


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


_A			=						logging.get_logger(__name__)

_A			=						'▁'

_A			=						{'vocab_file': 'sentencepiece.bpe.model'}

_A			=						{
    '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'
        ),
    }
}

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

# 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']






class    UpperCAmelCase__	( A_		):



    """simple docstring"""






    UpperCAmelCase__						:		List[str]              =  VOCAB_FILES_NAMES
    UpperCAmelCase__						:		Union[str, Any]              =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase__						:		Dict              =  PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase__						:		Optional[Any]              =  ["input_ids", "attention_mask"]

    UpperCAmelCase__						:		List[int]              =  []
    UpperCAmelCase__						:		List[int]              =  []






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

         __UpperCamelCase   							={} if sp_model_kwargs is None else sp_model_kwargs

         super().__init__(
             bos_token=A_ ,       eos_token=A_ ,       unk_token=A_ ,       sep_token=A_ ,       cls_token=A_ ,       pad_token=A_ ,       mask_token=A_ ,       tokenizer_file=A_ ,       src_lang=A_ ,       tgt_lang=A_ ,       additional_special_tokens=A_ ,       sp_model_kwargs=self.sp_model_kwargs ,       **A_ ,       )

         __UpperCamelCase   							=spm.SentencePieceProcessor(**self.sp_model_kwargs   )
         self.sp_model.Load(str(A_   )   )
         __UpperCamelCase   							=vocab_file

         # Original fairseq vocab and spm vocab must be "aligned":
         # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
         # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
         # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
         # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

         # Mimic fairseq token-to-id alignment for the first 4 token
         __UpperCamelCase   							={'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

         # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
         __UpperCamelCase   							=1

         __UpperCamelCase   							=len(self.sp_model   )
         __UpperCamelCase   							={
             code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(A_   )
         }
         __UpperCamelCase   							={v: k for k, v in self.lang_code_to_id.items()}
         __UpperCamelCase   							=len(self.sp_model   ) + len(self.lang_code_to_id   ) + self.fairseq_offset

         self.fairseq_tokens_to_ids.update(self.lang_code_to_id   )
         __UpperCamelCase   							={v: k for k, v in self.fairseq_tokens_to_ids.items()}
         __UpperCamelCase   							=list(self.lang_code_to_id.keys()   )

         if additional_special_tokens is not None:
              # Only add those special tokens if they are not already there.
              self._additional_special_tokens.extend(
                  [t for t in additional_special_tokens if t not in self._additional_special_tokens]   )

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






    def __getstate__(      self   )  ->	Tuple:
         __UpperCamelCase   							=self.__dict__.copy()
         __UpperCamelCase   							=None
         __UpperCamelCase   							=self.sp_model.serialized_model_proto()
         return state






    def __setstate__(      self ,       A_   )  ->	Optional[Any]:
         __UpperCamelCase   							=d

         # for backward compatibility
         if not hasattr(self ,       'sp_model_kwargs'   ):
              __UpperCamelCase   							={}

         __UpperCamelCase   							=spm.SentencePieceProcessor(**self.sp_model_kwargs   )
         self.sp_model.LoadFromSerializedProto(self.sp_model_proto   )






    @property
    def _a (      self   )  ->	str:
         return len(self.sp_model   ) + len(self.lang_code_to_id   ) + self.fairseq_offset + 1  # Plus 1 for the mask token






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






    @src_lang.setter
    def _a (      self ,       A_   )  ->	None:
         __UpperCamelCase   							=new_src_lang
         self.set_src_lang_special_tokens(self._src_lang   )






    def _a (      self ,       A_ ,       A_ = None ,       A_ = False   )  ->	List[int]:

         if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=A_ ,       token_ids_a=A_ ,       already_has_special_tokens=A_   )

