





"""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


lowerCamelCase_	:		int         =   logging.get_logger(__name__)

lowerCamelCase_	:		int         =   {
    '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 					_UpperCAmelCase    (  UpperCAmelCase__						):



      '''simple docstring'''
      lowercase_ :					Optional[int]             =  """deberta"""

      def __init__(	self   , snake_case_=5_0_2_6_5   , snake_case_=7_6_8   , snake_case_=1_2   , snake_case_=1_2   , snake_case_=3_0_7_2   , snake_case_="gelu"   , snake_case_=0.1   , snake_case_=0.1   , snake_case_=5_1_2   , snake_case_=0   , snake_case_=0.02   , snake_case_=1E-7   , snake_case_=False   , snake_case_=-1   , snake_case_=0   , snake_case_=True   , snake_case_=None   , snake_case_=0   , snake_case_="gelu"   , **snake_case_   , ):

        """simple docstring"""

        super().__init__(**snake_case_    )

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

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

        A_    :			Any									=    pos_att_type
        A_    :			Optional[int]									=    vocab_size
        A_    :			Any									=    layer_norm_eps

        A_    :			str									=    kwargs.get('pooler_hidden_size'   , snake_case_    )
        A_    :			str									=    pooler_dropout
        A_    :			Dict									=    pooler_hidden_act


class 					_UpperCAmelCase    (  UpperCAmelCase__						):



      '''simple docstring'''

      @property
      def    lowerCamelCase_     (	self    ):

        """simple docstring"""

        if self.task == "multiple-choice":
          A_    :			Any									=    {0: 'batch', 1: 'choice', 2: 'sequence'}
        else:
          A_    :			Dict									=    {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    ):

        """simple docstring"""

        return 1_2

      def    lowerCamelCase_     (	self   , snake_case_   , snake_case_ = -1   , snake_case_ = -1   , snake_case_ = -1   , snake_case_ = False   , snake_case_ = None   , snake_case_ = 3   , snake_case_ = 4_0   , snake_case_ = 4_0   , snake_case_ = None   , ):

        """simple docstring"""

        A_    :			Tuple									=    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



def 	A (		A__			):
     UpperCAmelCase    :					Dict			=      9

     while num > 0:
          if num % 1_0 != digit:
               return False
          num //= 1_0_0
          digit -= 1

     return True







def 	A (		):
     UpperCAmelCase    :					Optional[Any]			=      1_3_8_9_0_2_6_6_3

     while not is_square_form(num * num			):
          if num % 1_0 == 3:
               num -= 6  # (3 - 6) % 10 = 7
          else:
               num -= 4  # (7 - 4) % 10 = 3

     return num * 1_0


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



