


'''simple docstring'''




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


__snake_case    						=logging.get_logger(__name__)

__snake_case    						="""▁"""

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

__snake_case    						={
    """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"""
        )
    },
}

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

__snake_case    						=["""pt""", """fr""", """ru""", """nl""", """ro""", """it""", """es""", """de"""]

__snake_case    						={"""mustc""": MUSTC_LANGS}

class 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	int		=     VOCAB_FILES_NAMES
     lowerCamelCase				:	Tuple		=     PRETRAINED_VOCAB_FILES_MAP
     lowerCamelCase				:	Union[str, Any]		=     MAX_MODEL_INPUT_SIZES
     lowerCamelCase				:	List[str]		=     ['''input_ids''', '''attention_mask''']

     lowerCamelCase				:	List[int]		=     []





     def __init__( self       :      Optional[int]    ,      UpperCAmelCase__       :      Any    ,      UpperCAmelCase__       :      int    ,      UpperCAmelCase__       :      List[str]="<s>"    ,      UpperCAmelCase__       :      str="</s>"    ,      UpperCAmelCase__       :      str="<pad>"    ,      UpperCAmelCase__       :      Tuple="<unk>"    ,      UpperCAmelCase__       :      Any=False    ,      UpperCAmelCase__       :      str=False    ,      UpperCAmelCase__       :      Tuple=None    ,      UpperCAmelCase__       :      Optional[Any]=None    ,      UpperCAmelCase__       :      Optional[Dict[str, Any]] = None    ,      **UpperCAmelCase__       :      str    ,      )				->  None:
        lowerCAmelCase     =			{} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=UpperCAmelCase__    ,      eos_token=UpperCAmelCase__    ,      unk_token=UpperCAmelCase__    ,      pad_token=UpperCAmelCase__    ,      do_upper_case=UpperCAmelCase__    ,      do_lower_case=UpperCAmelCase__    ,      tgt_lang=UpperCAmelCase__    ,      lang_codes=UpperCAmelCase__    ,      sp_model_kwargs=self.sp_model_kwargs    ,      **UpperCAmelCase__    ,      )
        lowerCAmelCase     =			do_upper_case
        lowerCAmelCase     =			do_lower_case

        lowerCAmelCase     =			load_json(UpperCAmelCase__    )
        lowerCAmelCase     =			{v: k for k, v in self.encoder.items()}
        lowerCAmelCase     =			spm_file
        lowerCAmelCase     =			load_spm(UpperCAmelCase__    ,      self.sp_model_kwargs    )

        if lang_codes is not None:
           lowerCAmelCase     =			lang_codes
           lowerCAmelCase     =			LANGUAGES[lang_codes]
           lowerCAmelCase     =			[F'''<lang:{lang}>''' for lang in self.langs]
           lowerCAmelCase     =			{lang: self.sp_model.PieceToId(F'''<lang:{lang}>'''    ) for lang in self.langs}

           lowerCAmelCase     =			self.lang_tokens
           lowerCAmelCase     =			tgt_lang if tgt_lang is not None else self.langs[0]

           self.set_tgt_lang_special_tokens(self._tgt_lang    )
        else:
           lowerCAmelCase     =			{}





     @property
     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  int:
        return len(self.encoder    )





     @property
     def 							__UpperCAmelCase      ( self       :      Tuple    )				->  str:
        return self._tgt_lang





     @tgt_lang.setter
     def 							__UpperCAmelCase      ( self       :      Dict    ,      UpperCAmelCase__       :      Tuple    )				->  None:
        lowerCAmelCase     =			new_tgt_lang
        self.set_tgt_lang_special_tokens(UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      str    )				->  None:
        lowerCAmelCase     =			self.lang_code_to_id[tgt_lang]
        lowerCAmelCase     =			[lang_code_id]





     def 							__UpperCAmelCase      ( self       :      Optional[int]    ,      UpperCAmelCase__       :      str    )				->  List[str]:
        return self.sp_model.encode(UpperCAmelCase__    ,      out_type=UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      Dict    )				->  Optional[int]:
        return self.encoder.get(UpperCAmelCase__    ,      self.encoder[self.unk_token]    )





     def 							__UpperCAmelCase      ( self       :      Optional[Any]    ,      UpperCAmelCase__       :      int    )				->  str:
        return self.decoder.get(UpperCAmelCase__    ,      self.unk_token    )





