





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

A__    :       str              ={
    '''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_       ):
      _lowercase:      Any											=       '''deberta-v2'''




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

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

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

            _lowerCAmelCase												=							pos_att_type
            _lowerCAmelCase												=							vocab_size
            _lowerCAmelCase												=							layer_norm_eps

            _lowerCAmelCase												=							kwargs.get("""pooler_hidden_size"""      ,      __snake_case  )
            _lowerCAmelCase												=							pooler_dropout
            _lowerCAmelCase												=							pooler_hidden_act




class 			UpperCAmelCase					(      snake_case_       ):




      @property
      def     lowercase__   (      self      :			Optional[int]  )    ->				Mapping[str, Mapping[int, str]]:
            if self.task == "multiple-choice":
                  _lowerCAmelCase												=							{0: """batch""", 1: """choice""", 2: """sequence"""}
            else:
                  _lowerCAmelCase												=							{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     lowercase__   (      self      :			Optional[int]  )    ->				int:
            return 12




      def     lowercase__   (      self      :			Optional[int]      ,      __snake_case      :			Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]      ,      __snake_case      :			int = -1      ,      __snake_case      :			int = -1      ,      __snake_case      :			int = -1      ,      __snake_case      :			bool = False      ,      __snake_case      :			Optional["TensorType"] = None      ,      __snake_case      :			int = 3      ,      __snake_case      :			int = 40      ,      __snake_case      :			int = 40      ,      __snake_case      :			"PreTrainedTokenizerBase" = None      ,      )    ->				Mapping[str, Any]:
            _lowerCAmelCase												=							super().generate_dummy_inputs(preprocessor=__snake_case      ,      framework=__snake_case  )
            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        UpperCamelCase__				(		lowerCAmelCase = 4_00_00_00  ):





      """simple docstring"""


      _lowerCAmelCase												=							[]
      _lowerCAmelCase					,							_lowerCAmelCase												=							0, 1
      while b <= n:
            if b % 2 == 0:
                  even_fibs.append(lowerCAmelCase  )
            _lowerCAmelCase					,							_lowerCAmelCase												=							b, a + b
      return sum(lowerCAmelCase  )


if __name__ == "__main__":
      print(F"""{solution() = }""")






