
'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case:	Optional[Any]										=      logging.get_logger(__name__)

__snake_case:	Optional[int]										=      {
    "google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
    # See all CANINE models at https://huggingface.co/models?filter=canine
}


class 			_UpperCAmelCase			(			__A     ):

     """simple docstring"""

     a_     						=       'canine'


     def __init__(   self				,		lowerCAmelCase_=7_68				,		lowerCAmelCase_=12				,		lowerCAmelCase_=12				,		lowerCAmelCase_=30_72				,		lowerCAmelCase_="gelu"				,		lowerCAmelCase_=0.1				,		lowerCAmelCase_=0.1				,		lowerCAmelCase_=1_63_84				,		lowerCAmelCase_=16				,		lowerCAmelCase_=0.02				,		lowerCAmelCase_=1E-1_2				,		lowerCAmelCase_=0				,		lowerCAmelCase_=0xE000				,		lowerCAmelCase_=0xE001				,		lowerCAmelCase_=4				,		lowerCAmelCase_=4				,		lowerCAmelCase_=8				,		lowerCAmelCase_=1_63_84				,		lowerCAmelCase_=1_28				,		**lowerCAmelCase_				,		):

       '''simple docstring'''

       super().__init__(pad_token_id=snake_case_				,		bos_token_id=snake_case_				,		eos_token_id=snake_case_				,		**snake_case_			)

       a_   :						Dict   =				max_position_embeddings
       a_   :						Union[str, Any]   =				hidden_size
       a_   :						str   =				num_hidden_layers
       a_   :						Optional[Any]   =				num_attention_heads
       a_   :						str   =				intermediate_size
       a_   :						Optional[int]   =				hidden_act
       a_   :						Tuple   =				hidden_dropout_prob
       a_   :						int   =				attention_probs_dropout_prob
       a_   :						str   =				initializer_range
       a_   :						Tuple   =				type_vocab_size
       a_   :						Tuple   =				layer_norm_eps

       # Character config:
       a_   :						List[Any]   =				downsampling_rate
       a_   :						Optional[Any]   =				upsampling_kernel_size
       a_   :						Union[str, Any]   =				num_hash_functions
       a_   :						Any   =				num_hash_buckets
       a_   :						List[str]   =				local_transformer_stride



"""simple docstring"""



from collections.abc import Sequence

def  _A(		lowerCAmelCase			,  lowerCAmelCase							):
							return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase							)							)

def  _A(		lowerCAmelCase			,  lowerCAmelCase							):
							A__       :     str								=			0.0
							for coeff in reversed(lowerCAmelCase							):
														A__       :     Optional[int]								=			result * x + coeff
							return result


if __name__ == "__main__":
				_UpperCamelCase								=		(0.0, 0.0, 5.0, 9.3, 7.0)
				_UpperCamelCase								=		10.0
				print(evaluate_poly(poly, x))
				print(horner(poly, x))





