

'''simple docstring'''







import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin


@skip_mps
class    A__ ( _snake_case  ,  _snake_case  ,  unittest.TestCase     ):
    lowercase		   =						IFInpaintingPipeline
    lowercase		   =						TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"width", "height"}
    lowercase		   =						TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
    lowercase		   =						PipelineTesterMixin.required_optional_params - {"latents"}



    def    snake_case_     (   self    )  -> Union[str, Any]:





           '''simple docstring'''
           return self._get_dummy_components()



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__=0    )  -> Optional[Any]:





           '''simple docstring'''
           if str(UpperCamelCase__    ).startswith("""mps"""    ):
                  A_		   = torch.manual_seed(UpperCamelCase__    )
           else:
                  A_		   = torch.Generator(device=UpperCamelCase__    ).manual_seed(UpperCamelCase__    )

           A_		   = floats_tensor((1, 3, 32, 32)						,			rng=random.Random(UpperCamelCase__    )    ).to(UpperCamelCase__    )
           A_		   = floats_tensor((1, 3, 32, 32)						,			rng=random.Random(UpperCamelCase__    )    ).to(UpperCamelCase__    )

           A_		   = {
               """prompt""": """A painting of a squirrel eating a burger""",
               """image""": image,
               """mask_image""": mask_image,
               """generator""": generator,
               """num_inference_steps""": 2,
               """output_type""": """numpy""",
           }

           return inputs



    @unittest.skipIf(
        torch_device != """cuda""" or not is_xformers_available()						,			reason="""XFormers attention is only available with CUDA and `xformers` installed"""						,			)
    def    snake_case_     (   self    )  -> Any:





           '''simple docstring'''
           self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3    )



    def    snake_case_     (   self    )  -> str:





           '''simple docstring'''
           self._test_save_load_optional_components()



    @unittest.skipIf(torch_device != """cuda"""						,			reason="""float16 requires CUDA"""    )
    def    snake_case_     (   self    )  -> Optional[int]:





           '''simple docstring'''
           # Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
           super().test_save_load_floataa(expected_max_diff=1e-1    )



    def    snake_case_     (   self    )  -> Optional[Any]:





           '''simple docstring'''
           self._test_attention_slicing_forward_pass(expected_max_diff=1e-2    )



    def    snake_case_     (   self    )  -> List[Any]:





           '''simple docstring'''
           self._test_save_load_local()







    def    snake_case_     (   self    )  -> Union[str, Any]:





           '''simple docstring'''
           self._test_inference_batch_single_identical(
               expected_max_diff=1e-2						,			)



'''simple docstring'''







import heapq as hq
import math
from collections.abc import Iterator


class    A__ :



    def __init__(   self						,			UpperCamelCase__    )  -> Dict:





           '''simple docstring'''
           A_		   = str(id_    )
           A_		   = None
           A_		   = None
           A_		   = []
           A_		   = {}  # {vertex:distance}



    def __lt__(   self						,			UpperCamelCase__    )  -> Optional[int]:





           '''simple docstring'''
           return self.key < other.key



    def __repr__(   self    )  -> Dict:





           '''simple docstring'''
           return self.id



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> Dict:





           '''simple docstring'''
           self.neighbors.append(UpperCamelCase__    )







    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__    )  -> Optional[Any]:





           '''simple docstring'''
           A_		   = weight

def  UpperCAmelCase__      ( UpperCAmelCase__,    UpperCAmelCase__,    UpperCAmelCase__,    UpperCAmelCase__			)     ->     Optional[int]:
       # add the neighbors:
       graph[a - 1].add_neighbor(graph[b - 1]			)
       graph[b - 1].add_neighbor(graph[a - 1]			)
       # add the edges:
       graph[a - 1].add_edge(graph[b - 1],    UpperCAmelCase__			)
       graph[b - 1].add_edge(graph[a - 1],    UpperCAmelCase__			)
def  UpperCAmelCase__      ( UpperCAmelCase__,    UpperCAmelCase__			)     ->     list:
       A_		   = []
       for u in graph:
              A_		   = math.inf
              A_		   = None
       A_		   = 0
       A_		   = graph[:]
       while q:
              A_		   = min(UpperCAmelCase__			)
              q.remove(UpperCAmelCase__			)
              for v in u.neighbors:
                     if (v in q) and (u.edges[v.id] < v.key):
                            A_		   = u
                            A_		   = u.edges[v.id]
       for i in range(1,    len(UpperCAmelCase__			)			):
              a.append((int(graph[i].id			) + 1, int(graph[i].pi.id			) + 1)			)
       return a
def  UpperCAmelCase__      ( UpperCAmelCase__,    UpperCAmelCase__			)     ->     Iterator[tuple]:
       for u in graph:
              A_		   = math.inf
              A_		   = None
       A_		   = 0

       A_		   = list(UpperCAmelCase__			)
       hq.heapify(UpperCAmelCase__			)

       while h:
              A_		   = hq.heappop(UpperCAmelCase__			)
              for v in u.neighbors:
                     if (v in h) and (u.edges[v.id] < v.key):
                            A_		   = u
                            A_		   = u.edges[v.id]
                            hq.heapify(UpperCAmelCase__			)

       for i in range(1,    len(UpperCAmelCase__			)			):
              yield (int(graph[i].id			) + 1, int(graph[i].pi.id			) + 1)
def  UpperCAmelCase__      ( )     ->     None:
       pass


if __name__ == "__main__":
      import doctest

      doctest.testmod()
