
'''simple docstring'''

import gc
import unittest

from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
    import jax
    import jax.numpy as jnp
    from flax.jax_utils import replicate
    from flax.training.common_utils import shard


@slow
@require_flax
class  _UpperCAmelCase ( unittest.TestCase    ):

     """simple docstring"""

     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       super().tearDown()
       gc.collect()






     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	List[str]      =							load_image(
           """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"""
           """/sd2-inpaint/init_image.png""" )
       a_      :	str      =							load_image(
           """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png""" )

       a_      :	Any      =							"""xvjiarui/stable-diffusion-2-inpainting"""
       a_      , a_      :	Optional[Any]      =							FlaxStableDiffusionInpaintPipeline.from_pretrained(lowerCAmelCase_							,		safety_checker=lowerCAmelCase_ )

       a_      :	Optional[int]      =							"""Face of a yellow cat, high resolution, sitting on a park bench"""

       a_      :	Union[str, Any]      =							jax.random.PRNGKey(0 )
       a_      :	Dict      =							50

       a_      :	List[str]      =							jax.device_count()
       a_      :	str      =							num_samples * [prompt]
       a_      :	Tuple      =							num_samples * [init_image]
       a_      :	int      =							num_samples * [mask_image]
       a_      , a_      , a_      :	Dict      =							pipeline.prepare_inputs(lowerCAmelCase_							,		lowerCAmelCase_							,		lowerCAmelCase_ )

       # shard inputs and rng
       a_      :	List[Any]      =							replicate(lowerCAmelCase_ )
       a_      :	Optional[Any]      =							jax.random.split(lowerCAmelCase_							,		jax.device_count() )
       a_      :	Optional[Any]      =							shard(lowerCAmelCase_ )
       a_      :	Dict      =							shard(lowerCAmelCase_ )
       a_      :	Dict      =							shard(lowerCAmelCase_ )

       a_      :	Optional[int]      =							pipeline(
           lowerCAmelCase_							,		lowerCAmelCase_							,		lowerCAmelCase_							,		lowerCAmelCase_							,		lowerCAmelCase_							,		lowerCAmelCase_							,		jit=lowerCAmelCase_ )

       a_      :	Any      =							output.images.reshape(lowerCAmelCase_							,		5_12							,		5_12							,		3 )

       a_      :	Union[str, Any]      =							images[0, 2_53:2_56, 2_53:2_56, -1]

       a_      :	Dict      =							jnp.asarray(jax.device_get(image_slice.flatten() ) )
       a_      :	Dict      =							jnp.array(
           [0.3611307, 0.37649736, 0.3757408, 0.38213953, 0.39295167, 0.3841631, 0.41554978, 0.4137475, 0.4217084] )
       print(f'''output_slice: {output_slice}''' )
       assert jnp.abs(output_slice - expected_slice ).max() < 1E-2




'''simple docstring'''

def 	_snake_case						(      A_       :    int     ,		A_       :    Optional[Any]     ,		A_       :    Optional[int]     ,		A_       :    Dict   ):
  """simple docstring"""







  a_      :	Optional[int]      =							[False] * len(A_   )
  a_      :	List[str]      =							[]
  queue.append(A_   )
  a_      :	Union[str, Any]      =							True

  while queue:
    a_      :	List[Any]      =							queue.pop(0   )
    for ind in range(len(graph[u]   )   ):
      if visited[ind] is False and graph[u][ind] > 0:
        queue.append(A_   )
        a_      :	Any      =							True
        a_      :	List[Any]      =							u

  return visited[t]






def 	_snake_case						(      A_       :    Union[str, Any]     ,		A_       :    Union[str, Any]     ,		A_       :    List[Any]   ):
  """simple docstring"""







  a_      :	Dict      =							[-1] * (len(A_   ))
  a_      :	List[str]      =							0
  while bfs(A_     ,		A_     ,		A_     ,		A_   ):
    a_      :	Any      =							float("""Inf"""   )
    a_      :	Any      =							sink

    while s != source:
      # Find the minimum value in select path
      a_      :	Any      =							min(A_     ,		graph[parent[s]][s]   )
      a_      :	List[Any]      =							parent[s]

    max_flow += path_flow
    a_      :	Tuple      =							sink

    while v != source:
      a_      :	Tuple      =							parent[v]
      graph[u][v] -= path_flow
      graph[v][u] += path_flow
      a_      :	List[Any]      =							parent[v]
  return max_flow


__snake_case:  List[str]								=			[
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

__snake_case							,__snake_case:  int								=			0, 5




print(ford_fulkerson(graph, source, sink))


