


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 TFXLMRobertaModel







@require_tf
@require_sentencepiece
@require_tokenizers
class  snake_case_     (unittest.TestCase   ):
					@slow
					def 				lowerCamelCase__(   self     :List[Any]   )      ->					Union[str, Any]:
												a__    =  TFXLMRobertaModel.from_pretrained('jplu/tf-xlm-roberta-base'   )

												a__    =  {
												    'input_ids': tf.convert_to_tensor([[0, 26_46, 1_02_69, 83, 9_99_42, 2]]    ,dtype=tf.intaa   ),  # "My dog is cute"
												    'attention_mask': tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]    ,dtype=tf.intaa   ),
												}

												a__    =  model(__snake_case   )['last_hidden_state']
												a__    =  tf.TensorShape((1, 6, 7_68)   )
												self.assertEqual(output.shape    ,__snake_case   )
												# compare the actual values for a slice.
												a__    =  tf.convert_to_tensor(
												    [
												        [
												            [0.0_68_17_62, 0.10_89_44_51, 0.06_77_25_04],
												            [-0.06_42_36_68, 0.02_36_66_15, 0.04_32_93_44],
												            [-0.06_05_72_95, 0.09_97_41_35, -0.00_07_05_84],
												        ]
												    ]    ,dtype=tf.floataa    ,)

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








def 							__lowercase     (				__lowerCAmelCase							:       int     ):

							if length <= 0 or not isinstance(__lowerCAmelCase      ,					__lowerCAmelCase     ):
														raise ValueError('Length must be a positive integer.'     )
							return [n * (2 * n - 1) for n in range(__lowerCAmelCase     )]


if __name__ == "__main__":
						print(hexagonal_numbers(length=5))
						print(hexagonal_numbers(length=10))