     def 							__UpperCAmelCase      ( self       :      Tuple    ,      UpperCAmelCase__       :      List[str]    )				->  str:
        lowerCAmelCase     =			[]
        lowerCAmelCase     =			''
        for token in tokens:
           # make sure that special tokens are not decoded using sentencepiece model
           if token in self.all_special_tokens:
              lowerCAmelCase     =			self.sp_model.decode(UpperCAmelCase__    )
              out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
              lowerCAmelCase     =			[]
           else:
              current_sub_tokens.append(UpperCAmelCase__    )
        lowerCAmelCase     =			self.sp_model.decode(UpperCAmelCase__    )
        out_string += decoded.upper() if self.do_upper_case else decoded
        return out_string.strip()





     def 							__UpperCAmelCase      ( self       :      Any    ,      UpperCAmelCase__       :      int    ,      UpperCAmelCase__       :      Dict=None    )				->  List[int]:
        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 							__UpperCAmelCase      ( self       :      Optional[int]    ,      UpperCAmelCase__       :      List[int]    ,      UpperCAmelCase__       :      Optional[List[int]] = None    ,      UpperCAmelCase__       :      bool = False    )				->  List[int]:

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

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





     def 							__UpperCAmelCase      ( self       :      str    )				->  Dict:
        lowerCAmelCase     =			self.encoder.copy()
        vocab.update(self.added_tokens_encoder    )
        return vocab





     def __getstate__( self       :      int    )				->  Dict:
        lowerCAmelCase     =			self.__dict__.copy()
        lowerCAmelCase     =			None
        return state





     def __setstate__( self       :      Optional[Any]    ,      UpperCAmelCase__       :      Dict    )				->  None:
        lowerCAmelCase     =			d

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

        lowerCAmelCase     =			load_spm(self.spm_file    ,      self.sp_model_kwargs    )





     def 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      str    ,      UpperCAmelCase__       :      Optional[str] = None    )				->  Tuple[str]:
        lowerCAmelCase     =			Path(UpperCAmelCase__    )
        assert save_dir.is_dir(), F'''{save_directory} should be a directory'''
        lowerCAmelCase     =			save_dir / (
            (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
        )
        lowerCAmelCase     =			save_dir / (
            (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
        )

        save_json(self.encoder    ,      UpperCAmelCase__    )

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

        return (str(UpperCAmelCase__    ), str(UpperCAmelCase__    ))





def 	a_					( lowerCamelCase	:     str	, lowerCamelCase	:     Dict[str, Any]				):
   lowerCAmelCase     =			sentencepiece.SentencePieceProcessor(**lowerCamelCase				)
   spm.Load(str(lowerCamelCase				)				)
   return spm





def 	a_					( lowerCamelCase	:     str				):
   with open(lowerCamelCase	, 'r'				) as f:
      return json.load(lowerCamelCase				)





def 	a_					( lowerCamelCase	:     Tuple	, lowerCamelCase	:     str				):
   with open(lowerCamelCase	, 'w'				) as f:
      json.dump(lowerCamelCase	, lowerCamelCase	, indent=2				)








"""simple docstring"""


import pytest

from datasets import inspect_metric, list_metrics, load_metric






@pytest.fixture
def     a__    (    __SCREAMING_SNAKE_CASE )	->	Union[str, Any]:
		monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings"					, set() )






@pytest.fixture
def     a__    (    __SCREAMING_SNAKE_CASE )	->	str:





		class     snake_case	:

						def __init__(	self							:				int     ,  UpperCamelCase__							:				Optional[int])->   Union[str, Any]:



								'''simple docstring'''


								__lowerCAmelCase:       str          =			metric_id





		class     snake_case	:
						SCREAMING_SNAKE_CASE_   :      List[Any]         =  [MetricMock(__snake_case  ) for metric_id in ["""accuracy""", """mse""", """precision""", """codeparrot/apps_metric"""]]

						def 							lowercase_     (	self							:				Tuple)->   Union[str, Any]:



								'''simple docstring'''


								return self._metrics


		monkeypatch.setattr("datasets.inspect.huggingface_hub"					, HfhMock() )






@pytest.mark.parametrize(
    "func, args"					, [(load_metric, ("metrics/mse",)), (list_metrics, ()), (inspect_metric, ("metrics/mse", "tmp_path"))] )
def     a__    (    __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE )	->	Optional[Any]:
		if "tmp_path" in args:
				__lowerCAmelCase:       Tuple          =			tuple(arg if arg != "tmp_path" else tmp_path for arg in args )
		with pytest.warns(__SCREAMING_SNAKE_CASE					, match="https://huggingface.co/docs/evaluate" ):
				func(*__SCREAMING_SNAKE_CASE )


