





import copy
import random

from transformers import CLIPTokenizer


class 			lowercase				(							a_     ):



						"""simple docstring"""

						def __init__(    self			:		Union[str, Any] ,				*lowerCamelCase_			:		Dict ,				**lowerCamelCase_			:		Any					):





										'''simple docstring'''







										super().__init__(*lowerCamelCase_ ,				**lowerCamelCase_					)
										_snake_case :			List[Any]  						=   {}







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





										'''simple docstring'''







										_snake_case :			List[str]  						=   super().add_tokens(lowerCamelCase_ ,				*lowerCamelCase_ ,				**lowerCamelCase_					)
										if num_added_tokens == 0:
														raise ValueError(
														    f'''The tokenizer already contains the token {placeholder_token}. Please pass a different'''
														    ' `placeholder_token` that is not already in the tokenizer.'					)







						def 		__UpperCAmelCase       (    self			:		str ,				lowerCamelCase_			:		str ,				*lowerCamelCase_			:		List[Any] ,				lowerCamelCase_			:		Any=1 ,				**lowerCamelCase_			:		Tuple					):





										'''simple docstring'''







										_snake_case :			Dict  						=   []
										if num_vec_per_token == 1:
														self.try_adding_tokens(lowerCamelCase_ ,				*lowerCamelCase_ ,				**lowerCamelCase_					)
														output.append(lowerCamelCase_					)
										else:
														_snake_case :			int  						=   []
														for i in range(lowerCamelCase_					):
																		_snake_case :			List[Any]  						=   placeholder_token + f'''_{i}'''
																		self.try_adding_tokens(lowerCamelCase_ ,				*lowerCamelCase_ ,				**lowerCamelCase_					)
																		output.append(lowerCamelCase_					)
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
										for token in self.token_map:
														if token in placeholder_token:
																		raise ValueError(
																		    f'''The tokenizer already has placeholder token {token} that can get confused with'''
																		    f''' {placeholder_token}keep placeholder tokens independent'''					)
										_snake_case :			Optional[Any]  						=   output







						def 		__UpperCAmelCase       (    self			:		Dict ,				lowerCamelCase_			:		Union[str, Any] ,				lowerCamelCase_			:		List[str]=False ,				lowerCamelCase_			:		Tuple=1.0					):





										'''simple docstring'''







										if isinstance(lowerCamelCase_ ,				lowerCamelCase_					):
														_snake_case :			List[Any]  						=   []
														for i in range(len(lowerCamelCase_					)					):
																		output.append(self.replace_placeholder_tokens_in_text(text[i] ,				vector_shuffle=lowerCamelCase_					)					)
														return output
										for placeholder_token in self.token_map:
														if placeholder_token in text:
																		_snake_case :			Dict  						=   self.token_map[placeholder_token]
																		_snake_case :			Tuple  						=   tokens[: 1 + int(len(lowerCamelCase_					) * prop_tokens_to_load					)]
																		if vector_shuffle:
																						_snake_case :			Optional[int]  						=   copy.copy(lowerCamelCase_					)
																						random.shuffle(lowerCamelCase_					)
																		_snake_case :			Dict  						=   text.replace(lowerCamelCase_ ,				' '.join(lowerCamelCase_					)					)
										return text







						def __call__(    self			:		List[Any] ,				lowerCamelCase_			:		Optional[Any] ,				*lowerCamelCase_			:		Dict ,				lowerCamelCase_			:		Tuple=False ,				lowerCamelCase_			:		Union[str, Any]=1.0 ,				**lowerCamelCase_			:		Union[str, Any]					):





										'''simple docstring'''







										return super().__call__(
										    self.replace_placeholder_tokens_in_text(
										        lowerCamelCase_ ,				vector_shuffle=lowerCamelCase_ ,				prop_tokens_to_load=lowerCamelCase_					) ,				*lowerCamelCase_ ,				**lowerCamelCase_ ,				)







						def 		__UpperCAmelCase       (    self			:		str ,				lowerCamelCase_			:		int ,				*lowerCamelCase_			:		Any ,				lowerCamelCase_			:		Dict=False ,				lowerCamelCase_			:		int=1.0 ,				**lowerCamelCase_			:		Any					):





										'''simple docstring'''







										return super().encode(
										    self.replace_placeholder_tokens_in_text(
										        lowerCamelCase_ ,				vector_shuffle=lowerCamelCase_ ,				prop_tokens_to_load=lowerCamelCase_					) ,				*lowerCamelCase_ ,				**lowerCamelCase_ ,				)












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 )






