






def 		_a       ( a					:Dict      ,				a					:Union[str, Any]      ,				a					:Optional[int]      ,				a					:int      ,				a					:List[str]					)				->     int:







 if index == number_of_items:
  return 0
 a						    = 0
 a						    = 0
 a						    = knapsack(a      ,				a      ,				a      ,				a      ,				index + 1					)
 if weights[index] <= max_weight:
  a						    = values[index] + knapsack(
      a      ,				a      ,				a      ,				max_weight - weights[index]      ,				index + 1					)
 return max(a      ,				a					)


if __name__ == "__main__":
     import doctest

     doctest.testmod()








import unittest

from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax

from .test_modeling_common_flax import FlaxModelTesterMixin


if is_flax_available():
				import jax



@require_flax
class       a_       (     SCREAMING_SNAKE_CASE__  ,    unittest.TestCase     ):
	A    							= FlaxAutoencoderKL





	@property
	def 						A_(							self      )  ->					Optional[Any]:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						4
				SCREAMING_SNAKE_CASE_								=						3
				SCREAMING_SNAKE_CASE_								=						(32, 32)

				SCREAMING_SNAKE_CASE_								=						jax.random.PRNGKey(0      )
				SCREAMING_SNAKE_CASE_								=						jax.random.uniform(SCREAMING_SNAKE_CASE      ,     ((batch_size, num_channels) + sizes)      )

				return {"sample": image, "prng_key": prng_key}





	def 						A_(							self      )  ->					Tuple:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						{
				    'block_out_channels': [32, 64],
				    'in_channels': 3,
				    'out_channels': 3,
				    'down_block_types': ['DownEncoderBlock2D', 'DownEncoderBlock2D'],
				    'up_block_types': ['UpDecoderBlock2D', 'UpDecoderBlock2D'],
				    'latent_channels': 4,
				}
				SCREAMING_SNAKE_CASE_								=						self.dummy_input
				return init_dict, inputs_dict
