





'''simple docstring'''







def  _lowerCamelCase				( lowercase						:      list    ,							lowercase						:      list    ,							lowercase						:      int						)	->	list:
				_a								= len(lowercase						)
				_a								= [[0] * n for i in range(lowercase						)]
				for i in range(lowercase						):
								_a								= y_points[i]

				for i in range(2    ,							lowercase						):
								for j in range(lowercase    ,							lowercase						):
												_a								= (
												    (xa - x_points[j - i + 1]) * q[j][i - 1]
												    - (xa - x_points[j]) * q[j - 1][i - 1]
												) / (x_points[j] - x_points[j - i + 1])

				return [q[n - 1][n - 1], q]


if __name__ == "__main__":
					import doctest

					doctest.testmod()







'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase_					:    int      	=			logging.get_logger(__name__)

lowerCAmelCase_					:    Tuple      	=			{
    'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json',
    'google/bigbird-roberta-large': 'https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json',
    'google/bigbird-base-trivia-itc': 'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}
class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				__a            ='big_bird'




				def __init__(  self     :					Optional[int]					,				__a     :					Dict=5_03_58					,				__a     :					str=7_68					,				__a     :					List[Any]=12					,				__a     :					List[str]=12					,				__a     :					Union[str, Any]=30_72					,				__a     :					str="gelu_new"					,				__a     :					Dict=0.1					,				__a     :					Union[str, Any]=0.1					,				__a     :					Any=40_96					,				__a     :					int=2					,				__a     :					Tuple=0.02					,				__a     :					List[Any]=1e-1_2					,				__a     :					int=True					,				__a     :					List[str]=0					,				__a     :					Tuple=1					,				__a     :					Optional[Any]=2					,				__a     :					Tuple=66					,				__a     :					str="block_sparse"					,				__a     :					Tuple=True					,				__a     :					Optional[int]=False					,				__a     :					str=64					,				__a     :					Tuple=3					,				__a     :					Any=None					,				**__a     :					Dict					,				):
								super().__init__(
								    pad_token_id=__a					,				bos_token_id=__a					,				eos_token_id=__a					,				sep_token_id=__a					,				**__a					,				)

								_a								= vocab_size
								_a								= max_position_embeddings
								_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								= initializer_range
								_a								= type_vocab_size
								_a								= layer_norm_eps
								_a								= use_cache

								_a								= rescale_embeddings
								_a								= attention_type
								_a								= use_bias
								_a								= block_size
								_a								= num_random_blocks
								_a								= classifier_dropout


class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







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