



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:
    __UpperCAmelCase			  =			None


__UpperCAmelCase			  =			logging.get_logger(__name__)


__UpperCAmelCase			  =			{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

__UpperCAmelCase			  =			{
    '''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''',
    },
}

__UpperCAmelCase			  =			{
    '''facebook/mbart-large-en-ro''': 1_024,
    '''facebook/mbart-large-cc25''': 1_024,
}

# fmt: off
__UpperCAmelCase			  =			['''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 							lowerCAmelCase_						(    a__				):
       UpperCAmelCase__							:   List[Any]  	=    VOCAB_FILES_NAMES
       UpperCAmelCase__							:   List[str]  	=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCAmelCase__							:   Any  	=    PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase__							:   Tuple  	=    ["input_ids", "attention_mask"]
       UpperCAmelCase__							:   Any  	=    MBartTokenizer

       UpperCAmelCase__							:   List[int]  	=    []
       UpperCAmelCase__							:   List[int]  	=    []
       def __init__(     self,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_="<s>",     SCREAMING_SNAKE_CASE_="</s>",     SCREAMING_SNAKE_CASE_="</s>",     SCREAMING_SNAKE_CASE_="<s>",     SCREAMING_SNAKE_CASE_="<unk>",     SCREAMING_SNAKE_CASE_="<pad>",     SCREAMING_SNAKE_CASE_="<mask>",     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_=None,     **SCREAMING_SNAKE_CASE_,     )	->						List[str]:
          # Mask token behave like a normal word, i.e. include the space before it
          UpperCamelCase       :    str		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else mask_token

          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_,     **SCREAMING_SNAKE_CASE_,     )

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

          UpperCamelCase       :    Optional[Any]		      =      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       :    Tuple		      =      {
              lang_code: self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_			) for lang_code in FAIRSEQ_LANGUAGE_CODES
          }

          UpperCamelCase       :    Any		      =      src_lang if src_lang is not None else 'en_XX'
          UpperCamelCase       :    Union[str, Any]		      =      self.convert_tokens_to_ids(self._src_lang			)
          UpperCamelCase       :    List[Any]		      =      tgt_lang
          self.set_src_lang_special_tokens(self._src_lang			)
       @property
       def    snake_case_			(     self			)	->						str:
          return self._src_lang
       @src_lang.setter
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_			)	->						None:
          UpperCamelCase       :    List[str]		      =      new_src_lang
          self.set_src_lang_special_tokens(self._src_lang			)
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = None			)	->						List[int]:
          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    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = None			)	->						List[int]:
          UpperCamelCase       :    Union[str, Any]		      =      [self.sep_token_id]
          UpperCamelCase       :    Union[str, Any]		      =      [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    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_			)	->						Union[str, Any]:
          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       :    List[Any]		      =      src_lang
          UpperCamelCase       :    List[str]		      =      self(SCREAMING_SNAKE_CASE_,     add_special_tokens=SCREAMING_SNAKE_CASE_,     return_tensors=SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_			)
          UpperCamelCase       :    Any		      =      self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_			)
          UpperCamelCase       :    Any		      =      tgt_lang_id
          return inputs
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = "en_XX",     SCREAMING_SNAKE_CASE_ = None,     SCREAMING_SNAKE_CASE_ = "ro_RO",     **SCREAMING_SNAKE_CASE_,     )	->						BatchEncoding:
          UpperCamelCase       :    Tuple		      =      src_lang
          UpperCamelCase       :    Union[str, Any]		      =      tgt_lang
          return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_			)
       def    snake_case_			(     self			)	->						Any:
          return self.set_src_lang_special_tokens(self.src_lang			)
       def    snake_case_			(     self			)	->						Dict:
          return self.set_tgt_lang_special_tokens(self.tgt_lang			)
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_			)	->						None:
          UpperCamelCase       :    str		      =      self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_			)
          UpperCamelCase       :    Optional[Any]		      =      []
          UpperCamelCase       :    str		      =      [self.eos_token_id, self.cur_lang_code]

          UpperCamelCase       :    Dict		      =      self.convert_ids_to_tokens(self.prefix_tokens			)
          UpperCamelCase       :    List[str]		      =      self.convert_ids_to_tokens(self.suffix_tokens			)

          UpperCamelCase       :    Union[str, Any]		      =      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    snake_case_			(     self,     SCREAMING_SNAKE_CASE_			)	->						None:
          UpperCamelCase       :    Optional[Any]		      =      self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_			)
          UpperCamelCase       :    List[str]		      =      []
          UpperCamelCase       :    List[str]		      =      [self.eos_token_id, self.cur_lang_code]

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

          UpperCamelCase       :    Any		      =      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    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = None			)	->						Tuple[str]:
          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
          UpperCamelCase       :    Optional[Any]		      =      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,)







"""simple docstring"""


import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase     ,   unittest.TestCase  ):
   """simple docstring"""



   _a   :       Optional[int]									=    LayoutLMTokenizer
   _a   :       Dict									=    LayoutLMTokenizerFast
   _a   :       Dict									=    True
   _a   :       Any									=    True


   def 					UpperCAmelCase__(						self						)      ->							List[str]:
    super().setUp()

    lowercase__       :       int				=						[
        """[UNK]""",
        """[CLS]""",
        """[SEP]""",
        """want""",
        """##want""",
        """##ed""",
        """wa""",
        """un""",
        """runn""",
        """##ing""",
        """,""",
        """low""",
        """lowest""",
    ]
    lowercase__       :       Dict				=						os.path.join(self.tmpdirname ,     VOCAB_FILES_NAMES["""vocab_file"""]						)
    with open(self.vocab_file ,     """w""" ,     encoding="""utf-8"""						) as vocab_writer:
     vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]						)						)


   def 					UpperCAmelCase__(						self ,     **lowerCamelCase__						)      ->							Optional[int]:
    return LayoutLMTokenizer.from_pretrained(self.tmpdirname ,     **lowerCamelCase__						)


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__						)      ->							List[Any]:
    lowercase__       :       List[str]				=						"""UNwant\u00E9d,running"""
    lowercase__       :       Optional[int]				=						"""unwanted, running"""
    return input_text, output_text


   def 					UpperCAmelCase__(						self						)      ->							Optional[int]:
    lowercase__       :       str				=						self.tokenizer_class(self.vocab_file						)

    lowercase__       :       Optional[Any]				=						tokenizer.tokenize("""UNwant\u00E9d,running"""						)
    self.assertListEqual(lowerCamelCase__ ,     ["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]						)
    self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase__						) ,     [7, 4, 5, 10, 8, 9]						)







   def 					UpperCAmelCase__(						self						)      ->							Any:
    pass