





'''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__    :      int						=    logging.get_logger(__name__)

lowercase__    :      List[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  SCREAMING_SNAKE_CASE    (a__							):
     lowerCAmelCase					=       '''deberta-v2'''


     def __init__(						self						,	_UpperCAmelCase=12_8100						,	_UpperCAmelCase=1536						,	_UpperCAmelCase=24						,	_UpperCAmelCase=24						,	_UpperCAmelCase=6144						,	_UpperCAmelCase="gelu"						,	_UpperCAmelCase=0.1						,	_UpperCAmelCase=0.1						,	_UpperCAmelCase=512						,	_UpperCAmelCase=0						,	_UpperCAmelCase=0.02						,	_UpperCAmelCase=1e-7						,	_UpperCAmelCase=False						,	_UpperCAmelCase=-1						,	_UpperCAmelCase=0						,	_UpperCAmelCase=True						,	_UpperCAmelCase=None						,	_UpperCAmelCase=0						,	_UpperCAmelCase="gelu"						,	**_UpperCAmelCase						,	):

          '''simple docstring'''






          super().__init__(**_UpperCAmelCase)

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

          # Backwards compatibility
          if type(_UpperCAmelCase) == str:
               __A						: Union[str, Any]      =       [x.strip() for x in pos_att_type.lower().split('|')]

          __A						: str      =       pos_att_type
          __A						: Optional[int]      =       vocab_size
          __A						: List[str]      =       layer_norm_eps

          __A						: List[str]      =       kwargs.get('pooler_hidden_size'						,	_UpperCAmelCase)
          __A						: Optional[Any]      =       pooler_dropout
          __A						: Any      =       pooler_hidden_act




class  SCREAMING_SNAKE_CASE    (a__							):


     @property
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          if self.task == "multiple-choice":
               __A						: Optional[int]      =       {0: 'batch', 1: 'choice', 2: 'sequence'}
          else:
               __A						: str      =       {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 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          return 12


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase = -1						,	_UpperCAmelCase = -1						,	_UpperCAmelCase = -1						,	_UpperCAmelCase = False						,	_UpperCAmelCase = None						,	_UpperCAmelCase = 3						,	_UpperCAmelCase = 40						,	_UpperCAmelCase = 40						,	_UpperCAmelCase = None						,	):

          '''simple docstring'''






          __A						: Dict      =       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'''




from __future__ import annotations

from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray






def        _lowerCAmelCase			(  __snake_case  : float ,							__snake_case  : float ,							__snake_case  : bool = False			)     ->     list[float]:
     if radian_mode:
          return [magnitude * cos(__snake_case			), magnitude * sin(__snake_case			)]
     return [magnitude * cos(radians(__snake_case			)			), magnitude * sin(radians(__snake_case			)			)]






def        _lowerCAmelCase			(  __snake_case  : NDArray[floataa] ,							__snake_case  : NDArray[floataa] ,							__snake_case  : float = 10**-1			)     ->     bool:
     __A						: NDArray[floataa]      =       cross(__snake_case ,							__snake_case			)
     __A						: float      =       sum(__snake_case			)
     return abs(__snake_case			) < eps


if __name__ == "__main__":
  # Test to check if it works
  lowercase__    :      List[Any]						=    array(
      [
          polar_force(718.4, 1_80 - 30),
          polar_force(879.54, 45),
          polar_force(1_00, -90),
      ]
  )

  lowercase__    :      NDArray[floataa]						=    array([[0, 0], [0, 0], [0, 0]])

  assert in_static_equilibrium(forces, location)

  # Problem 1 in image_data/2D_problems.jpg
  lowercase__    :      Dict						=    array(
      [
          polar_force(30 * 9.81, 15),
          polar_force(2_15, 1_80 - 45),
          polar_force(2_64, 90 - 30),
      ]
  )

  lowercase__    :      Any						=    array([[0, 0], [0, 0], [0, 0]])

  assert in_static_equilibrium(forces, location)

  # Problem in image_data/2D_problems_1.jpg
  lowercase__    :      Optional[int]						=    array([[0, -20_00], [0, -12_00], [0, 1_56_00], [0, -1_24_00]])

  lowercase__    :      Optional[int]						=    array([[0, 0], [6, 0], [10, 0], [12, 0]])

  assert in_static_equilibrium(forces, location)

  import doctest

  doctest.testmod()