


'''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


__SCREAMING_SNAKE_CASE				:							Optional[int]		       =		logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE				:							List[str]		       =		{
    '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/config.json''',
    '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/config.json''',
    '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json''',
    '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json''',
    '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json''',
    '''microsoft/deberta-xlarge-mnli''': '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json''',
}






class 				__lowerCAmelCase      (      lowercase	):

						"""simple docstring"""






						_UpperCAmelCase		:					Any      	="deberta"






						def __init__(     self       :			Optional[int]   ,     lowerCAmelCase       :			Union[str, Any]=5_02_65   ,     lowerCAmelCase       :			Optional[Any]=7_68   ,     lowerCAmelCase       :			List[str]=12   ,     lowerCAmelCase       :			Union[str, Any]=12   ,     lowerCAmelCase       :			List[str]=30_72   ,     lowerCAmelCase       :			Optional[int]="gelu"   ,     lowerCAmelCase       :			str=0.1   ,     lowerCAmelCase       :			Union[str, Any]=0.1   ,     lowerCAmelCase       :			Dict=5_12   ,     lowerCAmelCase       :			str=0   ,     lowerCAmelCase       :			Optional[int]=0.0_2   ,     lowerCAmelCase       :			Optional[int]=1e-7   ,     lowerCAmelCase       :			Any=False   ,     lowerCAmelCase       :			Any=-1   ,     lowerCAmelCase       :			Union[str, Any]=0   ,     lowerCAmelCase       :			Tuple=True   ,     lowerCAmelCase       :			Any=None   ,     lowerCAmelCase       :			int=0   ,     lowerCAmelCase       :			List[str]="gelu"   ,     **lowerCAmelCase       :			Union[str, Any]   ,     ):
													super().__init__(**lowerCAmelCase  )

													A_ 						=		hidden_size
													A_ 						=		num_hidden_layers
													A_ 						=		num_attention_heads
													A_ 						=		intermediate_size
													A_ 						=		hidden_act
													A_ 						=		hidden_dropout_prob
													A_ 						=		attention_probs_dropout_prob
													A_ 						=		max_position_embeddings
													A_ 						=		type_vocab_size
													A_ 						=		initializer_range
													A_ 						=		relative_attention
													A_ 						=		max_relative_positions
													A_ 						=		pad_token_id
													A_ 						=		position_biased_input

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

													A_ 						=		pos_att_type
													A_ 						=		vocab_size
													A_ 						=		layer_norm_eps

													A_ 						=		kwargs.get("pooler_hidden_size"   ,     lowerCAmelCase  )
													A_ 						=		pooler_dropout
													A_ 						=		pooler_hidden_act






class 				__lowerCAmelCase      (      lowercase	):

						"""simple docstring"""






						@property
						def 							_UpperCAmelCase					(     self       :			List[Any]  ):
													if self.task == "multiple-choice":
																				A_ 						=		{0: "batch", 1: "choice", 2: "sequence"}
													else:
																				A_ 						=		{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 							_UpperCAmelCase					(     self       :			List[Any]  ):
													return 12






						def 							_UpperCAmelCase					(     self       :			Dict   ,     lowerCAmelCase       :			Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]   ,     lowerCAmelCase       :			int = -1   ,     lowerCAmelCase       :			int = -1   ,     lowerCAmelCase       :			int = -1   ,     lowerCAmelCase       :			bool = False   ,     lowerCAmelCase       :			Optional["TensorType"] = None   ,     lowerCAmelCase       :			int = 3   ,     lowerCAmelCase       :			int = 40   ,     lowerCAmelCase       :			int = 40   ,     lowerCAmelCase       :			"PreTrainedTokenizerBase" = None   ,     ):
													A_ 						=		super().generate_dummy_inputs(preprocessor=lowerCAmelCase   ,     framework=lowerCAmelCase  )
													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 			a_							(  UpperCamelCase_   ):
							if not isinstance(UpperCamelCase_	,     UpperCamelCase_   ):
														A_ 						=		f"Input value of [number={number}] must be an integer"
														raise TypeError(UpperCamelCase_   )
							if number < 0 or number % 2 == 1:
														return False
							A_ 						=		int(number**0.5   )
							return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
							import doctest

							doctest.testmod()





