
"""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     A_	(     unittest.TestCase   ):



							"""simple docstring"""






							@slow
							def       UpperCAmelCase__							(  self  :Dict       ):





										"""simple docstring"""

										lowerCamelCase__	:     Dict              =TFCamembertModel.from_pretrained('jplu/tf-camembert-base'       )

										lowerCamelCase__	:     Tuple              =tf.convert_to_tensor(
										    [[5, 121, 11, 660, 16, 730, 25_543, 110, 83, 6]]     ,							dtype=tf.intaa     ,							)  # J'aime le camembert !"

										lowerCamelCase__	:     List[Any]              =model(lowerCamelCase_       )['last_hidden_state']
										lowerCamelCase__	:     Optional[int]              =tf.TensorShape((1, 10, 768)       )
										self.assertEqual(output.shape     ,							lowerCamelCase_       )
										# compare the actual values for a slice.
										lowerCamelCase__	:     Any              =tf.convert_to_tensor(
										    [[[-0.02_54, 0.02_35, 0.10_27], [0.06_06, -0.18_11, -0.04_18], [-0.15_61, -0.11_27, 0.26_87]]]     ,							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       )       )



from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

SCREAMING_SNAKE_CASE       :      Tuple												= (3, 9, -11, 0, 7, 5, 1, -1)
SCREAMING_SNAKE_CASE       :      Union[str, Any]												= (4, 6, 2, 0, 8, 10, 3, -2)






@dataclass
class _lowerCamelCase:
       lowercase_ :	int
       lowercase_ :	Node | None






class _lowerCamelCase:
       def __init__(					self,      lowerCamelCase)       ->   None:




           """simple docstring"""

           _lowercase       :							Node | None      		=		None
           for i in sorted(lowerCamelCase,      reverse=lowerCamelCase):
               _lowercase       :							Tuple      		=		Node(lowerCamelCase,      self.head)
       def __iter__(					self)       ->   Iterator[int]:




           """simple docstring"""

           _lowercase       :							Union[str, Any]      		=		self.head
           while node:
               yield node.data
               _lowercase       :							int      		=		node.next_node
       def __len__(					self)       ->   int:




           """simple docstring"""

           return sum(1 for _ in self)




       def __str__(					self)       ->   str:




           """simple docstring"""

           return " -> ".join([str(lowerCamelCase) for node in self])



def 				UpperCamelCase_(      lowerCamelCase_							, lowerCamelCase_ )    ->						SortedLinkedList:
    return SortedLinkedList(list(lowerCamelCase_ ) + list(lowerCamelCase_ ) )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 SCREAMING_SNAKE_CASE       :      int												= SortedLinkedList
 print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))


