
from ...configuration_utils import PretrainedConfig


lowerCamelCase__	=							{
    "google/tapas-base-finetuned-sqa": (
        "https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"
    ),
    "google/tapas-base-finetuned-wtq": (
        "https://huggingface.co/google/tapas-base-finetuned-wtq/resolve/main/config.json"
    ),
    "google/tapas-base-finetuned-wikisql-supervised": (
        "https://huggingface.co/google/tapas-base-finetuned-wikisql-supervised/resolve/main/config.json"
    ),
    "google/tapas-base-finetuned-tabfact": (
        "https://huggingface.co/google/tapas-base-finetuned-tabfact/resolve/main/config.json"
    ),
}







class        lowerCAmelCase__      (   __lowercase	):
						UpperCamelCase_							: int	=		"tapas"

						def __init__(			self       ,							a=3_05_22       ,							a=7_68       ,							a=12       ,							a=12       ,							a=30_72       ,							a="gelu"       ,							a=0.1       ,							a=0.1       ,							a=10_24       ,							a=[3, 2_56, 2_56, 2, 2_56, 2_56, 10]       ,							a=0.02       ,							a=1e-12       ,							a=0       ,							a=10.0       ,							a=0       ,							a=1.0       ,							a=None       ,							a=1.0       ,							a=False       ,							a=None       ,							a=1.0       ,							a=1.0       ,							a=False       ,							a=False       ,							a="ratio"       ,							a=None       ,							a=None       ,							a=64       ,							a=32       ,							a=False       ,							a=True       ,							a=False       ,							a=False       ,							a=True       ,							a=False       ,							a=None       ,							a=None       ,							**a       ,							)					->      str:


								'''simple docstring'''

								super().__init__(pad_token_id=a       ,							**a				)

								# BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
								_UpperCamelCase						    =	vocab_size
								_UpperCamelCase						    =	hidden_size
								_UpperCamelCase						    =	num_hidden_layers
								_UpperCamelCase						    =	num_attention_heads
								_UpperCamelCase						    =	hidden_act
								_UpperCamelCase						    =	intermediate_size
								_UpperCamelCase						    =	hidden_dropout_prob
								_UpperCamelCase						    =	attention_probs_dropout_prob
								_UpperCamelCase						    =	max_position_embeddings
								_UpperCamelCase						    =	type_vocab_sizes
								_UpperCamelCase						    =	initializer_range
								_UpperCamelCase						    =	layer_norm_eps

								# Fine-tuning task hyperparameters
								_UpperCamelCase						    =	positive_label_weight
								_UpperCamelCase						    =	num_aggregation_labels
								_UpperCamelCase						    =	aggregation_loss_weight
								_UpperCamelCase						    =	use_answer_as_supervision
								_UpperCamelCase						    =	answer_loss_importance
								_UpperCamelCase						    =	use_normalized_answer_loss
								_UpperCamelCase						    =	huber_loss_delta
								_UpperCamelCase						    =	temperature
								_UpperCamelCase						    =	aggregation_temperature
								_UpperCamelCase						    =	use_gumbel_for_cells
								_UpperCamelCase						    =	use_gumbel_for_aggregation
								_UpperCamelCase						    =	average_approximation_function
								_UpperCamelCase						    =	cell_selection_preference
								_UpperCamelCase						    =	answer_loss_cutoff
								_UpperCamelCase						    =	max_num_rows
								_UpperCamelCase						    =	max_num_columns
								_UpperCamelCase						    =	average_logits_per_cell
								_UpperCamelCase						    =	select_one_column
								_UpperCamelCase						    =	allow_empty_column_selection
								_UpperCamelCase						    =	init_cell_selection_weights_to_zero
								_UpperCamelCase						    =	reset_position_index_per_cell
								_UpperCamelCase						    =	disable_per_token_loss

								# Aggregation hyperparameters
								_UpperCamelCase						    =	aggregation_labels
								_UpperCamelCase						    =	no_aggregation_label_index

								if isinstance(self.aggregation_labels       ,							a				):
										_UpperCamelCase						    =	{int(a				): v for k, v in aggregation_labels.items()}





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


def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase = "x"						,  lowerCAmelCase = 1_0**-1_0						,  lowerCAmelCase = 1						,  )		->				complex:

		"""simple docstring"""






		_UpperCamelCase						    =	symbols(lowerCAmelCase )
		_UpperCamelCase						    =	lambdify(lowerCAmelCase						,  lowerCAmelCase )
		_UpperCamelCase						    =	lambdify(lowerCAmelCase						,  diff(lowerCAmelCase						,  lowerCAmelCase ) )

		_UpperCamelCase						    =	starting_point

		while True:
				if diff_function(lowerCAmelCase ) != 0:
						_UpperCamelCase						    =	prev_guess - multiplicity * func(lowerCAmelCase ) / diff_function(
						    lowerCAmelCase )
				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", 10, precision=0.0_05)}""",
		)

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



