


"""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_mbartaa import MBartaaTokenizer
else:
						__a      			= None


__a      			= logging.get_logger(__name__)

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

__a      			= {
    "vocab_file": {
        "facebook/mbart-large-50-one-to-many-mmt": (
            "https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-50-one-to-many-mmt": (
            "https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json"
        ),
    },
}

__a      			= {
    "facebook/mbart-large-50-one-to-many-mmt": 10_24,
}

# fmt: off
__a      			= ["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", "af_ZA", "az_AZ", "bn_IN", "fa_IR", "he_IL", "hr_HR", "id_ID", "ka_GE", "km_KH", "mk_MK", "ml_IN", "mn_MN", "mr_IN", "pl_PL", "ps_AF", "pt_XX", "sv_SE", "sw_KE", "ta_IN", "te_IN", "th_TH", "tl_XX", "uk_UA", "ur_PK", "xh_ZA", "gl_ES", "sl_SI"]
class 				lowerCamelCase							(      __SCREAMING_SNAKE_CASE			):


							"""simple docstring"""
							SCREAMING_SNAKE_CASE              =   VOCAB_FILES_NAMES
							SCREAMING_SNAKE_CASE              =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							SCREAMING_SNAKE_CASE              =   PRETRAINED_VOCAB_FILES_MAP
							SCREAMING_SNAKE_CASE              =   ["""input_ids""", """attention_mask"""]
							SCREAMING_SNAKE_CASE              =   MBartaaTokenizer

							SCREAMING_SNAKE_CASE              =   []
							SCREAMING_SNAKE_CASE              =   []






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

													UpperCAmelCase__												=     kwargs.get('''additional_special_tokens'''		,			[]					)
													kwargs["additional_special_tokens"] += [
													    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
													]

													super().__init__(
													    lowerCamelCase_		,			src_lang=lowerCamelCase_		,			tgt_lang=lowerCamelCase_		,			tokenizer_file=lowerCamelCase_		,			eos_token=lowerCamelCase_		,			sep_token=lowerCamelCase_		,			cls_token=lowerCamelCase_		,			unk_token=lowerCamelCase_		,			pad_token=lowerCamelCase_		,			mask_token=lowerCamelCase_		,			**lowerCamelCase_		,			)

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

													UpperCAmelCase__												=     {
													    lang_code: self.convert_tokens_to_ids(lowerCamelCase_					) for lang_code in FAIRSEQ_LANGUAGE_CODES
													}

													UpperCAmelCase__												=     src_lang if src_lang is not None else '''en_XX'''
													UpperCAmelCase__												=     tgt_lang
													UpperCAmelCase__												=     self.lang_code_to_id[self._src_lang]
													self.set_src_lang_special_tokens(self._src_lang					)






							@property
							def        lowerCAmelCase  (    self			:  int					):
													return self._src_lang






							@src_lang.setter
							def        lowerCAmelCase  (    self			:  Optional[int]		,			lowerCamelCase_			:  str					):
													UpperCAmelCase__												=     new_src_lang
													self.set_src_lang_special_tokens(self._src_lang					)






							def        lowerCAmelCase  (    self			:  Any		,			lowerCamelCase_			:  List[int]		,			lowerCamelCase_			:  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        lowerCAmelCase  (    self			:  Optional[Any]		,			lowerCamelCase_			:  List[str]		,			lowerCamelCase_			:  str = "en_XX"		,			lowerCamelCase_			:  Optional[List[str]] = None		,			lowerCamelCase_			:  str = "ro_RO"		,			**lowerCamelCase_			:  int		,			):
													UpperCAmelCase__												=     src_lang
													UpperCAmelCase__												=     tgt_lang
													return super().prepare_seqaseq_batch(lowerCamelCase_		,			lowerCamelCase_		,			**lowerCamelCase_					)






							def        lowerCAmelCase  (    self			:  Dict					):
													return self.set_src_lang_special_tokens(self.src_lang					)






							def        lowerCAmelCase  (    self			:  str					):
													return self.set_tgt_lang_special_tokens(self.tgt_lang					)






							def        lowerCAmelCase  (    self			:  str		,			lowerCamelCase_			:  str					):
													UpperCAmelCase__												=     self.convert_tokens_to_ids(lowerCamelCase_					)
													UpperCAmelCase__												=     [self.cur_lang_code_id]
													UpperCAmelCase__												=     [self.eos_token_id]

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

													UpperCAmelCase__												=     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        lowerCAmelCase  (    self			:  Tuple		,			lowerCamelCase_			:  str					):
													UpperCAmelCase__												=     self.convert_tokens_to_ids(lowerCamelCase_					)
													UpperCAmelCase__												=     [self.cur_lang_code_id]
													UpperCAmelCase__												=     [self.eos_token_id]

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

													UpperCAmelCase__												=     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        lowerCAmelCase  (    self			:  Union[str, Any]		,			lowerCamelCase_			:  Dict		,			lowerCamelCase_			:  str		,			lowerCamelCase_			:  Optional[str]		,			lowerCamelCase_			:  Optional[str]		,			**lowerCamelCase_			:  str					):
													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__												=     src_lang
													UpperCAmelCase__												=     self(lowerCamelCase_		,			add_special_tokens=lowerCamelCase_		,			return_tensors=lowerCamelCase_		,			**lowerCamelCase_					)
													UpperCAmelCase__												=     self.convert_tokens_to_ids(lowerCamelCase_					)
													UpperCAmelCase__												=     tgt_lang_id
													return inputs






							def        lowerCAmelCase  (    self			:  Union[str, Any]		,			lowerCamelCase_			:  str		,			lowerCamelCase_			:  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(lowerCamelCase_					):
																			logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""					)
																			return
													UpperCAmelCase__												=     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"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available


__a      			= {}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= ["BarthezTokenizer"]

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= ["BarthezTokenizerFast"]


if TYPE_CHECKING:
						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_barthez import BarthezTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_barthez_fast import BarthezTokenizerFast

else:
						import sys

						__a      			= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)