






'''simple docstring'''

import unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
   import jax.numpy as jnp

   from transformers import FlaxXLMRobertaModel






@require_sentencepiece
@require_tokenizers
@require_flax
class     a_						(      unittest.TestCase    ):

  @slow
  def   A__						(				self				)  ->				Tuple:



        """simple docstring"""






        UpperCamelCase      = FlaxXLMRobertaModel.from_pretrained("""xlm-roberta-base"""				)
        UpperCamelCase      = AutoTokenizer.from_pretrained("""xlm-roberta-base"""				)
        UpperCamelCase      = """The dog is cute and lives in the garden house"""
        UpperCamelCase      = jnp.array([tokenizer.encode(_lowercase				)]				)

        UpperCamelCase      = (1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
        UpperCamelCase      = jnp.array(
            [[-0.0_1_0_1, 0.1_2_1_8, -0.0_8_0_3, 0.0_8_0_1, 0.1_3_2_7, 0.0_7_7_6, -0.1_2_1_5, 0.2_3_8_3, 0.3_3_3_8, 0.3_1_0_6, 0.0_3_0_0, 0.0_2_5_2]]				)

        UpperCamelCase      = model(_lowercase				)["""last_hidden_state"""]
        self.assertEqual(output.shape      ,		_lowercase				)
        # compare the actual values for a slice of last dim
        self.assertTrue(jnp.allclose(output[:, :, -1]      ,		_lowercase      ,		atol=1e-3				)				)








'''simple docstring'''

from PIL import Image







def    lowercase__			(				__UpperCamelCase		,						__UpperCamelCase   )->			Image:

      def brightness(__UpperCamelCase   ) -> float:
            return 128 + level + (c - 128)

      if not -255.0 <= level <= 255.0:
            raise ValueError("""level must be between -255.0 (black) and 255.0 (white)"""   )
      return img.point(__UpperCamelCase   )


if __name__ == "__main__":
     # Load image
     with Image.open('image_data/lena.jpg') as img:
          # Change brightness to 100
          SCREAMING_SNAKE_CASE__     =       change_brightness(img, 1_0_0)
          brigt_img.save('image_data/lena_brightness.png', format='png')
