

'''simple docstring'''


def 	_a       (				__lowerCAmelCase		:      Optional[Any]     ):  # noqa: E741

		"""simple docstring"""

		snake_case__						:       Tuple       						=  len(__lowerCAmelCase     )
		snake_case__						:       List[Any]       						=  0
		snake_case__						:       Optional[Any]       						=  [0] * n
		snake_case__						:       Union[str, Any]       						=  [False] * n
		snake_case__						:       Dict       						=  [False] * n

		def dfs(__lowerCAmelCase		:      Union[str, Any]   ,							__lowerCAmelCase		:      List[Any]   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      Tuple     ):
				if parent == root:
						out_edge_count += 1
				snake_case__						:       Tuple       						=  True
				snake_case__						:       Optional[int]       						=  at

				for to in l[at]:
						if to == parent:
								pass
						elif not visited[to]:
								snake_case__						:       Dict       						=  dfs(__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase     )
								snake_case__						:       str       						=  min(low[at]   ,							low[to]     )

								# AP found via bridge
								if at < low[to]:
										snake_case__						:       List[Any]       						=  True
								# AP found via cycle
								if at == low[to]:
										snake_case__						:       int       						=  True
						else:
								snake_case__						:       Tuple       						=  min(low[at]   ,							__lowerCAmelCase     )
				return out_edge_count

		for i in range(__lowerCAmelCase     ):
				if not visited[i]:
						snake_case__						:       Tuple       						=  0
						snake_case__						:       int       						=  dfs(__lowerCAmelCase   ,							__lowerCAmelCase   ,							-1   ,							__lowerCAmelCase     )
						snake_case__						:       Optional[Any]       						=  out_edge_count > 1

		for x in range(len(__lowerCAmelCase     )     ):
				if is_art[x] is True:
						print(__lowerCAmelCase     )


# Adjacency list of graph
lowerCAmelCase__						:       Union[str, Any]										=						{
    0: [1, 2],
    1: [0, 2],
    2: [0, 1, 3, 5],
    3: [2, 4],
    4: [3],
    5: [2, 6, 8],
    6: [5, 7],
    7: [6, 8],
    8: [5, 7],
}





compute_ap(data)






'''simple docstring'''


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       ):






						"""simple docstring"""




						__UpperCAmelCase			     =    FlaxAutoencoderKL







						@property
						def       __magic_name__							(							self					:      str  ):



								'''simple docstring'''



								snake_case__						:       Any       						=  4
								snake_case__						:       Optional[Any]       						=  3
								snake_case__						:       Optional[int]       						=  (3_2, 3_2)

								snake_case__						:       Optional[int]       						=  jax.random.PRNGKey(0  )
								snake_case__						:       Union[str, Any]       						=  jax.random.uniform(snake_case_			,			((batch_size, num_channels) + sizes)  )

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







						def       __magic_name__							(							self					:      Union[str, Any]  ):



								'''simple docstring'''



								snake_case__						:       Any       						=  {
								    '''block_out_channels''': [3_2, 6_4],
								    '''in_channels''': 3,
								    '''out_channels''': 3,
								    '''down_block_types''': ['''DownEncoderBlock2D''', '''DownEncoderBlock2D'''],
								    '''up_block_types''': ['''UpDecoderBlock2D''', '''UpDecoderBlock2D'''],
								    '''latent_channels''': 4,
								}
								snake_case__						:       Dict       						=  self.dummy_input
								return init_dict, inputs_dict



