



import argparse

import intel_extension_for_pytorch as ipex
import torch

from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline


snake_case__					:     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""")
snake_case__					:     str    		=   parser.parse_args()


snake_case__					:     int    		=   """cpu"""
snake_case__					:     Optional[int]    		=   """a lovely <dicoo> in red dress and hat, in the snowly and brightly night, with many brighly buildings"""

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

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

# optimize with ipex
snake_case__					:     List[Any]    		=   torch.randn(2, 4, 64, 64)
snake_case__					:     Optional[int]    		=   torch.rand(1) * 9_99
snake_case__					:     str    		=   torch.randn(2, 77, 7_68)
snake_case__					:     List[Any]    		=   (sample, timestep, encoder_hidden_status)
try:
		snake_case__					:     List[str]    		=   ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True, sample_input=input_example)
except Exception:
		snake_case__					:     Optional[int]    		=   ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True)
snake_case__					:     Dict    		=   ipex.optimize(pipe.vae.eval(), dtype=torch.bfloataa, inplace=True)
snake_case__					:     str    		=   ipex.optimize(pipe.text_encoder.eval(), dtype=torch.bfloataa, inplace=True)
if pipe.requires_safety_checker:
		snake_case__					:     Union[str, Any]    		=   ipex.optimize(pipe.safety_checker.eval(), dtype=torch.bfloataa, inplace=True)

# compute
snake_case__					:     Dict    		=   6_66
snake_case__					:     List[str]    		=   torch.Generator(device).manual_seed(seed)
snake_case__					:     int    		=   {"""generator""": generator}
if args.steps is not None:
		snake_case__					:     Optional[int]    		=   args.steps

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

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








from __future__ import annotations

from typing import Any

class   _A   :


						'''simple docstring'''





						def __init__(	self	:							Union[str, Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							__lowercase		       =			num_of_nodes
							__lowercase		       =			[]
							__lowercase		       =			{}



						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							self.m_edges.append([u_node, v_node, weight]	)



						def     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if self.m_component[u_node] == u_node:
								return u_node
							return self.find_component(self.m_component[u_node]	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if self.m_component[u_node] != u_node:
								for k in self.m_component:
									__lowercase		       =			self.find_component(lowerCamelCase	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							list[int]							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if component_size[u_node] <= component_size[v_node]:
								__lowercase		       =			v_node
								component_size[v_node] += component_size[u_node]
								self.set_component(lowerCamelCase	)

							elif component_size[u_node] >= component_size[v_node]:
								__lowercase		       =			self.find_component(lowerCamelCase	)
								component_size[u_node] += component_size[v_node]
								self.set_component(lowerCamelCase	)



						def     _snake_case	(	self	:							Any	):






							'''simple docstring'''



							__lowercase		       =			[]
							__lowercase		       =			0

							__lowercase		       =			[-1] * self.m_num_of_nodes

							# A list of components (initialized to all of the nodes)
							for node in range(self.m_num_of_nodes	):
								self.m_component.update({node: node}	)
								component_size.append(1	)

							__lowercase		       =			self.m_num_of_nodes

							while num_of_components > 1:
								for edge in self.m_edges:
									__lowercase       ,    __lowercase       ,    __lowercase		       =			edge

									__lowercase		       =			self.m_component[u]
									__lowercase		       =			self.m_component[v]

									if u_component != v_component:

										for component in (u_component, v_component):
											if (
											    minimum_weight_edge[component] == -1
											    or minimum_weight_edge[component][2] > w
											):
												__lowercase		       =			[u, v, w]

								for edge in minimum_weight_edge:
									if isinstance(lowerCamelCase							,      lowerCamelCase	):
										__lowercase       ,    __lowercase       ,    __lowercase		       =			edge

										__lowercase		       =			self.m_component[u]
										__lowercase		       =			self.m_component[v]

										if u_component != v_component:
											mst_weight += w
											self.union(lowerCamelCase							,      lowerCamelCase							,      lowerCamelCase	)
											print(f"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""	)
											num_of_components -= 1

								__lowercase		       =			[-1] * self.m_num_of_nodes
							print(f"""The total weight of the minimal spanning tree is: {mst_weight}"""	)



def    snake_case_				(    ):
	pass


if __name__ == "__main__":
	import doctest

	doctest.testmod()



