






'''simple docstring'''







from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
			from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


_A     :      Tuple     					=logging.get_logger(__name__)

_A     :      Optional[int]     					={
    '''microsoft/deberta-v2-xlarge''': '''https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/config.json''',
    '''microsoft/deberta-v2-xxlarge''': '''https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/config.json''',
    '''microsoft/deberta-v2-xlarge-mnli''': (
        '''https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/config.json'''
    ),
    '''microsoft/deberta-v2-xxlarge-mnli''': (
        '''https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/config.json'''
    ),
}

class _lowercase     (    snake_case_		):
							a    				=	"deberta-v2"




							def __init__(							self:    List[Any]      ,							UpperCamelCase__:    Optional[Any]=128_100      ,							UpperCamelCase__:    List[str]=1_536      ,							UpperCamelCase__:    Any=24      ,							UpperCamelCase__:    List[Any]=24      ,							UpperCamelCase__:    Optional[int]=6_144      ,							UpperCamelCase__:    int="gelu"      ,							UpperCamelCase__:    int=0.1      ,							UpperCamelCase__:    List[str]=0.1      ,							UpperCamelCase__:    List[str]=512      ,							UpperCamelCase__:    Tuple=0      ,							UpperCamelCase__:    str=0.02      ,							UpperCamelCase__:    Any=1e-7      ,							UpperCamelCase__:    List[str]=False      ,							UpperCamelCase__:    List[Any]=-1      ,							UpperCamelCase__:    Tuple=0      ,							UpperCamelCase__:    List[Any]=True      ,							UpperCamelCase__:    str=None      ,							UpperCamelCase__:    Optional[int]=0      ,							UpperCamelCase__:    Any="gelu"      ,							**UpperCamelCase__:    Union[str, Any]      ,							):
														super().__init__(**_A					)

														lowerCamelCase__ :     Optional[int]	  =	hidden_size
														lowerCamelCase__ :     Tuple	  =	num_hidden_layers
														lowerCamelCase__ :     Tuple	  =	num_attention_heads
														lowerCamelCase__ :     Optional[int]	  =	intermediate_size
														lowerCamelCase__ :     Dict	  =	hidden_act
														lowerCamelCase__ :     int	  =	hidden_dropout_prob
														lowerCamelCase__ :     Dict	  =	attention_probs_dropout_prob
														lowerCamelCase__ :     Optional[int]	  =	max_position_embeddings
														lowerCamelCase__ :     List[Any]	  =	type_vocab_size
														lowerCamelCase__ :     int	  =	initializer_range
														lowerCamelCase__ :     List[Any]	  =	relative_attention
														lowerCamelCase__ :     Any	  =	max_relative_positions
														lowerCamelCase__ :     Optional[Any]	  =	pad_token_id
														lowerCamelCase__ :     Dict	  =	position_biased_input

														# Backwards compatibility
														if type(_A					) == str:
																					lowerCamelCase__ :     List[str]	  =	[x.strip() for x in pos_att_type.lower().split("""|"""					)]

														lowerCamelCase__ :     int	  =	pos_att_type
														lowerCamelCase__ :     Any	  =	vocab_size
														lowerCamelCase__ :     Optional[Any]	  =	layer_norm_eps

														lowerCamelCase__ :     List[str]	  =	kwargs.get("""pooler_hidden_size"""      ,							_A					)
														lowerCamelCase__ :     Optional[int]	  =	pooler_dropout
														lowerCamelCase__ :     List[str]	  =	pooler_hidden_act



class _lowercase     (    snake_case_		):




							@property
							def 		lowerCamelCase_    (							self:    int					):


														if self.task == "multiple-choice":
																					lowerCamelCase__ :     List[Any]	  =	{0: 'batch', 1: 'choice', 2: 'sequence'}
														else:
																					lowerCamelCase__ :     Any	  =	{0: 'batch', 1: 'sequence'}
														if self._config.type_vocab_size > 0:
																					return OrderedDict(
																					    [("""input_ids""", dynamic_axis), ("""attention_mask""", dynamic_axis), ("""token_type_ids""", dynamic_axis)]					)
														else:
																					return OrderedDict([("""input_ids""", dynamic_axis), ("""attention_mask""", dynamic_axis)]					)




							@property
							def 		lowerCamelCase_    (							self:    Any					):
														return 12




							def 		lowerCamelCase_    (							self:    Union[str, Any]      ,							UpperCamelCase__:    Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]      ,							UpperCamelCase__:    int = -1      ,							UpperCamelCase__:    int = -1      ,							UpperCamelCase__:    int = -1      ,							UpperCamelCase__:    bool = False      ,							UpperCamelCase__:    Optional["TensorType"] = None      ,							UpperCamelCase__:    int = 3      ,							UpperCamelCase__:    int = 40      ,							UpperCamelCase__:    int = 40      ,							UpperCamelCase__:    "PreTrainedTokenizerBase" = None      ,							):
														lowerCamelCase__ :     List[str]	  =	super().generate_dummy_inputs(preprocessor=_A      ,							framework=_A					)
														if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
																					del dummy_inputs["token_type_ids"]
														return dummy_inputs









'''simple docstring'''







def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase				)				->	list:

							# bit count represents no. of bits in the gray code
							if bit_count < 0:
														raise ValueError("""The given input must be positive"""				)

							# get the generated string sequence
							lowerCamelCase__ :     List[str]	  =	gray_code_sequence_string(UpperCamelCase				)
							#
							# convert them to integers
							for i in range(len(UpperCamelCase				)				):
														lowerCamelCase__ :     int	  =	int(sequence[i]    ,      2				)

							return sequence





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase				)				->	list:

							# The approach is a recursive one
							# Base case achieved when either n = 0 or n=1
							if bit_count == 0:
														return ["0"]

							if bit_count == 1:
														return ["0", "1"]

							lowerCamelCase__ :     Optional[Any]	  =	1 << bit_count  # defines the length of the sequence
							# 1<< n is equivalent to 2^n

							# recursive answer will generate answer for n-1 bits
							lowerCamelCase__ :     Any	  =	gray_code_sequence_string(bit_count - 1				)

							lowerCamelCase__ :     Union[str, Any]	  =	[]

							# append 0 to first half of the smaller sequence generated
							for i in range(seq_len // 2				):
														lowerCamelCase__ :     Optional[int]	  =	"""0""" + smaller_sequence[i]
														sequence.append(UpperCamelCase				)

							# append 1 to second half ... start from the end of the list
							for i in reversed(range(seq_len // 2				)				):
														lowerCamelCase__ :     int	  =	"""1""" + smaller_sequence[i]
														sequence.append(UpperCamelCase				)

							return sequence


if __name__ == "__main__":
			import doctest

			doctest.testmod()

