


from collections import deque







class 	__lowercase    :





							"""simple docstring"""







							def __init__(      self			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     int					=					process_name  # process name
										SCREAMING_SNAKE_CASE_		:     str					=					arrival_time  # arrival time of the process
										# completion time of finished process or last interrupted time
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					arrival_time
										SCREAMING_SNAKE_CASE_		:     Tuple					=					burst_time  # remaining burst time
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					0  # total time of the process wait in ready queue
										SCREAMING_SNAKE_CASE_		:     Any					=					0  # time from arrival time to completion time







class 	__lowercase    :





							"""simple docstring"""







							def __init__(      self			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     str					=					number_of_queues
										# time slice of queues that round robin algorithm applied
										SCREAMING_SNAKE_CASE_		:     int					=					time_slices
										# unfinished process is in this ready_queue
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					queue
										# current time
										SCREAMING_SNAKE_CASE_		:     List[str]					=					current_time
										# finished process is in this sequence queue
										SCREAMING_SNAKE_CASE_		:     deque[Process]					=					deque()






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					[]
										for i in range(len(self.finish_queue       )       ):
													sequence.append(self.finish_queue[i].process_name       )
										return sequence






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					[]
										for i in range(len(lowerCAmelCase__       )       ):
													waiting_times.append(queue[i].waiting_time       )
										return waiting_times






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     List[str]					=					[]
										for i in range(len(lowerCAmelCase__       )       ):
													turnaround_times.append(queue[i].turnaround_time       )
										return turnaround_times






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					[]
										for i in range(len(lowerCAmelCase__       )       ):
													completion_times.append(queue[i].stop_time       )
										return completion_times






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										return [q.burst_time for q in queue]






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										process.waiting_time += self.current_time - process.stop_time
										return process.waiting_time






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     deque[Process]					=					deque()  # sequence deque of finished process
										while len(lowerCAmelCase__       ) != 0:
													SCREAMING_SNAKE_CASE_		:     Dict					=					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(lowerCAmelCase__       )
													# update current time
													self.current_time += cp.burst_time
													# finish the process and set the process's burst-time 0
													SCREAMING_SNAKE_CASE_		:     int					=					0
													# set the process's turnaround time because it is finished
													SCREAMING_SNAKE_CASE_		:     str					=					self.current_time - cp.arrival_time
													# set the completion time
													SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					self.current_time
													# add the process to queue that has finished queue
													finished.append(lowerCAmelCase__       )

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






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     deque[Process]					=					deque()  # sequence deque of terminated process
										# just for 1 cycle and unfinished processes will go back to queue
										for _ in range(len(lowerCAmelCase__       )       ):
													SCREAMING_SNAKE_CASE_		:     List[Any]					=					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(lowerCAmelCase__       )
													# 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
																SCREAMING_SNAKE_CASE_		:     Optional[int]					=					self.current_time
																# locate the process behind the queue because it is not finished
																ready_queue.append(lowerCAmelCase__       )
													else:
																# use CPU for remaining burst time
																self.current_time += cp.burst_time
																# set burst time 0 because the process is finished
																SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					0
																# set the finish time
																SCREAMING_SNAKE_CASE_		:     str					=					self.current_time
																# update the process' turnaround time because it is finished
																SCREAMING_SNAKE_CASE_		:     Any					=					self.current_time - cp.arrival_time
																# add the process to queue that has finished queue
																finished.append(lowerCAmelCase__       )

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






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										for i in range(self.number_of_queues - 1       ):
													SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					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

				lowerCAmelCase__			:      Tuple								=Process('P1', 0, 53)
				lowerCAmelCase__			:      str								=Process('P2', 0, 17)
				lowerCAmelCase__			:      int								=Process('P3', 0, 68)
				lowerCAmelCase__			:      List[Any]								=Process('P4', 0, 24)
				lowerCAmelCase__			:      Tuple								=3
				lowerCAmelCase__			:      Any								=[17, 25]
				lowerCAmelCase__			:      Tuple								=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])})

				lowerCAmelCase__			:      Optional[int]								=Process('P1', 0, 53)
				lowerCAmelCase__			:      List[str]								=Process('P2', 0, 17)
				lowerCAmelCase__			:      List[Any]								=Process('P3', 0, 68)
				lowerCAmelCase__			:      Optional[int]								=Process('P4', 0, 24)
				lowerCAmelCase__			:      List[Any]								=3
				lowerCAmelCase__			:      Optional[int]								=[17, 25]
				lowerCAmelCase__			:      Optional[int]								=deque([Pa, Pa, Pa, Pa])
				lowerCAmelCase__			:      List[Any]								=MLFQ(number_of_queues, time_slices, queue, 0)
				lowerCAmelCase__			:      Tuple								=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()}"""
				)









import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__			:      Optional[int]								=0B1011_0011_1110_1100_1001_0000_0111_1011_1011_0001_1001_1110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
lowerCAmelCase__			:      str								=[int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]







class 	__lowercase    :





							"""simple docstring"""







							def __init__(      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     List[Any]					=					WATERMARK_BITS
										SCREAMING_SNAKE_CASE_		:     int					=					WatermarkEncoder()

										self.encoder.set_watermark('bits'			,						self.watermark       )






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										if images.shape[-1] < 2_5_6:
													return images

										SCREAMING_SNAKE_CASE_		:     Tuple					=					(2_5_5 * (images / 2 + 0.5)).cpu().permute(0			,						2			,						3			,						1       ).float().numpy()

										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					[self.encoder.encode(lowerCAmelCase__			,						'dwtDct'       ) for image in images]

										SCREAMING_SNAKE_CASE_		:     List[str]					=					torch.from_numpy(np.array(lowerCAmelCase__       )       ).permute(0			,						3			,						1			,						2       )

										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					torch.clamp(2 * (images / 2_5_5 - 0.5)			,						min=-1.0			,						max=1.0       )
										return images





