





"""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:
		a		:					List[Any]	      =     None


a		:					str	      =     logging.get_logger(__name__)


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

a		:					Optional[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''',
    },
}

a		:					str	      =     {
    '''facebook/mbart-large-en-ro''': 1024,
    '''facebook/mbart-large-cc25''': 1024,
}

# fmt: off
a		:					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 			__UpperCamelCase							(		a__		):
							lowerCamelCase  :   str    =VOCAB_FILES_NAMES
							lowerCamelCase  :   List[str]    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCamelCase  :   str    =PRETRAINED_VOCAB_FILES_MAP
							lowerCamelCase  :   Union[str, Any]    =["""input_ids""", """attention_mask"""]
							lowerCamelCase  :   Tuple    =MBartTokenizer

							lowerCamelCase  :   List[int]    =[]
							lowerCamelCase  :   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__ ,   )      ->					Dict:
								# Mask token behave like a normal word, i.e. include the space before it
								a :						str      =							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 :						List[str]      =							vocab_file
								a :						Optional[Any]      =							False if not self.vocab_file else True

								a :						str      =							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 :						str      =							{
								    lang_code: self.convert_tokens_to_ids(lowerCAmelCase__ ) for lang_code in FAIRSEQ_LANGUAGE_CODES
								}

								a :						Tuple      =							src_lang if src_lang is not None else "en_XX"
								a :						Optional[int]      =							self.convert_tokens_to_ids(self._src_lang )
								a :						List[str]      =							tgt_lang
								self.set_src_lang_special_tokens(self._src_lang )






							@property
							def        __a  (  self )      ->					str:
								return self._src_lang






							@src_lang.setter
							def        __a  (  self ,   lowerCAmelCase__ )      ->					None:
								a :						int      =							new_src_lang
								self.set_src_lang_special_tokens(self._src_lang )






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ = 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        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ = None )      ->					List[int]:
								a :						Union[str, Any]      =							[self.sep_token_id]
								a :						List[str]      =							[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__ )      ->					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" )
								a :						Optional[int]      =							src_lang
								a :						Union[str, Any]      =							self(lowerCAmelCase__ ,   add_special_tokens=lowerCAmelCase__ ,   return_tensors=lowerCAmelCase__ ,   **lowerCAmelCase__ )
								a :						List[Any]      =							self.convert_tokens_to_ids(lowerCAmelCase__ )
								a :						List[Any]      =							tgt_lang_id
								return inputs






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ = "en_XX" ,   lowerCAmelCase__ = None ,   lowerCAmelCase__ = "ro_RO" ,   **lowerCAmelCase__ ,   )      ->					BatchEncoding:
								a :						List[str]      =							src_lang
								a :						Any      =							tgt_lang
								return super().prepare_seqaseq_batch(lowerCAmelCase__ ,   lowerCAmelCase__ ,   **lowerCAmelCase__ )






							def        __a  (  self )      ->					List[Any]:
								return self.set_src_lang_special_tokens(self.src_lang )






							def        __a  (  self )      ->					str:
								return self.set_tgt_lang_special_tokens(self.tgt_lang )






							def        __a  (  self ,   lowerCAmelCase__ )      ->					None:
								a :						Tuple      =							self.convert_tokens_to_ids(lowerCAmelCase__ )
								a :						Dict      =							[]
								a :						Optional[int]      =							[self.eos_token_id, self.cur_lang_code]

								a :						Optional[Any]      =							self.convert_ids_to_tokens(self.prefix_tokens )
								a :						Optional[int]      =							self.convert_ids_to_tokens(self.suffix_tokens )

								a :						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        __a  (  self ,   lowerCAmelCase__ )      ->					None:
								a :						Optional[int]      =							self.convert_tokens_to_ids(lowerCAmelCase__ )
								a :						List[Any]      =							[]
								a :						str      =							[self.eos_token_id, self.cur_lang_code]

								a :						Dict      =							self.convert_ids_to_tokens(self.prefix_tokens )
								a :						List[Any]      =							self.convert_ids_to_tokens(self.suffix_tokens )

								a :						Optional[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        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ = 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(lowerCAmelCase__ ):
									logger.error(f"""Vocabulary path ({save_directory}) should be a directory.""" )
									return
								a :						Union[str, Any]      =							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 unittest

from transformers import DonutProcessor


a		:					Optional[int]	      =     '''naver-clova-ix/donut-base'''


class 			__UpperCamelCase							(		unittest.TestCase		):






							def        __a  (  self )      ->					Dict:
								a :						Optional[Any]      =							DonutProcessor.from_pretrained(lowerCAmelCase__ )






							def        __a  (  self )      ->					List[Any]:
								a :						Optional[Any]      =							{
								    "name": "John Doe",
								    "age": "99",
								    "city": "Atlanta",
								    "state": "GA",
								    "zip": "30301",
								    "phone": "123-4567",
								    "nicknames": [{"nickname": "Johnny"}, {"nickname": "JD"}],
								}

								a :						Tuple      =							(
								    "<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"
								    "<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"
								    "<s_nicknames><s_nickname>Johnny</s_nickname>"
								    "<sep/><s_nickname>JD</s_nickname></s_nicknames>"
								)
								a :						List[Any]      =							self.processor.tokenajson(lowerCAmelCase__ )

								self.assertDictEqual(lowerCAmelCase__ ,   lowerCAmelCase__ )


