



"""simple docstring"""


import argparse

import torch
from safetensors.torch import load_file

from diffusers import StableDiffusionPipeline

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_		,     lowercase_		,     lowercase_		,     lowercase_						):
							# load base model
							UpperCAmelCase					=			StableDiffusionPipeline.from_pretrained(lowercase_		,     torch_dtype=torch.floataa						)

							# load LoRA weight from .safetensors
							UpperCAmelCase					=			load_file(lowercase_						)

							UpperCAmelCase					=			[]

							# directly update weight in diffusers model
							for key in state_dict:
														# it is suggested to print out the key, it usually will be something like below
														# "lora_te_text_model_encoder_layers_0_self_attn_k_proj.lora_down.weight"

														# as we have set the alpha beforehand, so just skip
														if ".alpha" in key or key in visited:
																					continue

														if "text" in key:
																					UpperCAmelCase					=			key.split('.'						)[0].split(LORA_PREFIX_TEXT_ENCODER + '_'						)[-1].split('_'						)
																					UpperCAmelCase					=			pipeline.text_encoder
														else:
																					UpperCAmelCase					=			key.split('.'						)[0].split(LORA_PREFIX_UNET + '_'						)[-1].split('_'						)
																					UpperCAmelCase					=			pipeline.unet

														# find the target layer
														UpperCAmelCase					=			layer_infos.pop(0						)
														while len(lowercase_						) > -1:
																					try:
																												UpperCAmelCase					=			curr_layer.__getattr__(lowercase_						)
																												if len(lowercase_						) > 0:
																																			UpperCAmelCase					=			layer_infos.pop(0						)
																												elif len(lowercase_						) == 0:
																																			break
																					except Exception:
																												if len(lowercase_						) > 0:
																																			temp_name += "_" + layer_infos.pop(0						)
																												else:
																																			UpperCAmelCase					=			layer_infos.pop(0						)

														UpperCAmelCase					=			[]
														if "lora_down" in key:
																					pair_keys.append(key.replace('lora_down'		,     'lora_up'						)						)
																					pair_keys.append(lowercase_						)
														else:
																					pair_keys.append(lowercase_						)
																					pair_keys.append(key.replace('lora_up'		,     'lora_down'						)						)

														# update weight
														if len(state_dict[pair_keys[0]].shape						) == 4:
																					UpperCAmelCase					=			state_dict[pair_keys[0]].squeeze(3						).squeeze(2						).to(torch.floataa						)
																					UpperCAmelCase					=			state_dict[pair_keys[1]].squeeze(3						).squeeze(2						).to(torch.floataa						)
																					curr_layer.weight.data += alpha * torch.mm(lowercase_		,     lowercase_						).unsqueeze(2						).unsqueeze(3						)
														else:
																					UpperCAmelCase					=			state_dict[pair_keys[0]].to(torch.floataa						)
																					UpperCAmelCase					=			state_dict[pair_keys[1]].to(torch.floataa						)
																					curr_layer.weight.data += alpha * torch.mm(lowercase_		,     lowercase_						)

														# update visited list
														for item in pair_keys:
																					visited.append(lowercase_						)

							return pipeline


if __name__ == "__main__":
				snake_case_    					=	argparse.ArgumentParser()

				parser.add_argument(
				    """--base_model_path""", default=None, type=str, required=True, help="""Path to the base model in diffusers format."""
				)
				parser.add_argument(
				    """--checkpoint_path""", default=None, type=str, required=True, help="""Path to the checkpoint to convert."""
				)
				parser.add_argument("""--dump_path""", default=None, type=str, required=True, help="""Path to the output model.""")
				parser.add_argument(
				    """--lora_prefix_unet""", default="""lora_unet""", type=str, help="""The prefix of UNet weight in safetensors"""
				)
				parser.add_argument(
				    """--lora_prefix_text_encoder""",
				    default="""lora_te""",
				    type=str,
				    help="""The prefix of text encoder weight in safetensors""",
				)
				parser.add_argument("""--alpha""", default=0.75, type=float, help="""The merging ratio in W = W0 + alpha * deltaW""")
				parser.add_argument(
				    """--to_safetensors""", action="""store_true""", help="""Whether to store pipeline in safetensors format or not."""
				)
				parser.add_argument("""--device""", type=str, help="""Device to use (e.g. cpu, cuda:0, cuda:1, etc.)""")

