



'''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 TFXLMRobertaModel






@require_tf
@require_sentencepiece
@require_tokenizers
class 						_UpperCamelCase  (							unittest.TestCase    ):


			'''simple docstring'''

			@slow
			def UpperCamelCase__					(							self     : List[Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Tuple           =		TFXLMRobertaModel.from_pretrained("""jplu/tf-xlm-roberta-base"""						)

					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		{
					    """input_ids""": tf.convert_to_tensor([[0, 2_6_4_6, 1_0_2_6_9, 8_3, 9_9_9_4_2, 2]]							,     dtype=tf.intaa						),  # "My dog is cute"
					    """attention_mask""": tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]							,     dtype=tf.intaa						),
					}

					__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		model(lowerCAmelCase__						)["""last_hidden_state"""]
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		tf.TensorShape((1, 6, 7_6_8)						)
					self.assertEqual(output.shape							,     lowerCAmelCase__						)
					# compare the actual values for a slice.
					__SCREAMING_SNAKE_CASE       :		str           =		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						)						)




'''simple docstring'''




from __future__ import annotations


def 				lowerCAmelCase_   (	_lowerCamelCase:   list[int]       ,      _lowerCamelCase:   list[int]       ,      _lowerCamelCase:   int					):
		__SCREAMING_SNAKE_CASE       :		List[Any]           =		list(range(len(_lowerCamelCase					)					)					)
		__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		[v / w for v, w in zip(_lowerCamelCase       ,      _lowerCamelCase					)]
		index.sort(key=lambda _lowerCamelCase					: ratio[i]       ,      reverse=_lowerCamelCase					)

		__SCREAMING_SNAKE_CASE       :		float           =		0
		__SCREAMING_SNAKE_CASE       :		list[float]           =		[0] * len(_lowerCamelCase					)
		for i in index:
				if weight[i] <= capacity:
						__SCREAMING_SNAKE_CASE       :		str           =		1
						max_value += value[i]
						capacity -= weight[i]
				else:
						__SCREAMING_SNAKE_CASE       :		int           =		capacity / weight[i]
						max_value += value[i] * capacity / weight[i]
						break

		return max_value, fractions


if __name__ == "__main__":
						import doctest

						doctest.testmod()