





import argparse

import intel_extension_for_pytorch as ipex
import torch

from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline


A       :   Union[str, Any]					= 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''')
A       :   List[Any]					= parser.parse_args()


A       :   List[str]					= '''cpu'''
A       :   Optional[Any]					= '''a lovely <dicoo> in red dress and hat, in the snowly and brightly night, with many brighly buildings'''

A       :   List[str]					= '''path-to-your-trained-model'''
A       :   Union[str, Any]					= StableDiffusionPipeline.from_pretrained(model_id)
if args.dpm:
					A       :   List[str]					= DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
A       :   List[str]					= pipe.to(device)

# to channels last
A       :   Tuple					= pipe.unet.to(memory_format=torch.channels_last)
A       :   Any					= pipe.vae.to(memory_format=torch.channels_last)
A       :   List[str]					= pipe.text_encoder.to(memory_format=torch.channels_last)
if pipe.requires_safety_checker:
					A       :   Any					= pipe.safety_checker.to(memory_format=torch.channels_last)

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

# compute
A       :   List[str]					= 6_6_6
A       :   List[str]					= torch.Generator(device).manual_seed(seed)
A       :   str					= {'''generator''': generator}
if args.steps is not None:
					A       :   str					= args.steps

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

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










def   __lowerCamelCase   (				__a  :Dict       )						->							Optional[int]:






		"""simple docstring"""

		A__     =  []
		A__     =  []
		A__     =  {
		    """^""": 3,
		    """*""": 2,
		    """/""": 2,
		    """%""": 2,
		    """+""": 1,
		    """-""": 1,
		}  # Priority of each operator
		A__     =  len(__a       ) if (len(__a       ) > 7) else 7

		# Print table header for output
		print(
		    """Symbol""".center(8       )       ,	"""Stack""".center(__a       )       ,	"""Postfix""".center(__a       )       ,	sep=""" | """       ,	)
		print("""-""" * (print_width * 3 + 7)       )

		for x in infix:
				if x.isalpha() or x.isdigit():
						post_fix.append(__a       )  # if x is Alphabet / Digit, add it to Postfix
				elif x == "(":
						stack.append(__a       )  # if x is "(" push to Stack
				elif x == ")":  # if x is ")" pop stack until "(" is encountered
						while stack[-1] != "(":
								post_fix.append(stack.pop()       )  # Pop stack & add the content to Postfix
						stack.pop()
				else:
						if len(__a       ) == 0:
								stack.append(__a       )  # If stack is empty, push x to stack
						else:  # while priority of x is not > priority of element in the stack
								while len(__a       ) > 0 and priority[x] <= priority[stack[-1]]:
										post_fix.append(stack.pop()       )  # pop stack & add to Postfix
								stack.append(__a       )  # push x to stack

				print(
				    x.center(8       )       ,	("""""".join(__a       )).ljust(__a       )       ,	("""""".join(__a       )).ljust(__a       )       ,	sep=""" | """       ,	)  # Output in tabular format

		while len(__a       ) > 0:  # while stack is not empty
				post_fix.append(stack.pop()       )  # pop stack & add to Postfix
				print(
				    """ """.center(8       )       ,	("""""".join(__a       )).ljust(__a       )       ,	("""""".join(__a       )).ljust(__a       )       ,	sep=""" | """       ,	)  # Output in tabular format

		return "".join(__a       )  # return Postfix as str







def   __lowerCamelCase   (				__a  :List[str]       )						->							Union[str, Any]:






		"""simple docstring"""

		A__     =  list(infix[::-1]       )  # reverse the infix equation

		for i in range(len(__a       )       ):
				if infix[i] == "(":
						A__     =  """)"""  # change "(" to ")"
				elif infix[i] == ")":
						A__     =  """("""  # change ")" to "("

		return (infix_2_postfix("""""".join(__a       )       ))[
		    ::-1
		]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
					A       :   Union[str, Any]					= input('''\nEnter an Infix Equation = ''')  # Input an Infix equation
					A       :   Dict					= ''''''.join(Infix.split())  # Remove spaces from the input
					print('''\n\t''', Infix, '''(Infix) -> ''', infix_2_prefix(Infix), '''(Prefix)''')



