




from __future__ import annotations

import pandas as pd







def      lowerCamelCase_						(			UpperCamelCase__							: list[int]					,	UpperCamelCase__							: list[int]					,	UpperCamelCase__							: int )	->			list[int]:





				"""simple docstring"""


				__lowerCamelCase									=       [0] * no_of_processes
				__lowerCamelCase									=       [0] * no_of_processes
				# Copy the burst time into remaining_time[]
				for i in range(UpperCamelCase__ ):
								__lowerCamelCase									=       burst_time[i]

				__lowerCamelCase									=       0
				__lowerCamelCase									=       0
				__lowerCamelCase									=       9_9999_9999
				__lowerCamelCase									=       0
				__lowerCamelCase									=       False

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

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

								__lowerCamelCase									=       remaining_time[short]
								if minm == 0:
												__lowerCamelCase									=       9_9999_9999

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

												# Find finish time of current process
												__lowerCamelCase									=       increment_time + 1

												# Calculate waiting time
												__lowerCamelCase									=       finish_time - arrival_time[short]
												__lowerCamelCase									=       finar - burst_time[short]

												if waiting_time[short] < 0:
																__lowerCamelCase									=       0

        # Increment time
								increment_time += 1
				return waiting_time







def      lowerCamelCase_						(			UpperCamelCase__							: list[int]					,	UpperCamelCase__							: int					,	UpperCamelCase__							: list[int] )	->			list[int]:





				"""simple docstring"""


				__lowerCamelCase									=       [0] * no_of_processes
				for i in range(UpperCamelCase__ ):
								__lowerCamelCase									=       burst_time[i] + waiting_time[i]
				return turn_around_time







def      lowerCamelCase_						(			UpperCamelCase__							: list[int]					,	UpperCamelCase__							: list[int]					,	UpperCamelCase__							: int )	->			None:





				"""simple docstring"""


				__lowerCamelCase									=       0
				__lowerCamelCase									=       0
				for i in range(UpperCamelCase__ ):
								__lowerCamelCase									=       total_waiting_time + waiting_time[i]
								__lowerCamelCase									=       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")
					__A								=       int(input())
					__A								=       [0] * no_of_processes
					__A								=       [0] * no_of_processes
					__A								=       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))
										__A					, __A								=       map(int, input().split())

					__A								=       calculate_waitingtime(arrival_time, burst_time, no_of_processes)

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

					calculate_average_times(waiting_time, turn_around_time, no_of_processes)

					__A								=       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)








import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
					import torch

					from transformers.activations import gelu_new, gelu_python, get_activation







@require_torch
class        __lowerCAmelCase					(			unittest.TestCase					):

			"""simple docstring"""







			def  lowercase_       ( self				)       -> int:



							'''simple docstring'''
							__lowerCamelCase									=       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
							__lowerCamelCase									=       get_activation('gelu'				)
							self.assertTrue(torch.allclose(gelu_python(lowerCamelCase__				)     ,		torch_builtin(lowerCamelCase__				)				)				)
							self.assertFalse(torch.allclose(gelu_python(lowerCamelCase__				)     ,		gelu_new(lowerCamelCase__				)				)				)


			def  lowercase_       ( self				)       -> Optional[int]:



							'''simple docstring'''
							__lowerCamelCase									=       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
							__lowerCamelCase									=       get_activation('gelu'				)
							__lowerCamelCase									=       get_activation('gelu_10'				)

							__lowerCamelCase									=       torch_builtin(lowerCamelCase__				)
							__lowerCamelCase									=       geluaa(lowerCamelCase__				)

							__lowerCamelCase									=       torch.where(y_gelu_aa < 10.0     ,		1     ,		0				)

							self.assertTrue(torch.max(lowerCamelCase__				).item() == 10.0				)
							self.assertTrue(torch.allclose(y_gelu * clipped_mask     ,		y_gelu_aa * clipped_mask				)				)


			def  lowercase_       ( self				)       -> Any:



							'''simple docstring'''
							get_activation('gelu'				)
							get_activation('gelu_10'				)
							get_activation('gelu_fast'				)
							get_activation('gelu_new'				)
							get_activation('gelu_python'				)
							get_activation('gelu_pytorch_tanh'				)
							get_activation('linear'				)
							get_activation('mish'				)
							get_activation('quick_gelu'				)
							get_activation('relu'				)
							get_activation('sigmoid'				)
							get_activation('silu'				)
							get_activation('swish'				)
							get_activation('tanh'				)
							with self.assertRaises(lowerCamelCase__				):
											get_activation('bogus'				)
							with self.assertRaises(lowerCamelCase__				):
											get_activation(lowerCamelCase__				)






			def  lowercase_       ( self				)       -> Dict:



							'''simple docstring'''
							__lowerCamelCase									=       get_activation('gelu'				)
							__lowerCamelCase									=       1
							__lowerCamelCase									=       get_activation('gelu'				)
							self.assertEqual(acta.a     ,		1				)
							with self.assertRaises(lowerCamelCase__				):
											__lowerCamelCase									=       acta.a


