


"""simple docstring"""
def 						lowercase				(	_snake_case		: Union[str, Any]	,  _snake_case		: List[Any]	)	->Optional[Any]:
	"""simple docstring"""





	__snake_case      :		Tuple         =							(boundary[1] - boundary[0]) / steps
	__snake_case      :		List[Any]         =							boundary[0]
	__snake_case      :		Dict         =							boundary[1]
	__snake_case      :		Dict         =							make_points(_snake_case	,  _snake_case	,  _snake_case	)
	__snake_case      :		Any         =							0.0
	y += (h / 3.0) * f(_snake_case	)
	__snake_case      :		List[Any]         =							2
	for i in x_i:
		y += (h / 3) * (4 - 2 * (cnt % 2)) * f(_snake_case	)
		cnt += 1
	y += (h / 3.0) * f(_snake_case	)
	return y






def 						lowercase				(	_snake_case		: Tuple	,  _snake_case		: Tuple	,  _snake_case		: int	)	->Optional[Any]:
	"""simple docstring"""





	__snake_case      :		str         =							a + h
	while x < (b - h):
		yield x
		__snake_case      :		Any         =							x + h






def 						lowercase				(	_snake_case		: List[Any]	)	->Any:  # enter your function here
	"""simple docstring"""





	__snake_case      :		int         =							(x - 0) * (x - 0)
	return y






def 						lowercase				(	)	->Optional[int]:
	"""simple docstring"""





	__snake_case      :		Tuple         =							0.0  # Lower bound of integration
	__snake_case      :		str         =							1.0  # Upper bound of integration
	__snake_case      :		Dict         =							10.0  # define number of steps or resolution
	__snake_case      :		str         =							[a, b]  # define boundary of integration
	__snake_case      :		int         =							method_a(_snake_case	,  _snake_case	)
	print(f"""y = {y}"""	)


if __name__ == "__main__":
			main()









"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowercase          = logging.get_logger(__name__)

__lowercase          = {
    """squeezebert/squeezebert-uncased""": (
        """https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"""
    ),
    """squeezebert/squeezebert-mnli""": """https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json""",
    """squeezebert/squeezebert-mnli-headless""": (
        """https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"""
    ),
}






class 		_A    (    _a    ):







    """simple docstring"""




    UpperCAmelCase			:				Tuple      =			SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
    UpperCAmelCase			:				Any      =			"""squeezebert"""






    def __init__(   self							:       List[str]							,					__UpperCAmelCase							:       Tuple=30522							,					__UpperCAmelCase							:       Tuple=768							,					__UpperCAmelCase							:       int=12							,					__UpperCAmelCase							:       str=12							,					__UpperCAmelCase							:       List[Any]=3072							,					__UpperCAmelCase							:       Dict="gelu"							,					__UpperCAmelCase							:       List[Any]=0.1							,					__UpperCAmelCase							:       Optional[int]=0.1							,					__UpperCAmelCase							:       Optional[Any]=512							,					__UpperCAmelCase							:       int=2							,					__UpperCAmelCase							:       Dict=0.02							,					__UpperCAmelCase							:       Optional[int]=1e-12							,					__UpperCAmelCase							:       Optional[Any]=0							,					__UpperCAmelCase							:       Optional[Any]=768							,					__UpperCAmelCase							:       Tuple=4							,					__UpperCAmelCase							:       Dict=4							,					__UpperCAmelCase							:       str=4							,					__UpperCAmelCase							:       List[Any]=1							,					__UpperCAmelCase							:       Optional[int]=4							,					__UpperCAmelCase							:       Optional[int]=4							,					**__UpperCAmelCase							:       Tuple							,					):
      super().__init__(pad_token_id=__UpperCAmelCase							,					**__UpperCAmelCase)

      a		:						List[Any] 				=     vocab_size
      a		:						List[Any] 				=     hidden_size
      a		:						Dict 				=     num_hidden_layers
      a		:						int 				=     num_attention_heads
      a		:						Dict 				=     hidden_act
      a		:						Tuple 				=     intermediate_size
      a		:						int 				=     hidden_dropout_prob
      a		:						List[Any] 				=     attention_probs_dropout_prob
      a		:						Union[str, Any] 				=     max_position_embeddings
      a		:						Union[str, Any] 				=     type_vocab_size
      a		:						Optional[Any] 				=     initializer_range
      a		:						Any 				=     layer_norm_eps
      a		:						Any 				=     embedding_size
      a		:						Tuple 				=     q_groups
      a		:						List[str] 				=     k_groups
      a		:						str 				=     v_groups
      a		:						Optional[Any] 				=     post_attention_groups
      a		:						List[str] 				=     intermediate_groups
      a		:						Optional[int] 				=     output_groups






class 		_A    (    _a    ):







    """simple docstring"""




    @property
    def       __snake_case				(   self							:       Optional[Any]):
      if self.task == "multiple-choice":
        a		:						Optional[int] 				=     {0: "batch", 1: "choice", 2: "sequence"}
      else:
        a		:						Tuple 				=     {0: "batch", 1: "sequence"}
      return OrderedDict(
          [
              ("input_ids", dynamic_axis),
              ("attention_mask", dynamic_axis),
              ("token_type_ids", dynamic_axis),
          ])






