





"""simple docstring"""





from cva import destroyAllWindows, imread, imshow, waitKey



def 					lowerCAmelCase_      (   SCREAMING_SNAKE_CASE							:				List[Any] ):


							'''simple docstring'''







							__lowerCamelCase     ,    __lowerCamelCase   :   List[Any]       =img.shape[0], img.shape[1]

							# converting each pixel's color to its negative
							for i in range(SCREAMING_SNAKE_CASE ):
														for j in range(SCREAMING_SNAKE_CASE ):
																					__lowerCamelCase   :   Union[str, Any]       =[255, 255, 255] - img[i][j]

							return img


if __name__ == "__main__":
							# read original image
							_UpperCamelCase					      =   imread('image_data/lena.jpg', 1)

							# convert to its negative
							_UpperCamelCase					      =   convert_to_negative(img)

							# show result image
							imshow('negative of original image', img)
							waitKey(0)
							destroyAllWindows()











"""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 		SCREAMING_SNAKE_CASE_				(     unittest.TestCase ):
				"""simple docstring"""




				@slow
				def        __lowercase	(  self	:Union[str, Any]      ):
											__lowerCamelCase   :   List[Any]       =TFXLMRobertaModel.from_pretrained('''jplu/tf-xlm-roberta-base'''      )

											__lowerCamelCase   :   Dict       ={
											    '''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      ),
											}

											__lowerCamelCase   :   Optional[int]       =model(__lowercase      )['''last_hidden_state''']
											__lowerCamelCase   :   str       =tf.TensorShape((1, 6, 768)      )
											self.assertEqual(output.shape    ,     __lowercase      )
											# compare the actual values for a slice.
											__lowerCamelCase   :   str       =tf.convert_to_tensor(
											    [
											        [
											            [0.0681762, 0.10894451, 0.06772504],
											            [-0.06423668, 0.02366615, 0.04329344],
											            [-0.06057295, 0.09974135, -0.00070584],
											        ]
											    ]    ,     dtype=tf.floataa    ,     )

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




