
'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case									=    logging.get_logger(__name__)

snake_case									=    {
    """caidas/swin2sr-classicalsr-x2-64""": (
        """https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json"""
    ),
}




class    lowerCAmelCase       (     UpperCamelCase_  ):
 A_				:				str	=			"""swin2sr"""

 A_				:				List[Any]	=			{
     """hidden_size""": """embed_dim""",
     """num_attention_heads""": """num_heads""",
     """num_hidden_layers""": """num_layers""",
 }


 def __init__(    self  : Union[str, Any]			,							a__  : Union[str, Any]=64			,							a__  : int=1			,							a__  : int=3			,							a__  : int=180			,							a__  : Tuple=[6, 6, 6, 6, 6, 6]			,							a__  : str=[6, 6, 6, 6, 6, 6]			,							a__  : Dict=8			,							a__  : List[str]=2.0			,							a__  : Tuple=True			,							a__  : int=0.0			,							a__  : Any=0.0			,							a__  : Dict=0.1			,							a__  : List[Any]="gelu"			,							a__  : List[Any]=False			,							a__  : Union[str, Any]=0.02			,							a__  : Tuple=1e-5			,							a__  : List[str]=2			,							a__  : int=1.0			,							a__  : Tuple="1conv"			,							a__  : Any="pixelshuffle"			,							**a__  : Union[str, Any]			,							):
  '''simple docstring'''

  super().__init__(**a__    )

  lowerCAmelCase__     :   Any     		=	image_size
  lowerCAmelCase__     :   int     		=	patch_size
  lowerCAmelCase__     :   Tuple     		=	num_channels
  lowerCAmelCase__     :   str     		=	embed_dim
  lowerCAmelCase__     :   List[str]     		=	depths
  lowerCAmelCase__     :   Tuple     		=	len(a__    )
  lowerCAmelCase__     :   Optional[Any]     		=	num_heads
  lowerCAmelCase__     :   int     		=	window_size
  lowerCAmelCase__     :   List[str]     		=	mlp_ratio
  lowerCAmelCase__     :   List[Any]     		=	qkv_bias
  lowerCAmelCase__     :   Tuple     		=	hidden_dropout_prob
  lowerCAmelCase__     :   List[str]     		=	attention_probs_dropout_prob
  lowerCAmelCase__     :   List[Any]     		=	drop_path_rate
  lowerCAmelCase__     :   str     		=	hidden_act
  lowerCAmelCase__     :   Optional[Any]     		=	use_absolute_embeddings
  lowerCAmelCase__     :   Union[str, Any]     		=	layer_norm_eps
  lowerCAmelCase__     :   Tuple     		=	initializer_range
  lowerCAmelCase__     :   int     		=	upscale
  lowerCAmelCase__     :   int     		=	img_range
  lowerCAmelCase__     :   int     		=	resi_connection
  lowerCAmelCase__     :   Optional[int]     		=	upsampler







'''simple docstring'''

from __future__ import annotations

import pandas as pd


def        UpperCAmelCase_ (  lowerCamelCase_      ,			lowerCamelCase_      ,			lowerCamelCase_			):







 """simple docstring"""


 lowerCAmelCase__     :   Tuple     		=	[0] * no_of_processes
 lowerCAmelCase__     :   Any     		=	[0] * no_of_processes
 # Copy the burst time into remaining_time[]
 for i in range(lowerCamelCase_			):
  lowerCAmelCase__     :   Dict     		=	burst_time[i]

 lowerCAmelCase__     :   str     		=	0
 lowerCAmelCase__     :   Optional[Any]     		=	0
 lowerCAmelCase__     :   Optional[Any]     		=	9_9_9_9_9_9_9_9_9
 lowerCAmelCase__     :   int     		=	0
 lowerCAmelCase__     :   str     		=	False

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

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

  lowerCAmelCase__     :   Optional[Any]     		=	remaining_time[short]
  if minm == 0:
   lowerCAmelCase__     :   Optional[int]     		=	9_9_9_9_9_9_9_9_9

  if remaining_time[short] == 0:
   complete += 1
   lowerCAmelCase__     :   int     		=	False

   # Find finish time of current process
   lowerCAmelCase__     :   Tuple     		=	increment_time + 1

   # Calculate waiting time
   lowerCAmelCase__     :   Dict     		=	finish_time - arrival_time[short]
   lowerCAmelCase__     :   Optional[Any]     		=	finar - burst_time[short]

   if waiting_time[short] < 0:
    lowerCAmelCase__     :   Tuple     		=	0

        # Increment time
  increment_time += 1
 return waiting_time


def        UpperCAmelCase_ (  lowerCamelCase_      ,			lowerCamelCase_      ,			lowerCamelCase_			):







 """simple docstring"""


 lowerCAmelCase__     :   Optional[Any]     		=	[0] * no_of_processes
 for i in range(lowerCamelCase_			):
  lowerCAmelCase__     :   Dict     		=	burst_time[i] + waiting_time[i]
 return turn_around_time


def        UpperCAmelCase_ (  lowerCamelCase_      ,			lowerCamelCase_      ,			lowerCamelCase_			):







 """simple docstring"""


 lowerCAmelCase__     :   Union[str, Any]     		=	0
 lowerCAmelCase__     :   Optional[int]     		=	0
 for i in range(lowerCamelCase_			):
  lowerCAmelCase__     :   Tuple     		=	total_waiting_time + waiting_time[i]
  lowerCAmelCase__     :   str     		=	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""")
     snake_case									=    int(input())
     snake_case									=    [0] * no_of_processes
     snake_case									=    [0] * no_of_processes
     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))
          snake_case					,					snake_case									=    map(int, input().split())

     snake_case									=    calculate_waitingtime(arrival_time, burst_time, no_of_processes)

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

     calculate_average_times(waiting_time, turn_around_time, no_of_processes)

     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)





