




"""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:
      SCREAMING_SNAKE_CASE							=			None


SCREAMING_SNAKE_CASE							=			logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE							=			{
    "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"
        ),
    },
}

SCREAMING_SNAKE_CASE							=			{
    "facebook/mbart-large-50-one-to-many-mmt": 1024,
}

# fmt: off
SCREAMING_SNAKE_CASE							=			["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       UpperCAmelCase_    (		_A				):
    lowercase__		   = VOCAB_FILES_NAMES
    lowercase__		   = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase__		   = PRETRAINED_VOCAB_FILES_MAP
    lowercase__		   = ["input_ids", "attention_mask"]
    lowercase__		   = MBartaaTokenizer

    lowercase__		   = []
    lowercase__		   = []




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




     '''simple docstring'''

     A__			=							AddedToken(__lowercase      ,					lstrip=__lowercase      ,					rstrip=__lowercase ) if isinstance(__lowercase      ,					__lowercase ) else mask_token

     A__			=							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__(
         __lowercase      ,					src_lang=__lowercase      ,					tgt_lang=__lowercase      ,					tokenizer_file=__lowercase      ,					eos_token=__lowercase      ,					sep_token=__lowercase      ,					cls_token=__lowercase      ,					unk_token=__lowercase      ,					pad_token=__lowercase      ,					mask_token=__lowercase      ,					**__lowercase      ,					)

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

     A__			=							{
         lang_code: self.convert_tokens_to_ids(__lowercase ) for lang_code in FAIRSEQ_LANGUAGE_CODES
     }

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




    @property
    def 				__magic_name__				(       self		:			List[str] ) ->				str:




     '''simple docstring'''

     return self._src_lang




    @src_lang.setter
    def 				__magic_name__				(       self		:			Union[str, Any]      ,					snake_case_		:			int ) ->				None:




     '''simple docstring'''

     A__			=							new_src_lang
     self.set_src_lang_special_tokens(self._src_lang )




    def 				__magic_name__				(       self		:			List[Any]      ,					snake_case_		:			int      ,					snake_case_		:			Dict = 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 				__magic_name__				(       self		:			Any      ,					snake_case_		:			Optional[int]      ,					snake_case_		:			str = "en_XX"      ,					snake_case_		:			List[Any] = None      ,					snake_case_		:			List[Any] = "ro_RO"      ,					**snake_case_		:			Any      ,					) ->				BatchEncoding:




     '''simple docstring'''

     A__			=							src_lang
     A__			=							tgt_lang
     return super().prepare_seqaseq_batch(__lowercase      ,					__lowercase      ,					**__lowercase )




    def 				__magic_name__				(       self		:			Any ) ->				Tuple:




     '''simple docstring'''

     return self.set_src_lang_special_tokens(self.src_lang )




    def 				__magic_name__				(       self		:			Any ) ->				List[Any]:




     '''simple docstring'''

     return self.set_tgt_lang_special_tokens(self.tgt_lang )




    def 				__magic_name__				(       self		:			Any      ,					snake_case_		:			Optional[Any] ) ->				None:




     '''simple docstring'''

     A__			=							self.convert_tokens_to_ids(__lowercase )
     A__			=							[self.cur_lang_code_id]
     A__			=							[self.eos_token_id]

     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 				__magic_name__				(       self		:			Optional[Any]      ,					snake_case_		:			Union[str, Any] ) ->				None:




     '''simple docstring'''

     A__			=							self.convert_tokens_to_ids(__lowercase )
     A__			=							[self.cur_lang_code_id]
     A__			=							[self.eos_token_id]

     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 				__magic_name__				(       self		:			Union[str, Any]      ,					snake_case_		:			str      ,					snake_case_		:			Any      ,					snake_case_		:			Optional[int]      ,					snake_case_		:			int      ,					**snake_case_		:			Union[str, Any] ) ->				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" )
     A__			=							src_lang
     A__			=							self(__lowercase      ,					add_special_tokens=__lowercase      ,					return_tensors=__lowercase      ,					**__lowercase )
     A__			=							self.convert_tokens_to_ids(__lowercase )
     A__			=							tgt_lang_id
     return inputs




    def 				__magic_name__				(       self		:			int      ,					snake_case_		:			Any      ,					snake_case_		:			Dict = 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(__lowercase ):
      logger.error(F"""Vocabulary path ({save_directory}) should be a directory""" )
      return
     A__			=							os.path.join(
         __lowercase      ,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )

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

     return (out_vocab_file,)












import pytest

from datasets.utils.version import Version


@pytest.mark.parametrize(
    '''other, expected_equality'''				,							[
        (Version('''1.0.0'''		), True),
        ('''1.0.0''', True),
        (Version('''2.0.0'''		), False),
        ('''2.0.0''', False),
        ('''1''', False),
        ('''a''', False),
        (1, False),
        (None, False),
    ]				,							)
def        A__						(							SCREAMING_SNAKE_CASE_				,							SCREAMING_SNAKE_CASE_		) ->  Optional[int]:
		lowerCamelCase :			str    		=Version('''1.0.0'''		)
		assert (version == other) is expected_equality
		assert (version != other) is not expected_equality
		assert (hash(SCREAMING_SNAKE_CASE_		) == hash(SCREAMING_SNAKE_CASE_		)) is expected_equality

