




"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


a_            =   logging.get_logger(__name__)

a_            =   {
    '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/config.json''',
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}

class        UpperCAmelCase_  (	snake_case_						):
		UpperCamelCase									="""rembert"""
		def __init__(		self							,		UpperCamelCase_=25_03_00							,		UpperCamelCase_=11_52							,		UpperCamelCase_=32							,		UpperCamelCase_=18							,		UpperCamelCase_=2_56							,		UpperCamelCase_=16_64							,		UpperCamelCase_=46_08							,		UpperCamelCase_="gelu"							,		UpperCamelCase_=0.0							,		UpperCamelCase_=0.0							,		UpperCamelCase_=0.1							,		UpperCamelCase_=5_12							,		UpperCamelCase_=2							,		UpperCamelCase_=0.0_2							,		UpperCamelCase_=1E-12							,		UpperCamelCase_=True							,		UpperCamelCase_=0							,		UpperCamelCase_=3_12							,		UpperCamelCase_=3_13							,		**UpperCamelCase_							,		)		->   Dict:
					super().__init__(pad_token_id=UpperCamelCase_							,		bos_token_id=UpperCamelCase_							,		eos_token_id=UpperCamelCase_							,		**UpperCamelCase_   )

					__lowercase	:       Union[str, Any]				=   vocab_size
					__lowercase	:       List[str]				=   input_embedding_size
					__lowercase	:       Optional[Any]				=   output_embedding_size
					__lowercase	:       Optional[int]				=   max_position_embeddings
					__lowercase	:       Tuple				=   hidden_size
					__lowercase	:       Any				=   num_hidden_layers
					__lowercase	:       Any				=   num_attention_heads
					__lowercase	:       Union[str, Any]				=   intermediate_size
					__lowercase	:       Tuple				=   hidden_act
					__lowercase	:       Dict				=   hidden_dropout_prob
					__lowercase	:       Union[str, Any]				=   attention_probs_dropout_prob
					__lowercase	:       Any				=   classifier_dropout_prob
					__lowercase	:       Optional[Any]				=   initializer_range
					__lowercase	:       Dict				=   type_vocab_size
					__lowercase	:       str				=   layer_norm_eps
					__lowercase	:       str				=   use_cache
					__lowercase	:       Any				=   False


class        UpperCAmelCase_  (	snake_case_						):
		@property
		def 					_lowerCamelCase    (		self   )		->   Mapping[str, Mapping[int, str]]:


					if self.task == "multiple-choice":
								__lowercase	:       str				=   {0: "batch", 1: "choice", 2: "sequence"}
					else:
								__lowercase	:       int				=   {0: "batch", 1: "sequence"}
					return OrderedDict(
					    [
					        ('''input_ids''', dynamic_axis),
					        ('''attention_mask''', dynamic_axis),
					        ('''token_type_ids''', dynamic_axis),
					    ]   )
		@property
		def 					_lowerCamelCase    (		self   )		->   float:
					return 1E-4









"""simple docstring"""




from collections.abc import Callable

a_            =   Callable[[float], float]  # type alias for a real -> real function







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					,							__UpperCamelCase					,							):
			__lowercase	:       str				=   float(__UpperCamelCase					)
			while True:
						try:
									__lowercase	:       Dict				=   prev_guess - function(__UpperCamelCase					) / derivative(__UpperCamelCase					)
						except ZeroDivisionError:
									raise ZeroDivisionError('''Could not find root'''					) from None
						if abs(prev_guess - next_guess					) < 10**-5:
									return next_guess
						__lowercase	:       List[Any]				=   next_guess







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return (x**3) - (2 * x) - 5







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return 3 * (x**2) - 2


if __name__ == "__main__":
			print(newton(f, fa, 3))



