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


_SCREAMING_SNAKE_CASE    :      int          =			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE    :      Optional[Any]          =			{
    '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  UpperCamelCase__		(    lowercase_   ):







	'''simple docstring'''
	_lowerCAmelCase							       =				"luke"





	def __init__(			self				,       UpperCamelCase__=5_0267				,       UpperCamelCase__=50_0000				,       UpperCamelCase__=768				,       UpperCamelCase__=256				,       UpperCamelCase__=12				,       UpperCamelCase__=12				,       UpperCamelCase__=3072				,       UpperCamelCase__="gelu"				,       UpperCamelCase__=0.1				,       UpperCamelCase__=0.1				,       UpperCamelCase__=512				,       UpperCamelCase__=2				,       UpperCamelCase__=0.0_2				,       UpperCamelCase__=1e-12				,       UpperCamelCase__=True				,       UpperCamelCase__=None				,       UpperCamelCase__=1				,       UpperCamelCase__=0				,       UpperCamelCase__=2				,       **UpperCamelCase__				,       ):
							super().__init__(pad_token_id=lowerCamelCase_				,       bos_token_id=lowerCamelCase_				,       eos_token_id=lowerCamelCase_				,       **lowerCamelCase_		)

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

import numpy as np

_SCREAMING_SNAKE_CASE    :      Any          =			[
    ['a', 'b', 'c', 'd', 'e'],
    ['f', 'g', 'h', 'i', 'k'],
    ['l', 'm', 'n', 'o', 'p'],
    ['q', 'r', 's', 't', 'u'],
    ['v', 'w', 'x', 'y', 'z'],
]







class  UpperCamelCase__		:







	'''simple docstring'''





	def __init__(			self		):
					A__  :	List[Any]         =							np.array(UpperCamelCase__		)





	def   __snake_case				(			self				,       UpperCamelCase__		):
					A__       ,							A__  :	Any         =							np.where(letter == self.SQUARE		)
					A__  :	int         =							np.concatenate([indexa + 1, indexa + 1]		)
					return indexes





	def   __snake_case				(			self				,       UpperCamelCase__				,       UpperCamelCase__		):
					A__  :	Union[str, Any]         =							self.SQUARE[indexa - 1, indexa - 1]
					return letter





	def   __snake_case				(			self				,       UpperCamelCase__		):
					A__  :	List[str]         =							message.lower()
					A__  :	str         =							message.replace(''' '''				,       ''''''		)
					A__  :	Union[str, Any]         =							message.replace('''j'''				,       '''i'''		)

					A__  :	List[Any]         =							np.empty((2, len(UpperCamelCase__		))		)
					for letter_index in range(len(UpperCamelCase__		)		):
									A__  :	Any         =							self.letter_to_numbers(message[letter_index]		)

									A__  :	Optional[Any]         =							numbers[0]
									A__  :	List[str]         =							numbers[1]

					A__  :	List[str]         =							first_step.reshape(2 * len(UpperCamelCase__		)		)
					A__  :	List[Any]         =							''''''
					for numbers_index in range(len(UpperCamelCase__		)		):
									A__  :	Dict         =							int(second_step[numbers_index * 2]		)
									A__  :	List[str]         =							int(second_step[(numbers_index * 2) + 1]		)
									A__  :	Dict         =							self.numbers_to_letter(UpperCamelCase__				,       UpperCamelCase__		)
									A__  :	Tuple         =							encoded_message + letter

					return encoded_message





	def   __snake_case				(			self				,       UpperCamelCase__		):
					A__  :	str         =							message.lower()
					message.replace(''' '''				,       ''''''		)
					A__  :	List[Any]         =							np.empty(2 * len(UpperCamelCase__		)		)
					for letter_index in range(len(UpperCamelCase__		)		):
									A__  :	List[str]         =							self.letter_to_numbers(message[letter_index]		)
									A__  :	Dict         =							numbers[0]
									A__  :	int         =							numbers[1]

					A__  :	Optional[Any]         =							first_step.reshape((2, len(UpperCamelCase__		))		)
					A__  :	int         =							''''''
					for numbers_index in range(len(UpperCamelCase__		)		):
									A__  :	Tuple         =							int(second_step[0, numbers_index]		)
									A__  :	Dict         =							int(second_step[1, numbers_index]		)
									A__  :	List[str]         =							self.numbers_to_letter(UpperCamelCase__				,       UpperCamelCase__		)
									A__  :	Tuple         =							decoded_message + letter

					return decoded_message