






A	:		Optional[int]    =       "Input must be a string of 8 numbers plus letter"
A	:		str    =       "TRWAGMYFPDXBNJZSQVHLCKE"






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




		if not isinstance(__magic_name__   ,   __magic_name__					):
				lowercase__					      =		f'''Expected string as input, found {type(__magic_name__					).__name__}'''
				raise TypeError(__magic_name__					)

		lowercase__					      =		spanish_id.replace("""-"""   ,   """"""					).upper()
		if len(__magic_name__					) != 9:
				raise ValueError(__magic_name__					)

		try:
				lowercase__					      =		int(spanish_id_clean[0:8]					)
				lowercase__					      =		spanish_id_clean[8]
		except ValueError as ex:
				raise ValueError(__magic_name__					) from ex

		if letter.isdigit():
				raise ValueError(__magic_name__					)

		return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
	import doctest

	doctest.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		)		)

