

"""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					:int    = logging.get_logger(__name__)

a					: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      __a							(__lowerCAmelCase):






     '''simple docstring'''
     _SCREAMING_SNAKE_CASE						:Optional[int]       = """deberta-v2"""

     def __init__(						self	,    _a=128_100	,    _a=1_536	,    _a=24	,    _a=24	,    _a=6_144	,    _a="gelu"	,    _a=0.1	,    _a=0.1	,    _a=512	,    _a=0	,    _a=0.02	,    _a=1E-7	,    _a=False	,    _a=-1	,    _a=0	,    _a=True	,    _a=None	,    _a=0	,    _a="gelu"	,    **_a	,    )  ->      Any:


           """simple docstring"""


           super().__init__(**_UpperCamelCase  )

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

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

           SCREAMING_SNAKE_CASE__   :      List[Any]      		=	pos_att_type
           SCREAMING_SNAKE_CASE__   :      Dict      		=	vocab_size
           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	layer_norm_eps

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





class      __a							(__lowerCAmelCase):






     '''simple docstring'''

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


           """simple docstring"""


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


           """simple docstring"""


           return 12





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


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      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





"""simple docstring"""


class      __a							:






     '''simple docstring'''

     def __init__(						self	,    _a	,    _a	,    _a  )  ->      str:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Any      		=	name
           SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	value
           SCREAMING_SNAKE_CASE__   :      List[Any]      		=	weight

     def __repr__(						self  )  ->      List[Any]:


           """simple docstring"""


           return f'''{self.__class__.__name__}({self.name}, {self.value}, {self.weight})'''

     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           return self.value

     def 					_a			(						self  )  ->      int:


           """simple docstring"""


           return self.name

     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


           return self.weight





     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           return self.value / self.weight





def  _lowercase					(    __lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase							)       ->				Dict:
      SCREAMING_SNAKE_CASE__   :      Any      		=	[]
      for i in range(len(__lowerCAmelCase							)							):
            menu.append(Things(name[i]  ,					value[i]  ,					weight[i]							)							)
      return menu




def  _lowercase					(    __lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase							)       ->				Union[str, Any]:
      SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	sorted(__lowerCAmelCase  ,					key=__lowerCAmelCase  ,					reverse=__lowerCAmelCase							)
      SCREAMING_SNAKE_CASE__   :      str      		=	[]
      SCREAMING_SNAKE_CASE__		,		SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	0.0, 0.0
      for i in range(len(__lowerCAmelCase							)							):
            if (total_cost + items_copy[i].get_weight()) <= max_cost:
                  result.append(items_copy[i]							)
                  total_cost += items_copy[i].get_weight()
                  total_value += items_copy[i].get_value()
      return (result, total_value)




def  _lowercase					(    )       ->				List[str]:
      pass


if __name__ == "__main__":
  import doctest

  doctest.testmod()




