





def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		return " ".join(input_str.split()[::-1]						)


if __name__ == "__main__":
		import doctest

		doctest.testmod()







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


_lowercase		:  Tuple			       =logging.get_logger(__name__)

_lowercase		:  Any			       ={
    """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 						UpperCamelCase_  (  snake_case__							):
					_a      :						int						    =					'deberta-v2'



					def __init__(		self     :     Any       ,      lowerCamelCase     :     Dict=12_81_00       ,      lowerCamelCase     :     List[Any]=15_36       ,      lowerCamelCase     :     Union[str, Any]=24       ,      lowerCamelCase     :     Union[str, Any]=24       ,      lowerCamelCase     :     Optional[int]=61_44       ,      lowerCamelCase     :     Any="gelu"       ,      lowerCamelCase     :     int=0.1       ,      lowerCamelCase     :     str=0.1       ,      lowerCamelCase     :     Optional[int]=5_12       ,      lowerCamelCase     :     str=0       ,      lowerCamelCase     :     Union[str, Any]=0.02       ,      lowerCamelCase     :     List[str]=1E-7       ,      lowerCamelCase     :     Dict=False       ,      lowerCamelCase     :     List[Any]=-1       ,      lowerCamelCase     :     Union[str, Any]=0       ,      lowerCamelCase     :     Optional[int]=True       ,      lowerCamelCase     :     Optional[int]=None       ,      lowerCamelCase     :     Tuple=0       ,      lowerCamelCase     :     Tuple="gelu"       ,      **lowerCamelCase     :     Optional[int]       ,      ):
							super().__init__(**lowerCamelCase						)

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

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

							lowerCamelCase_	:     Optional[Any] 						=      pos_att_type
							lowerCamelCase_	:     List[Any] 						=      vocab_size
							lowerCamelCase_	:     Any 						=      layer_norm_eps

							lowerCamelCase_	:     int 						=      kwargs.get('pooler_hidden_size'       ,      lowerCamelCase						)
							lowerCamelCase_	:     Dict 						=      pooler_dropout
							lowerCamelCase_	:     Tuple 						=      pooler_hidden_act






class 						UpperCamelCase_  (  snake_case__							):



					@property
					def   __a     (		self     :     Optional[int]						):
							if self.task == "multiple-choice":
									lowerCamelCase_	:     Optional[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   __a     (		self     :     List[Any]						):
							return 12





					def   __a     (		self     :     Tuple       ,      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       ,      ):
							lowerCamelCase_	:     Union[str, Any] 						=      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
