


"""simple docstring"""


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 snake_case      (  unittest.TestCase):







		@slow
		def  a_ (					self      :       Optional[int]		)       ->						Optional[int]:





						'''simple docstring'''







						_A					  =			TFCamembertModel.from_pretrained("jplu/tf-camembert-base"		)

						_A					  =			tf.convert_to_tensor(
						    [[5, 1_21, 11, 6_60, 16, 7_30, 2_55_43, 1_10, 83, 6]]    ,   dtype=tf.intaa    ,   )  # J'aime le camembert !"

						_A					  =			model(a__		)["last_hidden_state"]
						_A					  =			tf.TensorShape((1, 10, 7_68)		)
						self.assertEqual(output.shape    ,   a__		)
						# compare the actual values for a slice.
						_A					  =			tf.convert_to_tensor(
						    [[[-0.0_2_5_4, 0.0_2_3_5, 0.1_0_2_7], [0.0_6_0_6, -0.1_8_1_1, -0.0_4_1_8], [-0.1_5_6_1, -0.1_1_2_7, 0.2_6_8_7]]]    ,   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		)		)










"""simple docstring"""


import random






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	Optional[Any]:
				_A					  =			a[left_index]
				_A					  =			left_index + 1
				for j in range(left_index + 1     ,			__lowercase   ):
								if a[j] < pivot:
												_A  ,		_A					  =			a[i], a[j]
												i += 1
				_A  ,		_A					  =			a[i - 1], a[left_index]
				return i - 1






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	int:
				if left < right:
								_A					  =			random.randint(__lowercase     ,			right - 1   )
								_A  ,		_A					  =			(
								    a[left],
								    a[pivot],
								)  # switches the pivot with the left most bound
								_A					  =			partition(__lowercase     ,			__lowercase     ,			__lowercase   )
								quick_sort_random(
								    __lowercase     ,			__lowercase     ,			__lowercase   )  # recursive quicksort to the left of the pivot point
								quick_sort_random(
								    __lowercase     ,			pivot_index + 1     ,			__lowercase   )  # recursive quicksort to the right of the pivot point






def      a__ (				)	->	Dict:
				_A					  =			input("Enter numbers separated by a comma:\n"   ).strip()
				_A					  =			[int(__lowercase   ) for item in user_input.split(","   )]

				quick_sort_random(__lowercase     ,			0     ,			len(__lowercase   )   )

				print(__lowercase   )


if __name__ == "__main__":
		main()