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:
							_lowerCamelCase					:   Optional[int]							=		None


_lowerCamelCase					:   str							=		logging.get_logger(__name__)


_lowerCamelCase					:   Union[str, Any]							=		{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

_lowerCamelCase					:   Optional[int]							=		{
    '''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''',
    },
}

_lowerCamelCase					:   Union[str, Any]							=		{
    '''facebook/mbart-large-en-ro''': 10_24,
    '''facebook/mbart-large-cc25''': 10_24,
}

# fmt: off
_lowerCamelCase					:   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 						lowercase    (     a     ):
							lowercase__						:       List[str]								=							VOCAB_FILES_NAMES
							lowercase__						:       List[str]								=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase__						:       Union[str, Any]								=							PRETRAINED_VOCAB_FILES_MAP
							lowercase__						:       Optional[Any]								=							["""input_ids""", """attention_mask"""]
							lowercase__						:       Optional[Any]								=							MBartTokenizer

							lowercase__						:       List[int]								=							[]
							lowercase__						:       List[int]								=							[]




							def __init__(						self   :					int	,							_UpperCamelCase   :					Any=None	,							_UpperCamelCase   :					Optional[Any]=None	,							_UpperCamelCase   :					Tuple="<s>"	,							_UpperCamelCase   :					Optional[Any]="</s>"	,							_UpperCamelCase   :					List[Any]="</s>"	,							_UpperCamelCase   :					str="<s>"	,							_UpperCamelCase   :					Optional[Any]="<unk>"	,							_UpperCamelCase   :					Tuple="<pad>"	,							_UpperCamelCase   :					Union[str, Any]="<mask>"	,							_UpperCamelCase   :					List[Any]=None	,							_UpperCamelCase   :					Dict=None	,							_UpperCamelCase   :					List[Any]=None	,							**_UpperCamelCase   :					List[Any]	,							)					->				Optional[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       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	,							)

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

												SCREAMING_SNAKE_CASE    			=       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}      )
												SCREAMING_SNAKE_CASE    			=       {
												    lang_code: self.convert_tokens_to_ids(_UpperCamelCase      ) for lang_code in FAIRSEQ_LANGUAGE_CODES
												}

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




							@property
							def 	__snake_case(						self   :					str      )					->				str:



												'''simple docstring'''

												return self._src_lang




							@src_lang.setter
							def 	__snake_case(						self   :					Dict	,							_UpperCamelCase   :					str      )					->				None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       new_src_lang
												self.set_src_lang_special_tokens(self._src_lang      )




							def 	__snake_case(						self   :					Dict	,							_UpperCamelCase   :					List[int]	,							_UpperCamelCase   :					Optional[List[int]] = None      )					->				List[int]:



												'''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 	__snake_case(						self   :					Dict	,							_UpperCamelCase   :					List[int]	,							_UpperCamelCase   :					Optional[List[int]] = None      )					->				List[int]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       [self.sep_token_id]
												SCREAMING_SNAKE_CASE    			=       [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   :					Dict	,							_UpperCamelCase   :					Optional[int]	,							_UpperCamelCase   :					str	,							_UpperCamelCase   :					Optional[str]	,							_UpperCamelCase   :					Optional[str]	,							**_UpperCamelCase   :					int      )					->				Union[str, Any]:



												'''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"      )
												SCREAMING_SNAKE_CASE    			=       src_lang
												SCREAMING_SNAKE_CASE    			=       self(_UpperCamelCase	,							add_special_tokens=_UpperCamelCase	,							return_tensors=_UpperCamelCase	,							**_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       self.convert_tokens_to_ids(_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       tgt_lang_id
												return inputs




							def 	__snake_case(						self   :					Dict	,							_UpperCamelCase   :					List[str]	,							_UpperCamelCase   :					str = "en_XX"	,							_UpperCamelCase   :					Optional[List[str]] = None	,							_UpperCamelCase   :					str = "ro_RO"	,							**_UpperCamelCase   :					List[str]	,							)					->				BatchEncoding:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       src_lang
												SCREAMING_SNAKE_CASE    			=       tgt_lang
												return super().prepare_seqaseq_batch(_UpperCamelCase	,							_UpperCamelCase	,							**_UpperCamelCase      )




							def 	__snake_case(						self   :					List[Any]      )					->				Optional[Any]:



												'''simple docstring'''

												return self.set_src_lang_special_tokens(self.src_lang      )




							def 	__snake_case(						self   :					Any      )					->				int:



												'''simple docstring'''

												return self.set_tgt_lang_special_tokens(self.tgt_lang      )




							def 	__snake_case(						self   :					int	,							_UpperCamelCase   :					List[Any]      )					->				None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.convert_tokens_to_ids(_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       []
												SCREAMING_SNAKE_CASE    			=       [self.eos_token_id, self.cur_lang_code]

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

												SCREAMING_SNAKE_CASE    			=       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   :					Optional[Any]	,							_UpperCamelCase   :					str      )					->				None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.convert_tokens_to_ids(_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       []
												SCREAMING_SNAKE_CASE    			=       [self.eos_token_id, self.cur_lang_code]

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

												SCREAMING_SNAKE_CASE    			=       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   :					Any	,							_UpperCamelCase   :					str	,							_UpperCamelCase   :					Optional[str] = None      )					->				Tuple[str]:



												'''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
												SCREAMING_SNAKE_CASE    			=       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,)





import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property


@unittest.skipUnless(os.path.exists(a     )				,       """Tatoeba directory does not exist."""     )
class 						lowercase    (     unittest.TestCase     ):




							@cached_property
							def 	__snake_case(						self   :					int      )					->				List[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       tempfile.mkdtemp()
												return TatoebaConverter(save_dir=_UpperCamelCase      )




							@slow
							def 	__snake_case(						self   :					Tuple      )					->				List[Any]:



												'''simple docstring'''

												self.resolver.convert_models(["heb-eng"]      )





							@slow
							def 	__snake_case(						self   :					Any      )					->				Optional[int]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       self.resolver.write_model_card("opus-mt-he-en"	,							dry_run=_UpperCamelCase      )
												assert mmeta["long_pair"] == "heb-eng"




