



import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE_:Any             =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:Optional[Any]             =						"""▁"""

SCREAMING_SNAKE_CASE_:int             =						{
    """vocab_file""": """vocab.json""",
    """spm_file""": """sentencepiece.bpe.model""",
}

SCREAMING_SNAKE_CASE_:List[str]             =						{
    """vocab_file""": {
        """facebook/s2t-small-librispeech-asr""": (
            """https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json"""
        ),
    },
    """spm_file""": {
        """facebook/s2t-small-librispeech-asr""": (
            """https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model"""
        )
    },
}

SCREAMING_SNAKE_CASE_:int             =						{
    """facebook/s2t-small-librispeech-asr""": 1_024,
}

SCREAMING_SNAKE_CASE_:Tuple             =						["""pt""", """fr""", """ru""", """nl""", """ro""", """it""", """es""", """de"""]

SCREAMING_SNAKE_CASE_:Dict             =						{"""mustc""": MUSTC_LANGS}






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Optional[Any]					=      VOCAB_FILES_NAMES
    __lowerCamelCase			: List[Any]					=      PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase			: str					=      MAX_MODEL_INPUT_SIZES
    __lowerCamelCase			: Optional[Any]					=      ["input_ids", "attention_mask"]

    __lowerCamelCase			: List[int]					=      []






    def __init__(       self,		lowerCamelCase__,		lowerCamelCase__,		lowerCamelCase__="<s>",		lowerCamelCase__="</s>",		lowerCamelCase__="<pad>",		lowerCamelCase__="<unk>",		lowerCamelCase__=False,		lowerCamelCase__=False,		lowerCamelCase__=None,		lowerCamelCase__=None,		lowerCamelCase__ = None,		**lowerCamelCase__,		):
        A :       List[str]          =   {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=lowerCamelCase__,		eos_token=lowerCamelCase__,		unk_token=lowerCamelCase__,		pad_token=lowerCamelCase__,		do_upper_case=lowerCamelCase__,		do_lower_case=lowerCamelCase__,		tgt_lang=lowerCamelCase__,		lang_codes=lowerCamelCase__,		sp_model_kwargs=self.sp_model_kwargs,		**lowerCamelCase__,		)
        A :       str          =   do_upper_case
        A :       List[Any]          =   do_lower_case

        A :       Optional[int]          =   load_json(lowerCamelCase__		)
        A :       Optional[int]          =   {v: k for k, v in self.encoder.items()}
        A :       Union[str, Any]          =   spm_file
        A :       Optional[int]          =   load_spm(lowerCamelCase__,		self.sp_model_kwargs		)

        if lang_codes is not None:
            A :       Any          =   lang_codes
            A :       Tuple          =   LANGUAGES[lang_codes]
            A :       Union[str, Any]          =   [f'''<lang:{lang}>''' for lang in self.langs]
            A :       List[Any]          =   {lang: self.sp_model.PieceToId(f'''<lang:{lang}>'''		) for lang in self.langs}

            A :       Optional[int]          =   self.lang_tokens
            A :       Optional[Any]          =   tgt_lang if tgt_lang is not None else self.langs[0]

            self.set_tgt_lang_special_tokens(self._tgt_lang		)
        else:
            A :       List[str]          =   {}






    @property
    def 			_lowerCAmelCase					(       self		):
        return len(self.encoder		)






    @property
    def 			_lowerCAmelCase					(       self		):
        return self._tgt_lang






    @tgt_lang.setter
    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        A :       Optional[int]          =   new_tgt_lang
        self.set_tgt_lang_special_tokens(lowerCamelCase__		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        A :       Dict          =   self.lang_code_to_id[tgt_lang]
        A :       List[str]          =   [lang_code_id]






