





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


__lowerCamelCase :  Tuple										=  logging.get_logger(__name__)

__lowerCamelCase :  Tuple										=  """▁"""

__lowerCamelCase :  Optional[Any]										=  {"""vocab_file""": """sentencepiece.bpe.model"""}

__lowerCamelCase :  List[str]										=  {
    """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"""
        ),
    }
}

__lowerCamelCase :  Dict										=  {
    """facebook/mbart-large-en-ro""": 1024,
    """facebook/mbart-large-cc25""": 1024,
}

# fmt: off
__lowerCamelCase :  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__     ( __snake_case    ):
      _UpperCAmelCase			:Tuple							=     VOCAB_FILES_NAMES
      _UpperCAmelCase			:int							=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _UpperCAmelCase			:Optional[int]							=     PRETRAINED_VOCAB_FILES_MAP
      _UpperCAmelCase			: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_ ,							):
       '''simple docstring'''




       UpperCamelCase			:      int 			=     AddedToken(A_ ,							lstrip=A_ ,							rstrip=A_     ) if isinstance(A_ ,							A_     ) else mask_token

       UpperCamelCase			:      Optional[int] 			=     {} 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			:      Optional[int] 			=     spm.SentencePieceProcessor(**self.sp_model_kwargs     )
       self.sp_model.Load(str(A_     )     )
       UpperCamelCase			:      Optional[Any] 			=     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			:      Optional[int] 			=     {"<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			:      Any 			=     1

       UpperCamelCase			:      int 			=     len(self.sp_model     )
       UpperCamelCase			:      str 			=     {
           code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(A_     )
       }
       UpperCamelCase			:      List[str] 			=     {v: k for k, v in self.lang_code_to_id.items()}
       UpperCamelCase			:      Union[str, Any] 			=     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			:      Union[str, Any] 			=     {v: k for k, v in self.fairseq_tokens_to_ids.items()}
       UpperCamelCase			:      Any 			=     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			:      int 			=     src_lang if src_lang is not None else "en_XX"
       UpperCamelCase			:      str 			=     self.lang_code_to_id[self._src_lang]
       UpperCamelCase			:      Optional[Any] 			=     tgt_lang
       self.set_src_lang_special_tokens(self._src_lang     )





      def __getstate__(				self     ):
       '''simple docstring'''




       UpperCamelCase			:      Dict 			=     self.__dict__.copy()
       UpperCamelCase			:      Tuple 			=     None
       UpperCamelCase			:      str 			=     self.sp_model.serialized_model_proto()
       return state





      def __setstate__(				self ,							A_     ):
       '''simple docstring'''




       UpperCamelCase			:      int 			=     d

       # for backward compatibility
       if not hasattr(self ,							"sp_model_kwargs"     ):
        UpperCamelCase			:      Optional[int] 			=     {}

       UpperCamelCase			:      Tuple 			=     spm.SentencePieceProcessor(**self.sp_model_kwargs     )
       self.sp_model.LoadFromSerializedProto(self.sp_model_proto     )





      @property
      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




       return len(self.sp_model     ) + len(self.lang_code_to_id     ) + self.fairseq_offset + 1  # Plus 1 for the mask token





      @property
      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




       return self._src_lang





      @src_lang.setter
      def  __UpperCamelCase(				self ,							A_     ):
       '''simple docstring'''




       UpperCamelCase			:      Dict 			=     new_src_lang
       self.set_src_lang_special_tokens(self._src_lang     )





      def  __UpperCamelCase(				self ,							A_ ,							A_ = None ,							A_ = False     ):
       '''simple docstring'''




       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			:      int 			=     [1] * len(self.prefix_tokens     )
       UpperCamelCase			:      List[Any] 			=     [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  __UpperCamelCase(				self ,							A_ ,							A_ = 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  __UpperCamelCase(				self ,							A_ ,							A_ = None     ):
       '''simple docstring'''




       UpperCamelCase			:      Dict 			=     [self.sep_token_id]
       UpperCamelCase			:      Union[str, Any] 			=     [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  __UpperCamelCase(				self ,							A_ ,							A_ ,							A_ ,							A_ ,							**A_     ):
       '''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			:      Tuple 			=     src_lang
       UpperCamelCase			:      Tuple 			=     self(A_ ,							add_special_tokens=A_ ,							return_tensors=A_ ,							**A_     )
       UpperCamelCase			:      Optional[int] 			=     self.convert_tokens_to_ids(A_     )
       UpperCamelCase			:      Dict 			=     tgt_lang_id
       return inputs





      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




       UpperCamelCase			:      Tuple 			=     {self.convert_ids_to_tokens(A_     ): i for i in range(self.vocab_size     )}
       vocab.update(self.added_tokens_encoder     )
       return vocab





      def  __UpperCamelCase(				self ,							A_     ):
       '''simple docstring'''




       return self.sp_model.encode(A_ ,							out_type=A_     )





      def  __UpperCamelCase(				self ,							A_     ):
       '''simple docstring'''




       if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
       UpperCamelCase			:      Optional[Any] 			=     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  __UpperCamelCase(				self ,							A_     ):
       '''simple docstring'''




       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  __UpperCamelCase(				self ,							A_     ):
       '''simple docstring'''




       UpperCamelCase			:      Dict 			=     "".join(A_     ).replace(A_ ,							" "     ).strip()
       return out_string





      def  __UpperCamelCase(				self ,							A_ ,							A_ = None     ):
       '''simple docstring'''




       if not os.path.isdir(A_     ):
        logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""     )
        return
       UpperCamelCase			:      List[str] 			=     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			:      str 			=     self.sp_model.serialized_model_proto()
         fi.write(A_     )

       return (out_vocab_file,)





      def  __UpperCamelCase(				self ,							A_ ,							A_ = "en_XX" ,							A_ = None ,							A_ = "ro_RO" ,							**A_ ,							):
       '''simple docstring'''




       UpperCamelCase			:      str 			=     src_lang
       UpperCamelCase			:      Dict 			=     tgt_lang
       return super().prepare_seqaseq_batch(A_ ,							A_ ,							**A_     )





      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




       return self.set_src_lang_special_tokens(self.src_lang     )





      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




       return self.set_tgt_lang_special_tokens(self.tgt_lang     )





      def  __UpperCamelCase(				self ,							A_     ):
       '''simple docstring'''




       UpperCamelCase			:      List[str] 			=     self.lang_code_to_id[src_lang]
       UpperCamelCase			:      List[str] 			=     []
       UpperCamelCase			:      Optional[Any] 			=     [self.eos_token_id, self.cur_lang_code]





      def  __UpperCamelCase(				self ,							A_     ):
       '''simple docstring'''




       UpperCamelCase			:      List[Any] 			=     self.lang_code_to_id[lang]
       UpperCamelCase			:      Any 			=     []
       UpperCamelCase			:      Dict 			=     [self.eos_token_id, self.cur_lang_code]







from ..utils import DummyObject, requires_backends



class       A__     ( metaclass=__snake_case    ):
      _UpperCAmelCase			:Tuple							=     ['note_seq']





      def __init__(				self ,							*A_ ,							**A_     ):
       '''simple docstring'''




       requires_backends(self ,							["note_seq"]     )





      @classmethod
      def  __UpperCamelCase(				cls ,							*A_ ,							**A_     ):
       '''simple docstring'''




       requires_backends(cls ,							["note_seq"]     )





      @classmethod
      def  __UpperCamelCase(				cls ,							*A_ ,							**A_     ):
       '''simple docstring'''




       requires_backends(cls ,							["note_seq"]     )
