






"""simple docstring"""
import random

def 							snake_case (  A__      ,A__		):
			UpperCAmelCase_	,      UpperCAmelCase_	,      UpperCAmelCase_	:					List[str]     	=   [], [], []
			for element in data:
						if element < pivot:
									less.append(A__		)
						elif element > pivot:
									greater.append(A__		)
						else:
									equal.append(A__		)
			return less, equal, greater




def 							snake_case (  A__      ,A__		):
			# index = len(items) // 2 when trying to find the median
			#   (value of index when items is sorted)

			# invalid input
			if index >= len(A__		) or index < 0:
						return None

			UpperCAmelCase_	:					str     	=   items[random.randint(0      ,len(A__		) - 1		)]
			UpperCAmelCase_	:					Dict     	=   0
			UpperCAmelCase_	,      UpperCAmelCase_	,      UpperCAmelCase_	:					List[Any]     	=   _partition(A__      ,A__		)
			UpperCAmelCase_	:					Tuple     	=   len(A__		)
			UpperCAmelCase_	:					List[str]     	=   len(A__		)

			# index is the pivot
			if m <= index < m + count:
						return pivot
			# must be in smaller
			elif m > index:
						return quick_select(A__      ,A__		)
			# must be in larger
			else:
						return quick_select(A__      ,index - (m + count)		)






a_      =     frozenset(
    [
        'prompt',
        'height',
        'width',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
        'cross_attention_kwargs',
    ]
)

a_      =     frozenset(['prompt', 'negative_prompt'])

a_      =     frozenset([])

a_      =     frozenset(['image'])

a_      =     frozenset(
    [
        'image',
        'height',
        'width',
        'guidance_scale',
    ]
)

a_      =     frozenset(['image'])

a_      =     frozenset(
    [
        'prompt',
        'image',
        'height',
        'width',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
    ]
)

a_      =     frozenset(['prompt', 'image', 'negative_prompt'])

a_      =     frozenset(
    [
        # Text guided image variation with an image mask
        'prompt',
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
    ]
)

a_      =     frozenset(['prompt', 'image', 'mask_image', 'negative_prompt'])

a_      =     frozenset(
    [
        # image variation with an image mask
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
    ]
)

a_      =     frozenset(['image', 'mask_image'])

a_      =     frozenset(
    [
        'example_image',
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
    ]
)

a_      =     frozenset(['example_image', 'image', 'mask_image'])

a_      =     frozenset(['class_labels'])

a_      =     frozenset(['class_labels'])

a_      =     frozenset(['batch_size'])

a_      =     frozenset([])

a_      =     frozenset(['batch_size'])

a_      =     frozenset([])

a_      =     frozenset(
    [
        'prompt',
        'audio_length_in_s',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
        'cross_attention_kwargs',
    ]
)

a_      =     frozenset(['prompt', 'negative_prompt'])
a_      =     frozenset(['input_tokens'])

a_      =     frozenset(['input_tokens'])