





"""simple docstring"""



from statistics import mean

import numpy as np







def 						__lowercase	(  snake_case_    :    list							,snake_case_    :    list							,snake_case_    :    list							,snake_case_    :    int		)  ->list:



    '''simple docstring'''







    __A       :		Tuple							=	0
    # Number of processes finished
    __A       :		str							=	0
    # Displays the finished process.
    # If it is 0, the performance is completed if it is 1, before the performance.
    __A       :		List[str]							=	[0] * no_of_process
    # List to include calculation results
    __A       :		List[str]							=	[0] * no_of_process

    # Sort by arrival time.
    __A       :		Union[str, Any]							=	[burst_time[i] for i in np.argsort(snake_case_		)]
    __A       :		Optional[Any]							=	[process_name[i] for i in np.argsort(snake_case_		)]
    arrival_time.sort()

    while no_of_process > finished_process_count:
        __A       :		Union[str, Any]							=	0
        while finished_process[i] == 1:
            i += 1
        if current_time < arrival_time[i]:
            __A       :		Union[str, Any]							=	arrival_time[i]

        __A       :		Optional[Any]							=	0
        # Index showing the location of the process being performed
        __A       :		List[Any]							=	0
        # Saves the current response ratio.
        __A       :		Tuple							=	0
        for i in range(0							,snake_case_		):
            if finished_process[i] == 0 and arrival_time[i] <= current_time:
                __A       :		Optional[Any]							=	(burst_time[i] + (current_time - arrival_time[i])) / burst_time[
                    i
                ]
            if response_ratio < temp:
                __A       :		Dict							=	temp
                __A       :		Tuple							=	i

        # Calculate the turn around time
        __A       :		Dict							=	current_time + burst_time[loc] - arrival_time[loc]
        current_time += burst_time[loc]
        # Indicates that the process has been performed.
        __A       :		int							=	1
        # Increase finished_process_count by 1
        finished_process_count += 1

    return turn_around_time







def 						__lowercase	(  snake_case_    :    list							,snake_case_    :    list							,snake_case_    :    list							,snake_case_    :    int		)  ->list:



    '''simple docstring'''







    __A       :		Any							=	[0] * no_of_process
    for i in range(0							,snake_case_		):
        __A       :		Tuple							=	turn_around_time[i] - burst_time[i]
    return waiting_time


if __name__ == "__main__":
       a_					=     5
       a_					=     ["""A""", """B""", """C""", """D""", """E"""]
       a_					=     [1, 2, 3, 4, 5]
       a_					=     [1, 2, 3, 4, 5]

       a_					=     calculate_turn_around_time(
           process_name, arrival_time, burst_time, no_of_process
       )
       a_					=     calculate_waiting_time(
           process_name, turn_around_time, burst_time, no_of_process
       )

       print("""Process name \tArrival time \tBurst time \tTurn around time \tWaiting time""")
       for i in range(0, no_of_process):
              print(
                  f'''{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'''
                  f'''{turn_around_time[i]}\t\t\t{waiting_time[i]}'''
              )

       print(f'''average waiting time : {mean(waiting_time):.5f}''')
       print(f'''average turn around time : {mean(turn_around_time):.5f}''')











"""simple docstring"""



import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


a_					=     logging.get_logger(__name__)






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 def __init__(       self   ,		*__lowerCamelCase   ,		**__lowerCamelCase    ):



     '''simple docstring'''




     warnings.warn(
         '''The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
         ''' Please use PoolFormerImageProcessor instead.'''   ,		__lowerCamelCase   ,		)
     super().__init__(*__lowerCamelCase   ,		**__lowerCamelCase    )




