

import math
from collections.abc import Callable


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	xa
						snake_case_   =	xa
						while True:
												if x_n == x_na or function(SCREAMING_SNAKE_CASE__       ) == function(SCREAMING_SNAKE_CASE__       ):
																		raise ZeroDivisionError('''float division by zero, could not find root'''       )
												snake_case_   =	x_na - (
												    function(SCREAMING_SNAKE_CASE__       ) / ((function(SCREAMING_SNAKE_CASE__       ) - function(SCREAMING_SNAKE_CASE__       )) / (x_na - x_n))
												)
												if abs(x_na - x_na       ) < 10**-5:
																		return x_na
												snake_case_   =	x_na
												snake_case_   =	x_na


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__       ):
						return math.pow(SCREAMING_SNAKE_CASE__  ,		3       ) - (2 * x) - 5


if __name__ == "__main__":
					print(intersection(f, 3, 3.5))

from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
      import numpy as np
      import tensorflow as tf

      from transformers import TFCamembertModel





@require_tf
@require_sentencepiece
@require_tokenizers
class 							A__		(	unittest.TestCase):
      @slow
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Union[str, Any]							=      TFCamembertModel.from_pretrained("""jplu/tf-camembert-base"""      )

       lowerCamelCase		:	Any							=      tf.convert_to_tensor(
           [[5, 1_2_1, 1_1, 6_6_0, 1_6, 7_3_0, 2_5_5_4_3, 1_1_0, 8_3, 6]]    ,  dtype=tf.intaa    ,  )  # J'aime le camembert !"

       lowerCamelCase		:	str							=      model(__magic_name__      )["""last_hidden_state"""]
       lowerCamelCase		:	Union[str, Any]							=      tf.TensorShape((1, 1_0, 7_6_8)      )
       self.assertEqual(output.shape    ,  __magic_name__      )
       # compare the actual values for a slice.
       lowerCamelCase		:	Dict							=      tf.convert_to_tensor(
           [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]    ,  dtype=tf.floataa    ,  )
       # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
       # camembert.eval()
       # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

       self.assertTrue(np.allclose(output[:, :3, :3].numpy()    ,  expected_slice.numpy()    ,  atol=1e-4      )      )




