






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_       :int       =						None


A_       :Optional[int]       =						logging.get_logger(__name__)


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

A_       :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''',
    },
}

A_       :Union[str, Any]       =						{
    '''facebook/mbart-large-en-ro''': 1024,
    '''facebook/mbart-large-cc25''': 1024,
}

# fmt: off
A_       :int       =						['''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 				__A     (			a ):





				"""simple docstring"""







				UpperCamelCase__ :      List[str]			 =VOCAB_FILES_NAMES
				UpperCamelCase__ :      Union[str, Any]			 =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				UpperCamelCase__ :      Tuple			 =PRETRAINED_VOCAB_FILES_MAP
				UpperCamelCase__ :      str			 =["""input_ids""", """attention_mask"""]
				UpperCamelCase__ :      Any			 =MBartTokenizer

				UpperCamelCase__ :      List[int]			 =[]
				UpperCamelCase__ :      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__							,  ):




									"""simple docstring"""

									__UpperCamelCase      :					Union[str, Any]       		=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__							,  )

									__UpperCamelCase      :					int       		=vocab_file
									__UpperCamelCase      :					Tuple       		=False if not self.vocab_file else True

									__UpperCamelCase      :					Dict       		=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      :					List[str]       		={
									    lang_code: self.convert_tokens_to_ids(lowerCamelCase__    ) for lang_code in FAIRSEQ_LANGUAGE_CODES
									}

									__UpperCamelCase      :					Optional[Any]       		=src_lang if src_lang is not None else 'en_XX'
									__UpperCamelCase      :					str       		=self.convert_tokens_to_ids(self._src_lang    )
									__UpperCamelCase      :					str       		=tgt_lang
									self.set_src_lang_special_tokens(self._src_lang    )


				@property
				def       __lowercase							( self    ):




									"""simple docstring"""

									return self._src_lang


				@src_lang.setter
				def       __lowercase							( self							,  lowerCamelCase__    ):




									"""simple docstring"""

									__UpperCamelCase      :					Union[str, Any]       		=new_src_lang
									self.set_src_lang_special_tokens(self._src_lang    )


				def       __lowercase							( self							,  lowerCamelCase__							,  lowerCamelCase__ = None    ):




									"""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       __lowercase							( self							,  lowerCamelCase__							,  lowerCamelCase__ = None    ):




									"""simple docstring"""

									__UpperCamelCase      :					List[Any]       		=[self.sep_token_id]
									__UpperCamelCase      :					Tuple       		=[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       __lowercase							( self							,  lowerCamelCase__							,  lowerCamelCase__							,  lowerCamelCase__							,  lowerCamelCase__							,  **lowerCamelCase__    ):




									"""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'    )
									__UpperCamelCase      :					List[str]       		=src_lang
									__UpperCamelCase      :					List[str]       		=self(lowerCamelCase__							,  add_special_tokens=lowerCamelCase__							,  return_tensors=lowerCamelCase__							,  **lowerCamelCase__    )
									__UpperCamelCase      :					Optional[Any]       		=self.convert_tokens_to_ids(lowerCamelCase__    )
									__UpperCamelCase      :					Optional[int]       		=tgt_lang_id
									return inputs


				def       __lowercase							( self							,  lowerCamelCase__							,  lowerCamelCase__ = "en_XX"							,  lowerCamelCase__ = None							,  lowerCamelCase__ = "ro_RO"							,  **lowerCamelCase__							,  ):




									"""simple docstring"""

									__UpperCamelCase      :					Dict       		=src_lang
									__UpperCamelCase      :					Optional[Any]       		=tgt_lang
									return super().prepare_seqaseq_batch(lowerCamelCase__							,  lowerCamelCase__							,  **lowerCamelCase__    )


				def       __lowercase							( self    ):




									"""simple docstring"""

									return self.set_src_lang_special_tokens(self.src_lang    )


				def       __lowercase							( self    ):




									"""simple docstring"""

									return self.set_tgt_lang_special_tokens(self.tgt_lang    )


				def       __lowercase							( self							,  lowerCamelCase__    ):




									"""simple docstring"""

									__UpperCamelCase      :					Optional[Any]       		=self.convert_tokens_to_ids(lowerCamelCase__    )
									__UpperCamelCase      :					Tuple       		=[]
									__UpperCamelCase      :					Optional[Any]       		=[self.eos_token_id, self.cur_lang_code]

									__UpperCamelCase      :					Optional[Any]       		=self.convert_ids_to_tokens(self.prefix_tokens    )
									__UpperCamelCase      :					List[Any]       		=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       __lowercase							( self							,  lowerCamelCase__    ):




									"""simple docstring"""

									__UpperCamelCase      :					Union[str, Any]       		=self.convert_tokens_to_ids(lowerCamelCase__    )
									__UpperCamelCase      :					int       		=[]
									__UpperCamelCase      :					List[str]       		=[self.eos_token_id, self.cur_lang_code]

									__UpperCamelCase      :					Optional[int]       		=self.convert_ids_to_tokens(self.prefix_tokens    )
									__UpperCamelCase      :					Dict       		=self.convert_ids_to_tokens(self.suffix_tokens    )

									__UpperCamelCase      :					List[str]       		=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       __lowercase							( self							,  lowerCamelCase__							,  lowerCamelCase__ = None    ):




									"""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(lowerCamelCase__    ):
														logger.error(f'Vocabulary path ({save_directory}) should be a directory.'    )
														return
									__UpperCamelCase      :					List[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 jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


lowerCAmelCase__      				=   logging.get_logger(__name__)

lowerCAmelCase__      				=   '''T5Config'''
def 					a__			(				SCREAMING_SNAKE_CASE    :    jnp.array				,      SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    int				):


  '''simple docstring'''







  lowerCAmelCase     :     List[str]								=							jnp.zeros_like(SCREAMING_SNAKE_CASE				)
  lowerCAmelCase     :     Optional[int]								=							shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]				)
  lowerCAmelCase     :     List[str]								=							shifted_input_ids.at[:, 0].set(SCREAMING_SNAKE_CASE				)

  lowerCAmelCase     :     str								=							jnp.where(shifted_input_ids == -1_0_0				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
  return shifted_input_ids


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				List[Any]   ="mt5"
       a  :				Tuple   =MTaConfig


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				Union[str, Any]   ="mt5"
       a  :				Optional[Any]   =MTaConfig


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				str   ="mt5"
       a  :				Dict   =MTaConfig





