

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

A_	:			Union[str, Any]  	=      frozenset(['prompt', 'negative_prompt'])

A_	:			Optional[int]  	=      frozenset([])

A_	:			Any  	=      frozenset(['image'])

A_	:			int  	=      frozenset(
    [
        'image',
        'height',
        'width',
        'guidance_scale',
    ]
)

A_	:			List[Any]  	=      frozenset(['image'])

A_	:			Optional[Any]  	=      frozenset(
    [
        'prompt',
        'image',
        'height',
        'width',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
    ]
)

A_	:			int  	=      frozenset(['prompt', 'image', 'negative_prompt'])

A_	:			List[Any]  	=      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_	:			Tuple  	=      frozenset(['prompt', 'image', 'mask_image', 'negative_prompt'])

A_	:			Union[str, Any]  	=      frozenset(
    [
        # image variation with an image mask
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
    ]
)

A_	:			Dict  	=      frozenset(['image', 'mask_image'])

A_	:			List[Any]  	=      frozenset(
    [
        'example_image',
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
    ]
)

A_	:			List[Any]  	=      frozenset(['example_image', 'image', 'mask_image'])

A_	:			str  	=      frozenset(['class_labels'])

A_	:			List[Any]  	=      frozenset(['class_labels'])

A_	:			List[str]  	=      frozenset(['batch_size'])

A_	:			Optional[Any]  	=      frozenset([])

A_	:			str  	=      frozenset(['batch_size'])

A_	:			Optional[int]  	=      frozenset([])

A_	:			Optional[int]  	=      frozenset(
    [
        'prompt',
        'audio_length_in_s',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
        'cross_attention_kwargs',
    ]
)

A_	:			List[str]  	=      frozenset(['prompt', 'negative_prompt'])
A_	:			int  	=      frozenset(['input_tokens'])

A_	:			Dict  	=      frozenset(['input_tokens'])






from __future__ import annotations

def 						UpperCamelCase (lowercase_:			list[int]   ,				lowercase_:			list[int]   ,				lowercase_:			int )					->				tuple[float, list[float]]:
	A__							:   Tuple					       =		list(range(len(lowercase_ ) ) )
	A__							:   Union[str, Any]					       =		[v / w for v, w in zip(lowercase_   ,				lowercase_ )]
	index.sort(key=lambda lowercase_ : ratio[i]   ,				reverse=lowercase_ )

	A__							:   float					       =		0
	A__							:   list[float]					       =		[0] * len(lowercase_ )
	for i in index:
		if weight[i] <= capacity:
			A__							:   Optional[int]					       =		1
			max_value += value[i]
			capacity -= weight[i]
		else:
			A__							:   Union[str, Any]					       =		capacity / weight[i]
			max_value += value[i] * capacity / weight[i]
			break

	return max_value, fractions


if __name__ == "__main__":
	import doctest

	doctest.testmod()



