




'''simple docstring'''




from __future__ import annotations

from collections.abc import Iterable, Iterator
from typing import Any, Generic, TypeVar

UpperCAmelCase_       				=      TypeVar('T', bound=bool)

class 						lowerCAmelCase_   ( Generic[T]   ):







  '''simple docstring'''







  def __init__(						self    :	str						,		_UpperCAmelCase    :	T ):






   """simple docstring"""






   UpperCAmelCase__										=    value
   UpperCAmelCase__										=    None
   UpperCAmelCase__										=    None


  @property
  def 							SCREAMING_SNAKE_CASE__			(						self    :	Dict ):






   """simple docstring"""






   return self._value



  @staticmethod
  def 							SCREAMING_SNAKE_CASE__			(						_UpperCAmelCase    :	SkewNode[T] | None						,		_UpperCAmelCase    :	SkewNode[T] | None ):






   """simple docstring"""






   if not roota:
    return roota

   if not roota:
    return roota

   if roota.value > roota.value:
    UpperCAmelCase__							,			UpperCAmelCase__										=    roota, roota

   UpperCAmelCase__										=    roota
   UpperCAmelCase__										=    roota.right
   UpperCAmelCase__										=    roota.left
   UpperCAmelCase__										=    SkewNode.merge(_UpperCAmelCase						,		_UpperCAmelCase )

   return result

class 						lowerCAmelCase_   ( Generic[T]   ):







  '''simple docstring'''







  def __init__(						self    :	List[str]						,		_UpperCAmelCase    :	Iterable[T] | None = () ):






   """simple docstring"""






   UpperCAmelCase__										=    None
   if data:
    for item in data:
     self.insert(_UpperCAmelCase )


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






   """simple docstring"""






   return self._root is not None


  def __iter__(						self    :	str ):






   """simple docstring"""






   UpperCAmelCase__										=    []
   while self:
    result.append(self.pop() )

   # Pushing items back to the heap not to clear it.
   for item in result:
    self.insert(_UpperCAmelCase )

   return iter(_UpperCAmelCase )


  def 							SCREAMING_SNAKE_CASE__			(						self    :	Optional[int]						,		_UpperCAmelCase    :	T ):






   """simple docstring"""






   UpperCAmelCase__										=    SkewNode.merge(self._root						,		SkewNode(_UpperCAmelCase ) )


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






   """simple docstring"""






   UpperCAmelCase__										=    self.top()
   UpperCAmelCase__										=    (
       SkewNode.merge(self._root.left						,		self._root.right ) if self._root else None
   )

   return result


  def 							SCREAMING_SNAKE_CASE__			(						self    :	Any ):






   """simple docstring"""






   if not self._root:
    raise IndexError("""Can't get top element for the empty heap.""" )
   return self._root.value



  def 							SCREAMING_SNAKE_CASE__			(						self    :	int ):






   """simple docstring"""






   UpperCAmelCase__										=    None


if __name__ == "__main__":
    import doctest

    doctest.testmod()






'''simple docstring'''




import random
import unittest

import torch

from diffusers import IFImgaImgPipeline
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_VARIATION_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_VARIATION_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin

@skip_mps
class 						lowerCAmelCase_   ( lowerCamelCase_			,  lowerCamelCase_			,  unittest.TestCase   ):







  '''simple docstring'''







  lowerCAmelCase_				:					Any				     =						IFImgaImgPipeline
  lowerCAmelCase_				:					Dict				     =						TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {"""width""", """height"""}
  lowerCAmelCase_				:					Union[str, Any]				     =						TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS
  lowerCAmelCase_				:					Dict				     =						PipelineTesterMixin.required_optional_params - {"""latents"""}


  def 							SCREAMING_SNAKE_CASE__			(						self    :	Optional[int] ):






   """simple docstring"""






   return self._get_dummy_components()


  def 							SCREAMING_SNAKE_CASE__			(						self    :	Tuple						,		_UpperCAmelCase    :	Any						,		_UpperCAmelCase    :	Any=0 ):






   """simple docstring"""






   if str(_UpperCAmelCase ).startswith("""mps""" ):
    UpperCAmelCase__										=    torch.manual_seed(_UpperCAmelCase )
   else:
    UpperCAmelCase__										=    torch.Generator(device=_UpperCAmelCase ).manual_seed(_UpperCAmelCase )

   UpperCAmelCase__										=    floats_tensor((1, 3, 32, 32)						,		rng=random.Random(_UpperCAmelCase ) ).to(_UpperCAmelCase )

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

   return inputs


  def 							SCREAMING_SNAKE_CASE__			(						self    :	List[Any] ):






   """simple docstring"""






   self._test_save_load_optional_components()


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






   """simple docstring"""






   self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3 )


  @unittest.skipIf(torch_device != """cuda"""						,		reason="""float16 requires CUDA""" )
  def 							SCREAMING_SNAKE_CASE__			(						self    :	int ):






   """simple docstring"""






   super().test_save_load_floataa(expected_max_diff=1E-1 )


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






   """simple docstring"""






   super().test_floataa_inference(expected_max_diff=1E-1 )


  def 							SCREAMING_SNAKE_CASE__			(						self    :	List[str] ):






   """simple docstring"""






   self._test_attention_slicing_forward_pass(expected_max_diff=1E-2 )


  def 							SCREAMING_SNAKE_CASE__			(						self    :	int ):






   """simple docstring"""






   self._test_save_load_local()



  def 							SCREAMING_SNAKE_CASE__			(						self    :	Any ):






   """simple docstring"""






   self._test_inference_batch_single_identical(
       expected_max_diff=1E-2						,		)