				snake_case_    					=	parser.parse_args()

				snake_case_    					=	args.base_model_path
				snake_case_    					=	args.checkpoint_path
				snake_case_    					=	args.dump_path
				snake_case_    					=	args.lora_prefix_unet
				snake_case_    					=	args.lora_prefix_text_encoder
				snake_case_    					=	args.alpha

				snake_case_    					=	convert(base_model_path, checkpoint_path, lora_prefix_unet, lora_prefix_text_encoder, alpha)

				snake_case_    					=	pipe.to(args.device)
				pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)










"""simple docstring"""


from collections import deque







class 				A_      :



						"""simple docstring"""






						def __init__( self			:Any       ,  lowercase_			:str       ,  lowercase_			:int       ,  lowercase_			:int )    ->      None:
												UpperCAmelCase					=			process_name  # process name
												UpperCAmelCase					=			arrival_time  # arrival time of the process
												# completion time of finished process or last interrupted time
												UpperCAmelCase					=			arrival_time
												UpperCAmelCase					=			burst_time  # remaining burst time
												UpperCAmelCase					=			0  # total time of the process wait in ready queue
												UpperCAmelCase					=			0  # time from arrival time to completion time







class 				A_      :



						"""simple docstring"""






						def __init__( self			:Any       ,  lowercase_			:int       ,  lowercase_			:list[int]       ,  lowercase_			:deque[Process]       ,  lowercase_			:int       ,  )    ->      None:
												# total number of mlfq's queues
												UpperCAmelCase					=			number_of_queues
												# time slice of queues that round robin algorithm applied
												UpperCAmelCase					=			time_slices
												# unfinished process is in this ready_queue
												UpperCAmelCase					=			queue
												# current time
												UpperCAmelCase					=			current_time
												# finished process is in this sequence queue
												UpperCAmelCase					=			deque()






						def      UpperCAmelCase__					( self			:Optional[int] )    ->      list[str]:
												UpperCAmelCase					=			[]
												for i in range(len(self.finish_queue ) ):
																		sequence.append(self.finish_queue[i].process_name )
												return sequence






						def      UpperCAmelCase__					( self			:List[str]       ,  lowercase_			:list[Process] )    ->      list[int]:
												UpperCAmelCase					=			[]
												for i in range(len(lowercase_ ) ):
																		waiting_times.append(queue[i].waiting_time )
												return waiting_times






						def      UpperCAmelCase__					( self			:List[str]       ,  lowercase_			:list[Process] )    ->      list[int]:
												UpperCAmelCase					=			[]
												for i in range(len(lowercase_ ) ):
																		turnaround_times.append(queue[i].turnaround_time )
												return turnaround_times






						def      UpperCAmelCase__					( self			:Dict       ,  lowercase_			:list[Process] )    ->      list[int]:
												UpperCAmelCase					=			[]
												for i in range(len(lowercase_ ) ):
																		completion_times.append(queue[i].stop_time )
												return completion_times






						def      UpperCAmelCase__					( self			:str       ,  lowercase_			:deque[Process] )    ->      list[int]:
												return [q.burst_time for q in queue]






						def      UpperCAmelCase__					( self			:int       ,  lowercase_			:Process )    ->      int:
												process.waiting_time += self.current_time - process.stop_time
												return process.waiting_time






						def      UpperCAmelCase__					( self			:Optional[int]       ,  lowercase_			:deque[Process] )    ->      deque[Process]:
												UpperCAmelCase					=			deque()  # sequence deque of finished process
												while len(lowercase_ ) != 0:
																		UpperCAmelCase					=			ready_queue.popleft()  # current process

																		# if process's arrival time is later than current time, update current time
																		if self.current_time < cp.arrival_time:
																								self.current_time += cp.arrival_time