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        return self.sp_model.encode(lowerCamelCase__,		out_type=lowerCamelCase__		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        return self.encoder.get(lowerCamelCase__,		self.encoder[self.unk_token]		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        return self.decoder.get(lowerCamelCase__,		self.unk_token		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        A :       str          =   []
        A :       Union[str, Any]          =   """"""
        for token in tokens:
            # make sure that special tokens are not decoded using sentencepiece model
            if token in self.all_special_tokens:
                A :       Tuple          =   self.sp_model.decode(lowerCamelCase__		)
                out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
                A :       List[Any]          =   []
            else:
                current_sub_tokens.append(lowerCamelCase__		)
        A :       str          =   self.sp_model.decode(lowerCamelCase__		)
        out_string += decoded.upper() if self.do_upper_case else decoded
        return out_string.strip()






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__,		lowerCamelCase__=None		):
        if token_ids_a is None:
            return self.prefix_tokens + token_ids_a + [self.eos_token_id]
        # 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.eos_token_id]






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__,		lowerCamelCase__ = None,		lowerCamelCase__ = False		):

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

        A :       Optional[int]          =   [1] * len(self.prefix_tokens		)
        A :       str          =   [1]
        if token_ids_a is None:
            return prefix_ones + ([0] * len(lowerCamelCase__		)) + suffix_ones
        return prefix_ones + ([0] * len(lowerCamelCase__		)) + ([0] * len(lowerCamelCase__		)) + suffix_ones






    def 			_lowerCAmelCase					(       self		):
        A :       List[Any]          =   self.encoder.copy()
        vocab.update(self.added_tokens_encoder		)
        return vocab






    def __getstate__(       self		):
        A :       List[str]          =   self.__dict__.copy()
        A :       Any          =   None
        return state






    def __setstate__(       self,		lowerCamelCase__		):
        A :       List[str]          =   d

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

        A :       str          =   load_spm(self.spm_file,		self.sp_model_kwargs		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__,		lowerCamelCase__ = None		):
        A :       Tuple          =   Path(lowerCamelCase__		)
        assert save_dir.is_dir(), f'''{save_directory} should be a directory'''
        A :       Tuple          =   save_dir / (
            (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
        )
        A :       Optional[int]          =   save_dir / (
            (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
        )

        save_json(self.encoder,		lowerCamelCase__		)

        if os.path.abspath(self.spm_file		) != os.path.abspath(lowerCamelCase__		) and os.path.isfile(self.spm_file		):
            copyfile(self.spm_file,		lowerCamelCase__		)
        elif not os.path.isfile(self.spm_file		):
            with open(lowerCamelCase__,		"""wb"""		) as fi:
                A :       List[Any]          =   self.sp_model.serialized_model_proto()
                fi.write(lowerCamelCase__		)

        return (str(lowerCamelCase__		), str(lowerCamelCase__		))




def 	__UpperCamelCase	(  _lowerCAmelCase      ,     _lowerCAmelCase		)       ->  sentencepiece.SentencePieceProcessor:



    """simple docstring"""






    A :       Union[str, Any]          =   sentencepiece.SentencePieceProcessor(**_lowerCAmelCase		)
    spm.Load(str(_lowerCAmelCase		)		)
    return spm




def 	__UpperCamelCase	(  _lowerCAmelCase		)       ->  Union[Dict, List]:



    """simple docstring"""






    with open(_lowerCAmelCase      ,     """r"""		) as f:
        return json.load(_lowerCAmelCase		)




def 	__UpperCamelCase	(  _lowerCAmelCase      ,     _lowerCAmelCase		)       ->  None:



    """simple docstring"""






    with open(_lowerCAmelCase      ,     """w"""		) as f:
        json.dump(_lowerCAmelCase      ,     _lowerCAmelCase      ,     indent=2		)







from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

SCREAMING_SNAKE_CASE_:List[Any]             =						TypeVar("""KEY""")
SCREAMING_SNAKE_CASE_:Dict             =						TypeVar("""VAL""")






@dataclass(frozen=SCREAMING_SNAKE_CASE__ ,						slots=SCREAMING_SNAKE_CASE__    )
class SCREAMING_SNAKE_CASE__     (		Generic[KEY, VAL]    ):




    '''simple docstring'''






    __lowerCamelCase			: KEY
    __lowerCamelCase			: VAL






class SCREAMING_SNAKE_CASE__     (		_Item    ):




