


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,
)


lowerCAmelCase			=				pytest.mark.integration
@pytest.mark.parametrize('''path'''		,							['''paws''', '''csv''']	)
def      _a					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		inspect_dataset(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	)
		lowercase__				= path + '''.py'''
		assert script_name in os.listdir(SCREAMING_SNAKE_CASE	)
		assert "__pycache__" not in os.listdir(SCREAMING_SNAKE_CASE	)
@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					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		inspect_metric(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	)
		lowercase__				= path + '''.py'''
		assert script_name in os.listdir(SCREAMING_SNAKE_CASE	)
		assert "__pycache__" not in os.listdir(SCREAMING_SNAKE_CASE	)
@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					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		lowercase__				= get_dataset_config_info(SCREAMING_SNAKE_CASE		,							config_name=SCREAMING_SNAKE_CASE	)
		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					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		with pytest.raises(SCREAMING_SNAKE_CASE	):
				get_dataset_config_info(SCREAMING_SNAKE_CASE		,							config_name=SCREAMING_SNAKE_CASE	)
@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					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		lowercase__				= get_dataset_config_names(SCREAMING_SNAKE_CASE	)
		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					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		lowercase__				= get_dataset_infos(SCREAMING_SNAKE_CASE	)
		assert list(infos.keys()	) == expected_configs
		lowercase__				= expected_configs[0]
		assert expected_config in infos
		lowercase__				= 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					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		lowercase__				= get_dataset_infos(SCREAMING_SNAKE_CASE	)
		assert expected_config in infos
		lowercase__				= 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					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		with pytest.raises(SCREAMING_SNAKE_CASE	):
				get_dataset_split_names(SCREAMING_SNAKE_CASE		,							config_name=SCREAMING_SNAKE_CASE	)







"""simple docstring"""






import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


snake_case   					=				logging.get_logger(__name__)

snake_case   					=				{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case   					=				{
    '''vocab_file''': {
        '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt''',
        '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt''',
        '''junnyu/roformer_chinese_char_small''': (
            '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt'''
        ),
        '''junnyu/roformer_chinese_char_base''': (
            '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt'''
        ),
        '''junnyu/roformer_small_discriminator''': (
            '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt'''
        ),
        '''junnyu/roformer_small_generator''': (
            '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt'''
        ),
    }
}

snake_case   					=				{
    '''junnyu/roformer_chinese_small''': 1_5_3_6,
    '''junnyu/roformer_chinese_base''': 1_5_3_6,
    '''junnyu/roformer_chinese_char_small''': 5_1_2,
    '''junnyu/roformer_chinese_char_base''': 5_1_2,
    '''junnyu/roformer_small_discriminator''': 1_2_8,
    '''junnyu/roformer_small_generator''': 1_2_8,
}


snake_case   					=				{
    '''junnyu/roformer_chinese_small''': {'''do_lower_case''': True},
    '''junnyu/roformer_chinese_base''': {'''do_lower_case''': True},
    '''junnyu/roformer_chinese_char_small''': {'''do_lower_case''': True},
    '''junnyu/roformer_chinese_char_base''': {'''do_lower_case''': True},
    '''junnyu/roformer_small_discriminator''': {'''do_lower_case''': True},
    '''junnyu/roformer_small_generator''': {'''do_lower_case''': True},
}



class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):
   A__		:	str           =  VOCAB_FILES_NAMES
   A__		:	Tuple           =  PRETRAINED_VOCAB_FILES_MAP
   A__		:	List[Any]           =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A__		:	Dict           =  PRETRAINED_INIT_CONFIGURATION
   A__		:	Any           =  RoFormerTokenizer



   def __init__(       self    :	Optional[int]							,       __lowerCamelCase    :	Any=None							,       __lowerCamelCase    :	Optional[Any]=None							,       __lowerCamelCase    :	int=True							,       __lowerCamelCase    :	Any="[UNK]"							,       __lowerCamelCase    :	Tuple="[SEP]"							,       __lowerCamelCase    :	Optional[Any]="[PAD]"							,       __lowerCamelCase    :	Union[str, Any]="[CLS]"							,       __lowerCamelCase    :	int="[MASK]"							,       __lowerCamelCase    :	str=True							,       __lowerCamelCase    :	List[Any]=None							,       **__lowerCamelCase    :	Any							,       ):



     """simple docstring"""
     super().__init__(
         __lowerCamelCase							,       tokenizer_file=__lowerCamelCase							,       do_lower_case=__lowerCamelCase							,       unk_token=__lowerCamelCase							,       sep_token=__lowerCamelCase							,       pad_token=__lowerCamelCase							,       cls_token=__lowerCamelCase							,       mask_token=__lowerCamelCase							,       tokenize_chinese_chars=__lowerCamelCase							,       strip_accents=__lowerCamelCase							,       **__lowerCamelCase							,       )

     _snake_case   	=      json.loads(self.backend_tokenizer.normalizer.__getstate__()				)
     if (
         pre_tok_state.get('''lowercase'''							,       __lowerCamelCase				) != do_lower_case
         or pre_tok_state.get('''strip_accents'''							,       __lowerCamelCase				) != strip_accents
     ):
       _snake_case   	=      getattr(__lowerCamelCase							,       pre_tok_state.pop('''type'''				)				)
       _snake_case   	=      do_lower_case
       _snake_case   	=      strip_accents
       _snake_case   	=      pre_tok_class(**__lowerCamelCase				)

     _snake_case   	=      do_lower_case



   def __getstate__(       self    :	int				):



     """simple docstring"""
     _snake_case   	=      self.__dict__.copy()
     _snake_case   	=      BertPreTokenizer()
     return state



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



     """simple docstring"""
     _snake_case   	=      d
     _snake_case   	=      self.__dict__['''_tokenizer'''].get_vocab()
     _snake_case   	=      PreTokenizer.custom(JiebaPreTokenizer(__lowerCamelCase				)				)



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



     """simple docstring"""
     _snake_case   	=      [self.cls_token_id] + token_ids_a + [self.sep_token_id]

     if token_ids_a:
       output += token_ids_a + [self.sep_token_id]

     return output



   def    __UpperCAmelCase    (       self    :	Dict							,       __lowerCamelCase    :	List[int]							,       __lowerCamelCase    :	Optional[List[int]] = None				):



     """simple docstring"""
     _snake_case   	=      [self.sep_token_id]
     _snake_case   	=      [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				) * [0] + len(token_ids_a + sep				) * [1]



   def    __UpperCAmelCase    (       self    :	Union[str, Any]							,       __lowerCamelCase    :	str							,       __lowerCamelCase    :	Optional[str] = None				):



     """simple docstring"""
     _snake_case   	=      self._tokenizer.model.save(__lowerCamelCase							,       name=__lowerCamelCase				)
     return tuple(__lowerCamelCase				)





   def    __UpperCAmelCase    (       self    :	Optional[int]							,       __lowerCamelCase    :	List[str]							,       __lowerCamelCase    :	List[str]=None							,       __lowerCamelCase    :	Union[str, Any]=None							,       __lowerCamelCase    :	List[str]=False							,       **__lowerCamelCase    :	List[Any]							,       ):



     """simple docstring"""
     _snake_case   	=      BertPreTokenizer()
     return super().save_pretrained(__lowerCamelCase							,       __lowerCamelCase							,       __lowerCamelCase							,       __lowerCamelCase							,       **__lowerCamelCase				)





