
import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


lowerCamelCase__ :       Union[str, Any]						     =			namedtuple(
    "_TestCommandArgs",
    [
        "dataset",
        "name",
        "cache_dir",
        "data_dir",
        "all_configs",
        "save_infos",
        "ignore_verifications",
        "force_redownload",
        "clear_cache",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)





def __A						(   a_ :							Optional[Any]		,		a_ :							int     )->							Tuple:




		'''simple docstring'''






		return (abs(source - target     ) / target) < 0.01





@pytest.mark.integration
def __A						(   a_ :							List[Any]     )->							int:




		'''simple docstring'''






		SCREAMING_SNAKE_CASE       :     Optional[Any]				= _TestCommandArgs(dataset=a_		,		all_configs=a_		,		save_infos=a_     )
		SCREAMING_SNAKE_CASE       :     int				= TestCommand(*a_     )
		test_command.run()
		SCREAMING_SNAKE_CASE       :     Optional[int]				= os.path.join(a_		,		'''README.md'''     )
		assert os.path.exists(a_     )
		SCREAMING_SNAKE_CASE       :     Dict				= DatasetInfosDict.from_directory(a_     )
		SCREAMING_SNAKE_CASE       :     Any				= DatasetInfosDict(
		    {
		        '''default''': DatasetInfo(
		            features=Features(
		                {
		                    '''tokens''': Sequence(Value('''string'''     )     ),
		                    '''ner_tags''': Sequence(
		                        ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']     )     ),
		                    '''langs''': Sequence(Value('''string'''     )     ),
		                    '''spans''': Sequence(Value('''string'''     )     ),
		                }     )		,		splits=[
		                {
		                    '''name''': '''train''',
		                    '''num_bytes''': 2_35_15_63,
		                    '''num_examples''': 1_00_00,
		                },
		                {
		                    '''name''': '''validation''',
		                    '''num_bytes''': 23_84_18,
		                    '''num_examples''': 10_00,
		                },
		            ]		,		download_size=3_94_06_80		,		dataset_size=2_58_99_81		,		)
		    }     )
		assert dataset_infos.keys() == expected_dataset_infos.keys()
		for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
				SCREAMING_SNAKE_CASE       :     Any				= getattr(dataset_infos['''default''']		,		a_     ), getattr(expected_dataset_infos['''default''']		,		a_     )
				if key == "num_bytes":
						assert is_apercent_close(a_		,		a_     )
				elif key == "splits":
						assert list(a_     ) == list(a_     )
						for split in result:
								assert result[split].name == expected[split].name
								assert result[split].num_examples == expected[split].num_examples
								assert is_apercent_close(result[split].num_bytes		,		expected[split].num_bytes     )
				else:
						result == expected







"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase__ :       Tuple						     =			logging.get_logger(__name__)

lowerCamelCase__ :       str						     =			{
    "studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
    "studio-ousia/luke-large": "https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json",
}




class 				lowercase__(				_UpperCAmelCase   ):
	'''simple docstring'''

	UpperCamelCase				=  """luke"""





	def __init__(						self    :Optional[int]		, lowerCamelCase_    :Union[str, Any]=5_02_67		, lowerCamelCase_    :int=50_00_00		, lowerCamelCase_    :Tuple=7_68		, lowerCamelCase_    :List[str]=2_56		, lowerCamelCase_    :Dict=12		, lowerCamelCase_    :Optional[int]=12		, lowerCamelCase_    :Optional[Any]=30_72		, lowerCamelCase_    :List[Any]="gelu"		, lowerCamelCase_    :Any=0.1		, lowerCamelCase_    :Union[str, Any]=0.1		, lowerCamelCase_    :List[str]=5_12		, lowerCamelCase_    :Optional[int]=2		, lowerCamelCase_    :Tuple=0.0_2		, lowerCamelCase_    :Optional[int]=1E-12		, lowerCamelCase_    :List[Any]=True		, lowerCamelCase_    :List[str]=None		, lowerCamelCase_    :str=1		, lowerCamelCase_    :Any=0		, lowerCamelCase_    :str=2		, **lowerCamelCase_    :List[Any]		, )							->			Optional[int]:







			'''simple docstring'''




			super().__init__(pad_token_id=lowerCamelCase_		, bos_token_id=lowerCamelCase_		, eos_token_id=lowerCamelCase_		, **lowerCamelCase_					)

			SCREAMING_SNAKE_CASE       :     Dict				= vocab_size
			SCREAMING_SNAKE_CASE       :     List[str]				= entity_vocab_size
			SCREAMING_SNAKE_CASE       :     str				= hidden_size
			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= entity_emb_size
			SCREAMING_SNAKE_CASE       :     List[Any]				= num_hidden_layers
			SCREAMING_SNAKE_CASE       :     Optional[int]				= num_attention_heads
			SCREAMING_SNAKE_CASE       :     Optional[Any]				= hidden_act
			SCREAMING_SNAKE_CASE       :     Optional[Any]				= intermediate_size
			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= hidden_dropout_prob
			SCREAMING_SNAKE_CASE       :     Dict				= attention_probs_dropout_prob
			SCREAMING_SNAKE_CASE       :     Dict				= max_position_embeddings
			SCREAMING_SNAKE_CASE       :     Tuple				= type_vocab_size
			SCREAMING_SNAKE_CASE       :     str				= initializer_range
			SCREAMING_SNAKE_CASE       :     Dict				= layer_norm_eps
			SCREAMING_SNAKE_CASE       :     Optional[int]				= use_entity_aware_attention
			SCREAMING_SNAKE_CASE       :     List[str]				= classifier_dropout





