






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


snake_case__      :	Dict       	=      logging.get_logger(__name__)

snake_case__      :	List[Any]       	=      {
    """weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}


class 						_a       (  lowercase_    ):






		"""simple docstring"""





		A_						=   """roc_bert"""




		def __init__(     self		,		_UpperCAmelCase=30522		,		_UpperCAmelCase=768		,		_UpperCAmelCase=12		,		_UpperCAmelCase=12		,		_UpperCAmelCase=3072		,		_UpperCAmelCase="gelu"		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=512		,		_UpperCAmelCase=2		,		_UpperCAmelCase=0.0_2		,		_UpperCAmelCase=1e-12		,		_UpperCAmelCase=True		,		_UpperCAmelCase=0		,		_UpperCAmelCase="absolute"		,		_UpperCAmelCase=None		,		_UpperCAmelCase=True		,		_UpperCAmelCase=True		,		_UpperCAmelCase=768		,		_UpperCAmelCase=910		,		_UpperCAmelCase=512		,		_UpperCAmelCase=24858		,		_UpperCAmelCase=True		,		**_UpperCAmelCase		,		)			-> str:
					UpperCamelCase_									=     vocab_size
					UpperCamelCase_									=     max_position_embeddings
					UpperCamelCase_									=     hidden_size
					UpperCamelCase_									=     num_hidden_layers
					UpperCamelCase_									=     num_attention_heads
					UpperCamelCase_									=     intermediate_size
					UpperCamelCase_									=     hidden_act
					UpperCamelCase_									=     hidden_dropout_prob
					UpperCamelCase_									=     attention_probs_dropout_prob
					UpperCamelCase_									=     initializer_range
					UpperCamelCase_									=     type_vocab_size
					UpperCamelCase_									=     layer_norm_eps
					UpperCamelCase_									=     use_cache
					UpperCamelCase_									=     enable_pronunciation
					UpperCamelCase_									=     enable_shape
					UpperCamelCase_									=     pronunciation_embed_dim
					UpperCamelCase_									=     pronunciation_vocab_size
					UpperCamelCase_									=     shape_embed_dim
					UpperCamelCase_									=     shape_vocab_size
					UpperCamelCase_									=     concat_input
					UpperCamelCase_									=     position_embedding_type
					UpperCamelCase_									=     classifier_dropout
					super().__init__(pad_token_id=lowerCamelCase_		,		**lowerCamelCase_ )













from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403






def     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase = "x"    ,      __lowercase = 10**-10    ,      __lowercase = 1    ,      ):
   UpperCamelCase_									=     symbols(__lowercase)
   UpperCamelCase_									=     lambdify(__lowercase    ,      __lowercase)
   UpperCamelCase_									=     lambdify(__lowercase    ,      diff(__lowercase    ,      __lowercase))

   UpperCamelCase_									=     starting_point

   while True:
      if diff_function(__lowercase) != 0:
         UpperCamelCase_									=     prev_guess - multiplicity * func(__lowercase) / diff_function(
             __lowercase)
      else:
         raise ZeroDivisionError('Could not find root') from None

      # Precision is checked by comparing the difference of consecutive guesses
      if abs(next_guess - prev_guess) < precision:
         return next_guess

      UpperCamelCase_									=     next_guess


# Let's Execute
if __name__ == "__main__":
 # Find root of trigonometric function
 # Find value of pi
 print(f'The root of sin(x) = 0 is {newton_raphson("sin(x)", 2)}')

 # Find root of polynomial
 # Find fourth Root of 5
 print(f'The root of x**4 - 5 = 0 is {newton_raphson("x**4 -5", 0.4 +5J)}')

 # Find value of e
 print(
     """The root of log(y) - 1 = 0 is """,
     f'{newton_raphson("log(y) - 1", 2, variable="y")}',
 )

 # Exponential Roots
 print(
     """The root of exp(x) - 1 = 0 is""",
     f'{newton_raphson("exp(x) - 1", 1_0, precision=0.005)}',
 )

 # Find root of cos(x)
 print(f'The root of cos(x) = 0 is {newton_raphson("cos(x)", 0)}')





