:
              if common_letter in freq_order[:6]:
                     match_score += 1

       for uncommon_letter in ETAOIN[-6:]:
              if uncommon_letter in freq_order[-6:]:
                     match_score += 1

       return match_score


if __name__ == "__main__":
   import doctest

   doctest.testmod()
