


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 _lowerCamelCase(						unittest.TestCase   ):
       @slow
       def 			UpperCamelCase     (					self)       ->   int:




           """simple docstring"""

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

           _lowercase       :							Tuple      		=		tf.convert_to_tensor(
               [[5, 1_21, 11, 6_60, 16, 7_30, 2_55_43, 1_10, 83, 6]],      dtype=tf.intaa,      )  # J'aime le camembert !"

           _lowercase       :							List[Any]      		=		model(lowerCamelCase)['last_hidden_state']
           _lowercase       :							Optional[int]      		=		tf.TensorShape((1, 10, 7_68))
           self.assertEqual(output.shape,      lowerCamelCase)
           # compare the actual values for a slice.
           _lowercase       :							Any      		=		tf.convert_to_tensor(
               [[[-0.0_2_5_4, 0.0_2_3_5, 0.1_0_2_7], [0.0_6_0_6, -0.1_8_1_1, -0.0_4_1_8], [-0.1_5_6_1, -0.1_1_2_7, 0.2_6_8_7]]],      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)))


