



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


UpperCAmelCase__   =       logging.get_logger(__name__)

UpperCAmelCase__   =       {
    "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 			__lowerCAmelCase    (			__lowerCamelCase						):
			UpperCamelCase   					=     "deberta-v2"



			def __init__(						self   :  Tuple ,		A   :  str=12_81_00 ,		A   :  List[str]=15_36 ,		A   :  List[str]=24 ,		A   :  Dict=24 ,		A   :  Union[str, Any]=61_44 ,		A   :  int="gelu" ,		A   :  Any=0.1 ,		A   :  Union[str, Any]=0.1 ,		A   :  Optional[int]=5_12 ,		A   :  Optional[int]=0 ,		A   :  Dict=0.0_2 ,		A   :  int=1E-7 ,		A   :  Tuple=False ,		A   :  List[str]=-1 ,		A   :  str=0 ,		A   :  Dict=True ,		A   :  Optional[Any]=None ,		A   :  int=0 ,		A   :  Optional[Any]="gelu" ,		**A   :  List[str] ,		)   ->    Union[str, Any]:



						"""simple docstring"""






						super().__init__(**A)

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

						# Backwards compatibility
						if type(A) == str:
									_UpperCAmelCase		       =   [x.strip() for x in pos_att_type.lower().split('|')]

						_UpperCAmelCase		       =   pos_att_type
						_UpperCAmelCase		       =   vocab_size
						_UpperCAmelCase		       =   layer_norm_eps

						_UpperCAmelCase		       =   kwargs.get('pooler_hidden_size' ,		A)
						_UpperCAmelCase		       =   pooler_dropout
						_UpperCAmelCase		       =   pooler_hidden_act







class 			__lowerCAmelCase    (			__lowerCamelCase						):



			@property
			def     _lowerCamelCase       (						self   :  Dict)   ->    Mapping[str, Mapping[int, str]]:



						"""simple docstring"""






						if self.task == "multiple-choice":
									_UpperCAmelCase		       =   {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
						else:
									_UpperCAmelCase		       =   {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   :  int)   ->    int:



						"""simple docstring"""






						return 12



			def     _lowerCamelCase       (						self   :  Dict ,		A   :  Dict ,		A   :  Any = -1 ,		A   :  Optional[int] = -1 ,		A   :  str = -1 ,		A   :  str = False ,		A   :  Optional[Any] = None ,		A   :  str = 3 ,		A   :  Any = 40 ,		A   :  Any = 40 ,		A   :  Optional[Any] = None ,		)   ->    Mapping[str, Any]:



						"""simple docstring"""






						_UpperCAmelCase		       =   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







UpperCAmelCase_     							= 'Input must be a string of 8 numbers plus letter'
UpperCAmelCase_     							= 'TRWAGMYFPDXBNJZSQVHLCKE'




def 		lowerCAmelCase_    (  __UpperCAmelCase:			str      )      ->	bool:

    if not isinstance(__UpperCAmelCase		,   __UpperCAmelCase      ):
        UpperCamelCase__							:				Any          =      f"Expected string as input, found {type(__UpperCAmelCase      ).__name__}"
        raise TypeError(__UpperCAmelCase      )

    UpperCamelCase__							:				int          =      spanish_id.replace('''-'''		,   ''''''      ).upper()
    if len(__UpperCAmelCase      ) != 9:
        raise ValueError(__UpperCAmelCase      )

    try:
        UpperCamelCase__							:				List[str]          =      int(spanish_id_clean[0:8]      )
        UpperCamelCase__							:				Optional[int]          =      spanish_id_clean[8]
    except ValueError as ex:
        raise ValueError(__UpperCAmelCase      ) from ex

    if letter.isdigit():
        raise ValueError(__UpperCAmelCase      )

    return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
  import doctest

  doctest.testmod()

