


'''simple docstring'''

import argparse

import intel_extension_for_pytorch as ipex
import torch

from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline


lowerCAmelCase				:Optional[int]        =      argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm''', action='''store_true''', help='''Enable DPMSolver or not''')
parser.add_argument('''--steps''', default=None, type=int, help='''Num inference steps''')
lowerCAmelCase				:Optional[int]        =      parser.parse_args()


lowerCAmelCase				:Union[str, Any]        =      "cpu"
lowerCAmelCase				:Dict        =      "a lovely <dicoo> in red dress and hat, in the snowly and brightly night, with many brighly buildings"

lowerCAmelCase				:int        =      "path-to-your-trained-model"
lowerCAmelCase				:List[str]        =      StableDiffusionPipeline.from_pretrained(model_id)
if args.dpm:
							lowerCAmelCase				:Optional[Any]        =      DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
lowerCAmelCase				:Optional[Any]        =      pipe.to(device)

# to channels last
lowerCAmelCase				:Tuple        =      pipe.unet.to(memory_format=torch.channels_last)
lowerCAmelCase				:Optional[int]        =      pipe.vae.to(memory_format=torch.channels_last)
lowerCAmelCase				:int        =      pipe.text_encoder.to(memory_format=torch.channels_last)
if pipe.requires_safety_checker:
							lowerCAmelCase				:Tuple        =      pipe.safety_checker.to(memory_format=torch.channels_last)

# optimize with ipex
lowerCAmelCase				:Tuple        =      torch.randn(2, 4, 6_4, 6_4)
lowerCAmelCase				:Any        =      torch.rand(1) * 9_9_9
lowerCAmelCase				:Any        =      torch.randn(2, 7_7, 7_6_8)
lowerCAmelCase				:List[Any]        =      (sample, timestep, encoder_hidden_status)
try:
							lowerCAmelCase				:Union[str, Any]        =      ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True, sample_input=input_example)
except Exception:
							lowerCAmelCase				:str        =      ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True)
lowerCAmelCase				:Tuple        =      ipex.optimize(pipe.vae.eval(), dtype=torch.bfloataa, inplace=True)
lowerCAmelCase				:str        =      ipex.optimize(pipe.text_encoder.eval(), dtype=torch.bfloataa, inplace=True)
if pipe.requires_safety_checker:
							lowerCAmelCase				:List[Any]        =      ipex.optimize(pipe.safety_checker.eval(), dtype=torch.bfloataa, inplace=True)

# compute
lowerCAmelCase				:Optional[Any]        =      6_6_6
lowerCAmelCase				:int        =      torch.Generator(device).manual_seed(seed)
lowerCAmelCase				:int        =      {"generator": generator}
if args.steps is not None:
							lowerCAmelCase				:str        =      args.steps

with torch.cpu.amp.autocast(enabled=True, dtype=torch.bfloataa):
							lowerCAmelCase				:str        =      pipe(prompt, **generate_kwargs).images[0]

# save image
image.save('''generated.png''')



'''simple docstring'''

def lowerCamelCase      (      lowerCAmelCase    :     str		,		lowerCAmelCase    :     Any		,		lowerCAmelCase    :     Any=False		):





	"""simple docstring"""







	if isinstance(lowerCAmelCase		,		lowerCAmelCase		) and isinstance(lowerCAmelCase		,		lowerCAmelCase		):
		__magic_name__	:   str					     =					len(set_a.intersection(lowerCAmelCase		)		)

		if alternative_union:
			__magic_name__	:   List[str]					     =					len(lowerCAmelCase		) + len(lowerCAmelCase		)
		else:
			__magic_name__	:   Any					     =					len(set_a.union(lowerCAmelCase		)		)

		return intersection / union

	if isinstance(lowerCAmelCase		,		(list, tuple)		) and isinstance(lowerCAmelCase		,		(list, tuple)		):
		__magic_name__	:   str					     =					[element for element in set_a if element in set_b]

		if alternative_union:
			__magic_name__	:   Dict					     =					len(lowerCAmelCase		) + len(lowerCAmelCase		)
			return len(lowerCAmelCase		) / union
		else:
			__magic_name__	:   Any					     =					set_a + [element for element in set_b if element not in set_a]
			return len(lowerCAmelCase		) / len(lowerCAmelCase		)

		return len(lowerCAmelCase		) / len(lowerCAmelCase		)
	return None


if __name__ == "__main__":
							lowerCAmelCase				:Dict        =      {'''a''', '''b''', '''c''', '''d''', '''e'''}
							lowerCAmelCase				:Tuple        =      {'''c''', '''d''', '''e''', '''f''', '''h''', '''i'''}
							print(jaccard_similarity(set_a, set_b))