

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     :       List[Any]        =       {
    "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 		SCREAMING_SNAKE_CASE__					(		lowerCamelCase__   ):







						"""simple docstring"""




						lowercase  :				Optional[int]											=							'deberta'

						def __init__(				self , __UpperCamelCase=5_02_65 , __UpperCamelCase=7_68 , __UpperCamelCase=12 , __UpperCamelCase=12 , __UpperCamelCase=30_72 , __UpperCamelCase="gelu" , __UpperCamelCase=0.1 , __UpperCamelCase=0.1 , __UpperCamelCase=5_12 , __UpperCamelCase=0 , __UpperCamelCase=0.02 , __UpperCamelCase=1E-7 , __UpperCamelCase=False , __UpperCamelCase=-1 , __UpperCamelCase=0 , __UpperCamelCase=True , __UpperCamelCase=None , __UpperCamelCase=0 , __UpperCamelCase="gelu" , **__UpperCamelCase , )							->	List[Any]:




									'''simple docstring'''


									super().__init__(**__UpperCamelCase    )

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

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

									__UpperCamelCase    :    int								=      pos_att_type
									__UpperCamelCase    :    Optional[Any]								=      vocab_size
									__UpperCamelCase    :    Union[str, Any]								=      layer_norm_eps

									__UpperCamelCase    :    Optional[int]								=      kwargs.get("pooler_hidden_size" , __UpperCamelCase    )
									__UpperCamelCase    :    Optional[int]								=      pooler_dropout
									__UpperCamelCase    :    Optional[Any]								=      pooler_hidden_act







class 		SCREAMING_SNAKE_CASE__					(		lowerCamelCase__   ):







						"""simple docstring"""




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




									'''simple docstring'''


									if self.task == "multiple-choice":
												__UpperCamelCase    :    Any								=      {0: "batch", 1: "choice", 2: "sequence"}
									else:
												__UpperCamelCase    :    Optional[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    )							->	int:




									'''simple docstring'''


									return 12




						def __lowerCamelCase					(				self , __UpperCamelCase , __UpperCamelCase = -1 , __UpperCamelCase = -1 , __UpperCamelCase = -1 , __UpperCamelCase = False , __UpperCamelCase = None , __UpperCamelCase = 3 , __UpperCamelCase = 40 , __UpperCamelCase = 40 , __UpperCamelCase = None , )							->	Mapping[str, Any]:




									'''simple docstring'''


									__UpperCamelCase    :    Union[str, Any]								=      super().generate_dummy_inputs(preprocessor=__UpperCamelCase , framework=__UpperCamelCase    )
									if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
												del dummy_inputs["token_type_ids"]
									return dummy_inputs


from .balanced_parentheses import balanced_parentheses
from .stack import Stack







def  UpperCAmelCase_   (_lowerCAmelCase :		str		):
			return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(_lowerCAmelCase     ,			-1		)







def  UpperCAmelCase_   (_lowerCAmelCase :		str		):
			if not balanced_parentheses(_lowerCAmelCase		):
						raise ValueError("Mismatched parentheses"		)
			__UpperCamelCase    :    Stack[str]								=      Stack()
			__UpperCamelCase    :    int								=      []
			for char in expression_str:
						if char.isalpha() or char.isdigit():
									postfix.append(_lowerCAmelCase		)
						elif char == "(":
									stack.push(_lowerCAmelCase		)
						elif char == ")":
									while not stack.is_empty() and stack.peek() != "(":
												postfix.append(stack.pop()		)
									stack.pop()
						else:
									while not stack.is_empty() and precedence(_lowerCAmelCase		) <= precedence(stack.peek()		):
												postfix.append(stack.pop()		)
									stack.push(_lowerCAmelCase		)
			while not stack.is_empty():
						postfix.append(stack.pop()		)
			return " ".join(_lowerCAmelCase		)


if __name__ == "__main__":
					from doctest import testmod

					testmod()
					lowercase     :       int        =       "a+b*(c^d-e)^(f+g*h)-i"

					print("Infix to Postfix Notation demonstration:\n")
					print("Infix notation: " + expression)
					print("Postfix notation: " + infix_to_postfix(expression))