


'''simple docstring'''
from statistics import mean

import numpy as np


def 			_lowercase       (				UpperCamelCase__       :					list,				UpperCamelCase__       :					list,				UpperCamelCase__       :					list,				UpperCamelCase__       :					int			):
 __A  :		Optional[Any]       =			0
 # Number of processes finished
 __A  :		Optional[int]       =			0
 # Displays the finished process.
 # If it is 0, the performance is completed if it is 1, before the performance.
 __A  :		Optional[Any]       =			[0] * no_of_process
 # List to include calculation results
 __A  :		List[str]       =			[0] * no_of_process

 # Sort by arrival time.
 __A  :		List[str]       =			[burst_time[i] for i in np.argsort(UpperCamelCase__			)]
 __A  :		Tuple       =			[process_name[i] for i in np.argsort(UpperCamelCase__			)]
 arrival_time.sort()

 while no_of_process > finished_process_count:
  __A  :		Tuple       =			0
  while finished_process[i] == 1:
   i += 1
  if current_time < arrival_time[i]:
   __A  :		List[str]       =			arrival_time[i]

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

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

 return turn_around_time


def 			_lowercase       (				UpperCamelCase__       :					list,				UpperCamelCase__       :					list,				UpperCamelCase__       :					list,				UpperCamelCase__       :					int			):
 __A  :		Tuple       =			[0] * no_of_process
 for i in range(0,				UpperCamelCase__			):
  __A  :		str       =			turn_around_time[i] - burst_time[i]
 return waiting_time


if __name__ == "__main__":
 UpperCAmelCase_ :     int								=      5
 UpperCAmelCase_ :     Optional[int]								=      ['A', 'B', 'C', 'D', 'E']
 UpperCAmelCase_ :     str								=      [1, 2, 3, 4, 5]
 UpperCAmelCase_ :     List[str]								=      [1, 2, 3, 4, 5]

 UpperCAmelCase_ :     Tuple								=      calculate_turn_around_time(
     process_name, arrival_time, burst_time, no_of_process
 )
 UpperCAmelCase_ :     Dict								=      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'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_ :     Dict								=      logging.get_logger(__name__)

UpperCAmelCase_ :     Optional[int]								=      {
    'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}

class 						_lowerCamelCase					(    snake_case_				):




 '''simple docstring'''
 __lowercase				:		Tuple    							=						'''vit_msn'''


 def __init__(      self      ,      __lowercase=768      ,      __lowercase=12      ,      __lowercase=12      ,      __lowercase=3_072      ,      __lowercase="gelu"      ,      __lowercase=0.0      ,      __lowercase=0.0      ,      __lowercase=0.0_2      ,      __lowercase=1E-06      ,      __lowercase=224      ,      __lowercase=16      ,      __lowercase=3      ,      __lowercase=True      ,      **__lowercase      ,      ):

  """simple docstring"""







  super().__init__(**__lowercase						)

  __A  :		Tuple       =			hidden_size
  __A  :		Optional[int]       =			num_hidden_layers
  __A  :		str       =			num_attention_heads
  __A  :		Dict       =			intermediate_size
  __A  :		Optional[Any]       =			hidden_act
  __A  :		Union[str, Any]       =			hidden_dropout_prob
  __A  :		Optional[Any]       =			attention_probs_dropout_prob
  __A  :		List[str]       =			initializer_range
  __A  :		Dict       =			layer_norm_eps
  __A  :		List[Any]       =			image_size
  __A  :		Optional[int]       =			patch_size
  __A  :		List[Any]       =			num_channels
  __A  :		Optional[Any]       =			qkv_bias






