





"""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   snake_case		(				UpperCAmelCase						:							Optional[int],    UpperCAmelCase						:							str ):
				# "Simpson Rule"
				# int(f) = delta_x/2 * (b-a)/3*(f1 + 4f2 + 2f_3 + ... + fn)
				A									=   (boundary[1] - boundary[0]) / steps
				A									=   boundary[0]
				A									=   boundary[1]
				A									=   make_points(UpperCAmelCase,    UpperCAmelCase,    UpperCAmelCase )
				A									=   0.0
				y += (h / 3.0) * f(UpperCAmelCase )
				A									=   2
				for i in x_i:
								y += (h / 3) * (4 - 2 * (cnt % 2)) * f(UpperCAmelCase )
								cnt += 1
				y += (h / 3.0) * f(UpperCAmelCase )
				return y







def   snake_case		(				UpperCAmelCase						:							int,    UpperCAmelCase						:							int,    UpperCAmelCase						:							List[Any] ):
				A									=   a + h
				while x < (b - h):
								yield x
								A									=   x + h







def   snake_case		(				UpperCAmelCase						:							str ):  # enter your function here
				A									=   (x - 0) * (x - 0)
				return y







def   snake_case		(				):
				A									=   0.0  # Lower bound of integration
				A									=   1.0  # Upper bound of integration
				A									=   10.0  # define number of steps or resolution
				A									=   [a, b]  # define boundary of integration
				A									=   method_a(UpperCAmelCase,    UpperCAmelCase )
				print(f'y = {y}' )


if __name__ == "__main__":
					main()





