





'''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       UpperCAmelCase (						unittest.TestCase  ):




		@slow
		def 				UpperCAmelCase__   (self      :	List[str]				)					-> Optional[Any]:
						lowercase         = TFCamembertModel.from_pretrained("jplu/tf-camembert-base"				)

						lowercase         = 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 !"

						lowercase         = model(_lowercase				)["""last_hidden_state"""]
						lowercase         = tf.TensorShape((1, 1_0, 7_6_8)				)
						self.assertEqual(output.shape							,			_lowercase				)
						# compare the actual values for a slice.
						lowercase         = 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'''

from functools import lru_cache







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				lowercase         = 2
				lowercase         = set()
				while i * i <= n:
								if n % i:
												i += 1
								else:
												n //= i
												factors.add(lowerCAmelCase_							)
				if n > 1:
								factors.add(lowerCAmelCase_							)
				return factors







@lru_cache
def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return len(unique_prime_factors(lowerCAmelCase_							)							)







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return len(set(lowerCAmelCase_							)							) in (0, 1)







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				lowercase         = 2

				while True:
								# Increment each value of a generated range
								lowercase         = [base + i for i in range(lowerCAmelCase_							)]

								# Run elements through out unique_prime_factors function
								# Append our target number to the end.
								lowercase         = [upf_len(lowerCAmelCase_							) for x in group]
								checker.append(lowerCAmelCase_							)

								# If all numbers in the list are equal, return the group variable.
								if equality(lowerCAmelCase_							):
												return group

								# Increment our base variable by 1
								base += 1







def 							UpperCAmelCase_    (	lowerCAmelCase_ = 4							):

				"""simple docstring"""






				lowercase         = run(lowerCAmelCase_							)
				return results[0] if len(lowerCAmelCase_							) else None


if __name__ == "__main__":
			print(solution())




