


def 			UpperCamelCase (     __magic_name__					:							str					)       ->  str:
		"""simple docstring"""




		if not all(char in """01""" for char in bin_string					):
				raise ValueError("""Non-binary value was passed to the function"""					)
		if not bin_string:
				raise ValueError("""Empty string was passed to the function"""					)
		lowercase__					      =		""""""
		while len(__magic_name__					) % 3 != 0:
				lowercase__					      =		"""0""" + bin_string
		lowercase__					      =		[
		    bin_string[index : index + 3]
		    for index in range(len(__magic_name__					)					)
		    if index % 3 == 0
		]
		for bin_group in bin_string_in_3_list:
				lowercase__					      =		0
				for index, val in enumerate(__magic_name__					):
						oct_val += int(2 ** (2 - index) * int(__magic_name__					)					)
				oct_string += str(__magic_name__					)
		return oct_string


if __name__ == "__main__":
	from doctest import testmod

	testmod()





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 							A   (	unittest.TestCase							):
					'''simple docstring'''






					@slow
					def   lowerCamelCase__					(self   :						Any		)						->       Union[str, Any]:




							"""simple docstring"""


							lowercase__					      =		TFXLMRobertaModel.from_pretrained("""jplu/tf-xlm-roberta-base"""		)

							lowercase__					      =		{
							    """input_ids""": tf.convert_to_tensor([[0, 2646, 1_0269, 83, 9_9942, 2]]				, dtype=tf.intaa		),  # "My dog is cute"
							    """attention_mask""": tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]				, dtype=tf.intaa		),
							}

							lowercase__					      =		model(_UpperCAmelCase		)["""last_hidden_state"""]
							lowercase__					      =		tf.TensorShape((1, 6, 768)		)
							self.assertEqual(output.shape				, _UpperCAmelCase		)
							# compare the actual values for a slice.
							lowercase__					      =		tf.convert_to_tensor(
							    [
							        [
							            [0.0_681_762, 0.10_894_451, 0.06_772_504],
							            [-0.06_423_668, 0.02_366_615, 0.04_329_344],
							            [-0.06_057_295, 0.09_974_135, -0.00_070_584],
							        ]
							    ]				, dtype=tf.floataa				, )

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

