





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


lowercase_		:				Any				=						logging.get_logger(__name__)

lowercase_		:				Any				=						'''▁'''

lowercase_		:				str				=						{
    '''vocab_file''': '''vocab.json''',
    '''spm_file''': '''sentencepiece.bpe.model''',
}

lowercase_		:				Dict				=						{
    '''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'''
        )
    },
}

lowercase_		:				Dict				=						{
    '''facebook/s2t-small-librispeech-asr''': 1024,
}

lowercase_		:				List[Any]				=						['''pt''', '''fr''', '''ru''', '''nl''', '''ro''', '''it''', '''es''', '''de''']

lowercase_		:				Optional[Any]				=						{'''mustc''': MUSTC_LANGS}


class 			lowercase				(							a_     ):



						"""simple docstring"""

						_UpperCamelCase  :	Dict								=	VOCAB_FILES_NAMES
						_UpperCamelCase  :	Tuple								=	PRETRAINED_VOCAB_FILES_MAP
						_UpperCamelCase  :	Tuple								=	MAX_MODEL_INPUT_SIZES
						_UpperCamelCase  :	Optional[int]								=	["input_ids", "attention_mask"]

						_UpperCamelCase  :	List[int]								=	[]







						def __init__(    self			:		str ,				lowerCamelCase_			:		Union[str, Any] ,				lowerCamelCase_			:		Union[str, Any] ,				lowerCamelCase_			:		List[Any]="<s>" ,				lowerCamelCase_			:		str="</s>" ,				lowerCamelCase_			:		Union[str, Any]="<pad>" ,				lowerCamelCase_			:		int="<unk>" ,				lowerCamelCase_			:		int=False ,				lowerCamelCase_			:		Any=False ,				lowerCamelCase_			:		Optional[int]=None ,				lowerCamelCase_			:		List[str]=None ,				lowerCamelCase_			:		Optional[Dict[str, Any]] = None ,				**lowerCamelCase_			:		Optional[Any] ,				):





										'''simple docstring'''







										_snake_case :			Any  						=   {} 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_ ,				)
										_snake_case :			Union[str, Any]  						=   do_upper_case
										_snake_case :			List[str]  						=   do_lower_case

										_snake_case :			Tuple  						=   load_json(lowerCamelCase_					)
										_snake_case :			int  						=   {v: k for k, v in self.encoder.items()}
										_snake_case :			List[str]  						=   spm_file
										_snake_case :			Dict  						=   load_spm(lowerCamelCase_ ,				self.sp_model_kwargs					)

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

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

														self.set_tgt_lang_special_tokens(self._tgt_lang					)
										else:
														_snake_case :			List[Any]  						=   {}







						@property
						def 		__UpperCAmelCase       (    self			:		List[str]					):





										'''simple docstring'''







										return len(self.encoder					)







						@property
						def 		__UpperCAmelCase       (    self			:		Any					):





										'''simple docstring'''







										return self._tgt_lang







						@tgt_lang.setter
						def 		__UpperCAmelCase       (    self			:		Dict ,				lowerCamelCase_			:		Any					):





										'''simple docstring'''







										_snake_case :			Any  						=   new_tgt_lang
										self.set_tgt_lang_special_tokens(lowerCamelCase_					)







						def 		__UpperCAmelCase       (    self			:		Union[str, Any] ,				lowerCamelCase_			:		str					):





										'''simple docstring'''







										_snake_case :			Dict  						=   self.lang_code_to_id[tgt_lang]
										_snake_case :			Optional[Any]  						=   [lang_code_id]







						def 		__UpperCAmelCase       (    self			:		str ,				lowerCamelCase_			:		str					):





										'''simple docstring'''







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







						def 		__UpperCAmelCase       (    self			:		Optional[int] ,				lowerCamelCase_			:		Optional[Any]					):





										'''simple docstring'''







										return self.encoder.get(lowerCamelCase_ ,				self.encoder[self.unk_token]					)







						def 		__UpperCAmelCase       (    self			:		Optional[int] ,				lowerCamelCase_			:		int					):





										'''simple docstring'''







										return self.decoder.get(lowerCamelCase_ ,				self.unk_token					)







						def 		__UpperCAmelCase       (    self			:		Dict ,				lowerCamelCase_			:		List[str]					):





										'''simple docstring'''







										_snake_case :			int  						=   []
										_snake_case :			List[str]  						=   ''
										for token in tokens:
														# make sure that special tokens are not decoded using sentencepiece model
														if token in self.all_special_tokens:
																		_snake_case :			Dict  						=   self.sp_model.decode(lowerCamelCase_					)
																		out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
																		_snake_case :			Optional[int]  						=   []
														else:
																		current_sub_tokens.append(lowerCamelCase_					)
										_snake_case :			Any  						=   self.sp_model.decode(lowerCamelCase_					)
										out_string += decoded.upper() if self.do_upper_case else decoded
										return out_string.strip()







						def 		__UpperCAmelCase       (    self			:		List[Any] ,				lowerCamelCase_			:		List[Any] ,				lowerCamelCase_			:		Optional[Any]=None					):





										'''simple docstring'''







										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			:		int ,				lowerCamelCase_			:		List[int] ,				lowerCamelCase_			:		Optional[List[int]] = None ,				lowerCamelCase_			:		bool = False					):





