





import argparse
import os
from io import BytesIO
from pathlib import Path

import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				):
	snake_case_						:     Tuple     =		1.5
	snake_case_						:     Optional[Any]     =		int(factor * num_class_images				)
	snake_case_						:     str     =		ClipClient(
	    url='https://knn.laion.ai/knn-service'				,	indice_name='laion_400m'				,	num_images=__a				,	aesthetic_weight=0.1				)

	os.makedirs(f"""{class_data_dir}/images"""				,	exist_ok=__a				)
	if len(list(Path(f"""{class_data_dir}/images"""				).iterdir()				)				) >= num_class_images:
		return

	while True:
		snake_case_						:     Dict     =		client.query(text=__a				)
		if len(__a				) >= factor * num_class_images or num_images > 1E4:
			break
		else:
			snake_case_						:     Optional[Any]     =		int(factor * num_images				)
			snake_case_						:     Optional[Any]     =		ClipClient(
			    url='https://knn.laion.ai/knn-service'				,	indice_name='laion_400m'				,	num_images=__a				,	aesthetic_weight=0.1				,	)

	snake_case_						:     List[str]     =		0
	snake_case_						:     Tuple     =		0
	snake_case_						:     Any     =		tqdm(desc='downloading real regularization images'				,	total=__a				)

	with open(f"""{class_data_dir}/caption.txt"""				,	'w'				) as fa, open(f"""{class_data_dir}/urls.txt"""				,	'w'				) as fa, open(
	    f"""{class_data_dir}/images.txt"""				,	'w'				) as fa:
		while total < num_class_images:
			snake_case_						:     List[Any]     =		class_images[count]
			count += 1
			try:
				snake_case_						:     Union[str, Any]     =		requests.get(images['url']				)
				if img.status_code == 2_00:
					snake_case_						:     int     =		Image.open(BytesIO(img.content				)				)
					with open(f"""{class_data_dir}/images/{total}.jpg"""				,	'wb'				) as f:
						f.write(img.content				)
					fa.write(images['caption'] + '\n'				)
					fa.write(images['url'] + '\n'				)
					fa.write(f"""{class_data_dir}/images/{total}.jpg""" + '\n'				)
					total += 1
					pbar.update(1				)
				else:
					continue
			except Exception:
				continue
	return


def 							SCREAMING_SNAKE_CASE__  (      ):
	snake_case_						:     List[str]     =		argparse.ArgumentParser(''				,	add_help=__a				)
	parser.add_argument('--class_prompt'				,	help='text prompt to retrieve images'				,	required=__a				,	type=__a				)
	parser.add_argument('--class_data_dir'				,	help='path to save images'				,	required=__a				,	type=__a				)
	parser.add_argument('--num_class_images'				,	help='number of images to download'				,	default=2_00				,	type=__a				)
	return parser.parse_args()


if __name__ == "__main__":
						_SCREAMING_SNAKE_CASE 		=						parse_args()
						retrieve(args.class_prompt, args.class_data_dir, args.num_class_images)








from __future__ import annotations

import pandas as pd


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				):
	snake_case_						:     Optional[Any]     =		[0] * no_of_processes
	snake_case_						:     Tuple     =		[0] * no_of_processes
	# Copy the burst time into remaining_time[]
	for i in range(__a				):
		snake_case_						:     Union[str, Any]     =		burst_time[i]

	snake_case_						:     Optional[Any]     =		0
	snake_case_						:     Dict     =		0
	snake_case_						:     Any     =		9_99_99_99_99
	snake_case_						:     Tuple     =		0
	snake_case_						:     List[Any]     =		False

	# Process until all processes are completed
	while complete != no_of_processes:
		for j in range(__a				):
			if arrival_time[j] <= increment_time and remaining_time[j] > 0:
				if remaining_time[j] < minm:
					snake_case_						:     str     =		remaining_time[j]
					snake_case_						:     Any     =		j
					snake_case_						:     List[str]     =		True

		if not check:
			increment_time += 1
			continue
		remaining_time[short] -= 1

		snake_case_						:     Any     =		remaining_time[short]
		if minm == 0:
			snake_case_						:     Dict     =		9_99_99_99_99

		if remaining_time[short] == 0:
			complete += 1
			snake_case_						:     List[str]     =		False

			# Find finish time of current process
			snake_case_						:     List[str]     =		increment_time + 1

			# Calculate waiting time
			snake_case_						:     Any     =		finish_time - arrival_time[short]
			snake_case_						:     Any     =		finar - burst_time[short]

			if waiting_time[short] < 0:
				snake_case_						:     Optional[int]     =		0

        # Increment time
		increment_time += 1
	return waiting_time


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				):
	snake_case_						:     Tuple     =		[0] * no_of_processes
	for i in range(__a				):
		snake_case_						:     str     =		burst_time[i] + waiting_time[i]
	return turn_around_time


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				):
	snake_case_						:     int     =		0
	snake_case_						:     Optional[Any]     =		0
	for i in range(__a				):
		snake_case_						:     int     =		total_waiting_time + waiting_time[i]
		snake_case_						:     Optional[Any]     =		total_turn_around_time + turn_around_time[i]
	print(f"""Average waiting time = {total_waiting_time / no_of_processes:.5f}"""				)
	print('Average turn around time ='				,	total_turn_around_time / no_of_processes				)


if __name__ == "__main__":
						print("""Enter how many process you want to analyze""")
						_SCREAMING_SNAKE_CASE 		=						int(input())
						_SCREAMING_SNAKE_CASE 		=						[0] * no_of_processes
						_SCREAMING_SNAKE_CASE 		=						[0] * no_of_processes
						_SCREAMING_SNAKE_CASE 		=						list(range(1, no_of_processes + 1))

						for i in range(no_of_processes):
												print("""Enter the arrival time and burst time for process:--""" + str(i + 1))
												_SCREAMING_SNAKE_CASE		,							_SCREAMING_SNAKE_CASE 		=						map(int, input().split())

						_SCREAMING_SNAKE_CASE 		=						calculate_waitingtime(arrival_time, burst_time, no_of_processes)

						_SCREAMING_SNAKE_CASE 		=						burst_time
						_SCREAMING_SNAKE_CASE 		=						no_of_processes
						_SCREAMING_SNAKE_CASE 		=						waiting_time
						_SCREAMING_SNAKE_CASE 		=						calculate_turnaroundtime(bt, n, wt)

						calculate_average_times(waiting_time, turn_around_time, no_of_processes)

						_SCREAMING_SNAKE_CASE 		=						pd.DataFrame(
						    list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
						    columns=[
						        """Process""",
						        """BurstTime""",
						        """ArrivalTime""",
						        """WaitingTime""",
						        """TurnAroundTime""",
						    ],
						)

						# Printing the dataFrame
						pd.set_option("""display.max_rows""", fcfs.shape[0] + 1)
						print(fcfs)