																		# update waiting time of current process
																		self.update_waiting_time(lowercase_ )
																		# update current time
																		self.current_time += cp.burst_time
																		# finish the process and set the process's burst-time 0
																		UpperCAmelCase					=			0
																		# set the process's turnaround time because it is finished
																		UpperCAmelCase					=			self.current_time - cp.arrival_time
																		# set the completion time
																		UpperCAmelCase					=			self.current_time
																		# add the process to queue that has finished queue
																		finished.append(lowercase_ )

												self.finish_queue.extend(lowercase_ )  # add finished process to finish queue
												# FCFS will finish all remaining processes
												return finished






						def      UpperCAmelCase__					( self			:Tuple       ,  lowercase_			:deque[Process]       ,  lowercase_			:int )    ->      tuple[deque[Process], deque[Process]]:
												UpperCAmelCase					=			deque()  # sequence deque of terminated process
												# just for 1 cycle and unfinished processes will go back to queue
												for _ in range(len(lowercase_ ) ):
																		UpperCAmelCase					=			ready_queue.popleft()  # current process

																		# if process's arrival time is later than current time, update current time
																		if self.current_time < cp.arrival_time:
																								self.current_time += cp.arrival_time

																		# update waiting time of unfinished processes
																		self.update_waiting_time(lowercase_ )
																		# if the burst time of process is bigger than time-slice
																		if cp.burst_time > time_slice:
																								# use CPU for only time-slice
																								self.current_time += time_slice
																								# update remaining burst time
																								cp.burst_time -= time_slice
																								# update end point time
																								UpperCAmelCase					=			self.current_time
																								# locate the process behind the queue because it is not finished
																								ready_queue.append(lowercase_ )
																		else:
																								# use CPU for remaining burst time
																								self.current_time += cp.burst_time
																								# set burst time 0 because the process is finished
																								UpperCAmelCase					=			0
																								# set the finish time
																								UpperCAmelCase					=			self.current_time
																								# update the process' turnaround time because it is finished
																								UpperCAmelCase					=			self.current_time - cp.arrival_time
																								# add the process to queue that has finished queue
																								finished.append(lowercase_ )

												self.finish_queue.extend(lowercase_ )  # add finished process to finish queue
												# return finished processes queue and remaining processes queue
												return finished, ready_queue






						def      UpperCAmelCase__					( self			:Optional[Any] )    ->      deque[Process]:

												#  all queues except last one have round_robin algorithm
												for i in range(self.number_of_queues - 1 ):
																		UpperCAmelCase				,   UpperCAmelCase					=			self.round_robin(
																		    self.ready_queue       ,  self.time_slices[i] )
												#  the last queue has first_come_first_served algorithm
												self.first_come_first_served(self.ready_queue )

												return self.finish_queue


if __name__ == "__main__":
				import doctest

				snake_case_    					=	Process("""P1""", 0, 53)
				snake_case_    					=	Process("""P2""", 0, 17)
				snake_case_    					=	Process("""P3""", 0, 68)
				snake_case_    					=	Process("""P4""", 0, 24)
				snake_case_    					=	3
				snake_case_    					=	[17, 25]
				snake_case_    					=	deque([Pa, Pa, Pa, Pa])

				if len(time_slices) != number_of_queues - 1:
								raise SystemExit(0)

				doctest.testmod(extraglobs={"""queue""": deque([Pa, Pa, Pa, Pa])})

				snake_case_    					=	Process("""P1""", 0, 53)
				snake_case_    					=	Process("""P2""", 0, 17)
				snake_case_    					=	Process("""P3""", 0, 68)
				snake_case_    					=	Process("""P4""", 0, 24)
				snake_case_    					=	3
				snake_case_    					=	[17, 25]
				snake_case_    					=	deque([Pa, Pa, Pa, Pa])
				snake_case_    					=	MLFQ(number_of_queues, time_slices, queue, 0)
				snake_case_    					=	mlfq.multi_level_feedback_queue()

				# print total waiting times of processes(P1, P2, P3, P4)
				print(
				    f'''waiting time:\
        \t\t\t{MLFQ.calculate_waiting_time(mlfq, [Pa, Pa, Pa, Pa])}'''
				)
				# print completion times of processes(P1, P2, P3, P4)
				print(
				    f'''completion time:\
        \t\t{MLFQ.calculate_completion_time(mlfq, [Pa, Pa, Pa, Pa])}'''
				)
				# print total turnaround times of processes(P1, P2, P3, P4)
				print(
				    f'''turnaround time:\
        \t\t{MLFQ.calculate_turnaround_time(mlfq, [Pa, Pa, Pa, Pa])}'''
				)
				# print sequence of finished processes
				print(
				    f'''sequence of finished processes:\
        {mlfq.calculate_sequence_of_finish_queue()}'''
				)