										'''simple docstring'''







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

										_snake_case :			List[str]  						=   [1] * len(self.prefix_tokens					)
										_snake_case :			Optional[Any]  						=   [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 		__UpperCAmelCase       (    self			:		int					):





										'''simple docstring'''







										_snake_case :			Any  						=   self.encoder.copy()
										vocab.update(self.added_tokens_encoder					)
										return vocab







						def __getstate__(    self			:		int					):





										'''simple docstring'''







										_snake_case :			Union[str, Any]  						=   self.__dict__.copy()
										_snake_case :			int  						=   None
										return state







						def __setstate__(    self			:		Optional[Any] ,				lowerCamelCase_			:		Dict					):





										'''simple docstring'''







										_snake_case :			Dict  						=   d

										# for backward compatibility
										if not hasattr(self ,				'sp_model_kwargs'					):
														_snake_case :			List[str]  						=   {}

										_snake_case :			int  						=   load_spm(self.spm_file ,				self.sp_model_kwargs					)







						def 		__UpperCAmelCase       (    self			:		str ,				lowerCamelCase_			:		str ,				lowerCamelCase_			:		Optional[str] = None					):





										'''simple docstring'''







										_snake_case :			Optional[int]  						=   Path(lowerCamelCase_					)
										assert save_dir.is_dir(), f'''{save_directory} should be a directory'''
										_snake_case :			Any  						=   save_dir / (
										    (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
										)
										_snake_case :			Optional[Any]  						=   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:
																		_snake_case :			Union[str, Any]  						=   self.sp_model.serialized_model_proto()
																		fi.write(lowerCamelCase_					)

										return (str(lowerCamelCase_					), str(lowerCamelCase_					))



def       A__(		__lowerCAmelCase	,			__lowerCAmelCase ):
				_snake_case :			Optional[Any]  						=   sentencepiece.SentencePieceProcessor(**__lowerCAmelCase )
				spm.Load(str(__lowerCAmelCase ) )
				return spm

def       A__(		__lowerCAmelCase ):
				with open(__lowerCAmelCase	,			'r' ) as f:
								return json.load(__lowerCAmelCase )

def       A__(		__lowerCAmelCase	,			__lowerCAmelCase ):
				with open(__lowerCAmelCase	,			'w' ) as f:
								json.dump(__lowerCAmelCase	,			__lowerCAmelCase	,			indent=2 )












import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


lowercase_		:				Optional[Any]				=						pytest.mark.integration

@pytest.mark.parametrize('path'	,			['paws', 'csv'] )
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase ):
				inspect_dataset(__lowerCAmelCase	,			__lowerCAmelCase )
				_snake_case :			str  						=   path + '.py'
				assert script_name in os.listdir(__lowerCAmelCase )
				assert "__pycache__" not in os.listdir(__lowerCAmelCase )

@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning' )
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning' )
@pytest.mark.parametrize('path'	,			['accuracy'] )
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase ):
				inspect_metric(__lowerCAmelCase	,			__lowerCAmelCase )
				_snake_case :			Tuple  						=   path + '.py'
				assert script_name in os.listdir(__lowerCAmelCase )
				assert "__pycache__" not in os.listdir(__lowerCAmelCase )

@pytest.mark.parametrize(
    'path, config_name, expected_splits'	,			[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]	,			)
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				_snake_case :			Union[str, Any]  						=   get_dataset_config_info(__lowerCAmelCase	,			config_name=__lowerCAmelCase )
				assert info.config_name == config_name
				assert list(info.splits.keys() ) == expected_splits

@pytest.mark.parametrize(
    'path, config_name, expected_exception'	,			[
        ('paws', None, ValueError),
    ]	,			)
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				with pytest.raises(__lowerCAmelCase ):
								get_dataset_config_info(__lowerCAmelCase	,			config_name=__lowerCAmelCase )

@pytest.mark.parametrize(
    'path, expected'	,			[
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]	,			)
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase ):
				_snake_case :			Optional[Any]  						=   get_dataset_config_names(__lowerCAmelCase )
				assert expected in config_names

@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'	,			[
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]	,			)
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				_snake_case :			List[Any]  						=   get_dataset_infos(__lowerCAmelCase )
				assert list(infos.keys() ) == expected_configs
				_snake_case :			Any  						=   expected_configs[0]
				assert expected_config in infos
				_snake_case :			str  						=   infos[expected_config]
				assert info.config_name == expected_config
				assert list(info.splits.keys() ) == expected_splits_in_first_config

@pytest.mark.parametrize(
    'path, expected_config, expected_splits'	,			[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]	,			)
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				_snake_case :			Any  						=   get_dataset_infos(__lowerCAmelCase )
				assert expected_config in infos
				_snake_case :			Any  						=   infos[expected_config]
				assert info.config_name == expected_config
				assert list(info.splits.keys() ) == expected_splits

@pytest.mark.parametrize(
    'path, config_name, expected_exception'	,			[
        ('paws', None, ValueError),
    ]	,			)
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				with pytest.raises(__lowerCAmelCase ):
								get_dataset_split_names(__lowerCAmelCase	,			config_name=__lowerCAmelCase )