         __UpperCamelCase   							=[1] * len(self.prefix_tokens   )
         __UpperCamelCase   							=[1] * len(self.suffix_tokens   )
         if token_ids_a is None:
              return prefix_ones + ([0] * len(A_   )) + suffix_ones
         return prefix_ones + ([0] * len(A_   )) + ([0] * len(A_   )) + suffix_ones






    def _a (      self ,       A_ ,       A_ = 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 ,       A_ ,       A_ = None   )  ->	List[int]:
         __UpperCamelCase   							=[self.sep_token_id]
         __UpperCamelCase   							=[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 ,       A_ ,       A_ ,       A_ ,       A_ ,       **A_   )  ->	Optional[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'   )
         __UpperCamelCase   							=src_lang
         __UpperCamelCase   							=self(A_ ,       add_special_tokens=A_ ,       return_tensors=A_ ,       **A_   )
         __UpperCamelCase   							=self.convert_tokens_to_ids(A_   )
         __UpperCamelCase   							=tgt_lang_id
         return inputs






    def _a (      self   )  ->	List[str]:
         __UpperCamelCase   							={self.convert_ids_to_tokens(A_   ): i for i in range(self.vocab_size   )}
         vocab.update(self.added_tokens_encoder   )
         return vocab






    def _a (      self ,       A_   )  ->	List[str]:
         return self.sp_model.encode(A_ ,       out_type=A_   )






    def _a (      self ,       A_   )  ->	Tuple:
         if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
         __UpperCamelCase   							=self.sp_model.PieceToId(A_   )

         # Need to return unknown token if the SP model returned 0
         return spm_id + self.fairseq_offset if spm_id else self.unk_token_id






    def _a (      self ,       A_   )  ->	Any:
         if index in self.fairseq_ids_to_tokens:
              return self.fairseq_ids_to_tokens[index]
         return self.sp_model.IdToPiece(index - self.fairseq_offset   )






    def _a (      self ,       A_   )  ->	str:
         __UpperCamelCase   							=''.join(A_   ).replace(A_ ,       ' '   ).strip()
         return out_string






    def _a (      self ,       A_ ,       A_ = None   )  ->	Tuple[str]:
         if not os.path.isdir(A_   ):
              logger.error(f'Vocabulary path ({save_directory}) should be a directory'   )
              return
         __UpperCamelCase   							=os.path.join(
             A_ ,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

         if os.path.abspath(self.vocab_file   ) != os.path.abspath(A_   ) and os.path.isfile(self.vocab_file   ):
              copyfile(self.vocab_file ,       A_   )
         elif not os.path.isfile(self.vocab_file   ):
              with open(A_ ,       'wb'   ) as fi:
                   __UpperCamelCase   							=self.sp_model.serialized_model_proto()
                   fi.write(A_   )

         return (out_vocab_file,)






    def _a (      self ,       A_ ,       A_ = "en_XX" ,       A_ = None ,       A_ = "ro_RO" ,       **A_ ,       )  ->	BatchEncoding:
         __UpperCamelCase   							=src_lang
         __UpperCamelCase   							=tgt_lang
         return super().prepare_seqaseq_batch(A_ ,       A_ ,       **A_   )






    def _a (      self   )  ->	Union[str, Any]:
         return self.set_src_lang_special_tokens(self.src_lang   )






    def _a (      self   )  ->	Optional[Any]:
         return self.set_tgt_lang_special_tokens(self.tgt_lang   )






    def _a (      self ,       A_   )  ->	None:
         __UpperCamelCase   							=self.lang_code_to_id[src_lang]
         __UpperCamelCase   							=[]
         __UpperCamelCase   							=[self.eos_token_id, self.cur_lang_code]






    def _a (      self ,       A_   )  ->	None:
         __UpperCamelCase   							=self.lang_code_to_id[lang]
         __UpperCamelCase   							=[]
         __UpperCamelCase   							=[self.eos_token_id, self.cur_lang_code]









from ..utils import DummyObject, requires_backends






class    UpperCAmelCase__	( metaclass=A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Any              =  ["speech"]






    def __init__(      self ,       *A_ ,       **A_   )  ->	Any:
         requires_backends(self ,       ['speech']   )






class    UpperCAmelCase__	( metaclass=A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Union[str, Any]              =  ["speech"]






    def __init__(      self ,       *A_ ,       **A_   )  ->	Union[str, Any]:
         requires_backends(self ,       ['speech']   )





