



'''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


lowercase_		       =  logging.get_logger(__name__)

lowercase_		       =  {
    '''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			(  _lowercase						):



 '''simple docstring'''







 __lowerCamelCase    :       Tuple          =       '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 ,   )    ->     str:


      """simple docstring"""



      super().__init__(**UpperCamelCase__       )

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

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

      _a      =  pos_att_type
      _a      =  vocab_size
      _a      =  layer_norm_eps

      _a      =  kwargs.get('''pooler_hidden_size''' ,   UpperCamelCase__       )
      _a      =  pooler_dropout
      _a      =  pooler_hidden_act






class __A			(  _lowercase						):



 '''simple docstring'''







 @property
 def 					a__  (self       )    ->     List[Any]:


      """simple docstring"""



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


      """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 ,   )    ->     List[str]:


      """simple docstring"""



      _a      =  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'''







def  SCREAMING_SNAKE_CASE_       (UpperCamelCase = 1000      )      ->       int:
							lowerCamelCase__					:	str         =       -1
							lowerCamelCase__					:	Dict         =       0
							for a in range(1				,			n // 3      ):
														# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
														lowerCamelCase__					:	Dict         =       (n * n - 2 * a * n) // (2 * n - 2 * a)
														lowerCamelCase__					:	Any         =       n - a - b
														if c * c == (a * a + b * b):
																					lowerCamelCase__					:	Dict         =       a * b * c
																					if candidate >= product:
																												lowerCamelCase__					:	Union[str, Any]         =       candidate
							return product


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