    '''simple docstring'''






    def __init__(       self		):
        super().__init__(lowerCamelCase__,		lowerCamelCase__		)






    def __bool__(       self		):
        return False


SCREAMING_SNAKE_CASE_:Optional[Any]             =						_DeletedItem()






class SCREAMING_SNAKE_CASE__     (		MutableMapping[KEY, VAL]    ):




    '''simple docstring'''






    def __init__(       self,		lowerCamelCase__ = 8,		lowerCamelCase__ = 0.75		):
        A :       List[str]          =   initial_block_size
        A :       list[_Item | None]          =   [None] * initial_block_size
        assert 0.0 < capacity_factor < 1.0
        A :       Dict          =   capacity_factor
        A :       Optional[Any]          =   0






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        return hash(lowerCamelCase__		) % len(self._buckets		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        return (ind + 1) % len(self._buckets		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__,		lowerCamelCase__,		lowerCamelCase__		):
        A :       List[Any]          =   self._buckets[ind]
        if not stored:
            A :       Optional[int]          =   _Item(lowerCamelCase__,		lowerCamelCase__		)
            self._len += 1
            return True
        elif stored.key == key:
            A :       int          =   _Item(lowerCamelCase__,		lowerCamelCase__		)
            return True
        else:
            return False






    def 			_lowerCAmelCase					(       self		):
        A :       Union[str, Any]          =   len(self._buckets		) * self._capacity_factor
        return len(self		) >= int(lowerCamelCase__		)






    def 			_lowerCAmelCase					(       self		):
        if len(self._buckets		) <= self._initial_block_size:
            return False
        A :       Optional[Any]          =   len(self._buckets		) * self._capacity_factor / 2
        return len(self		) < limit






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        A :       Dict          =   self._buckets
        A :       Optional[Any]          =   [None] * new_size
        A :       List[str]          =   0
        for item in old_buckets:
            if item:
                self._add_item(item.key,		item.val		)






    def 			_lowerCAmelCase					(       self		):
        self._resize(len(self._buckets		) * 2		)






    def 			_lowerCAmelCase					(       self		):
        self._resize(len(self._buckets		) // 2		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__		):
        A :       Union[str, Any]          =   self._get_bucket_index(lowerCamelCase__		)
        for _ in range(len(self._buckets		)		):
            yield ind
            A :       Dict          =   self._get_next_ind(lowerCamelCase__		)






    def 			_lowerCAmelCase					(       self,		lowerCamelCase__,		lowerCamelCase__		):
        for ind in self._iterate_buckets(lowerCamelCase__		):
            if self._try_set(lowerCamelCase__,		lowerCamelCase__,		lowerCamelCase__		):
                break






    def __setitem__(       self,		lowerCamelCase__,		lowerCamelCase__		):
        if self._is_full():
            self._size_up()

        self._add_item(lowerCamelCase__,		lowerCamelCase__		)






    def __delitem__(       self,		lowerCamelCase__		):
        for ind in self._iterate_buckets(lowerCamelCase__		):
            A :       Tuple          =   self._buckets[ind]
            if item is None:
                raise KeyError(lowerCamelCase__		)
            if item is _deleted:
                continue
            if item.key == key:
                A :       int          =   _deleted
                self._len -= 1
                break
        if self._is_sparse():
            self._size_down()






    def __getitem__(       self,		lowerCamelCase__		):
        for ind in self._iterate_buckets(lowerCamelCase__		):
            A :       int          =   self._buckets[ind]
            if item is None:
                break
            if item is _deleted:
                continue
            if item.key == key:
                return item.val
        raise KeyError(lowerCamelCase__		)






    def __len__(       self		):
        return self._len






    def __iter__(       self		):
        yield from (item.key for item in self._buckets if item)






    def __repr__(       self		):
        A :       Union[str, Any]          =   """ ,""".join(
            f'''{item.key}: {item.val}''' for item in self._buckets if item		)
        return f'''HashMap({val_string})'''


