



'''simple docstring'''




from __future__ import annotations

import pandas as pd



def       __lowerCamelCase  (					_lowercase	,				_lowercase	,				_lowercase		)      ->			list[int]:
							UpperCAmelCase     :		Optional[Any]							     =		[0] * no_of_processes
							UpperCAmelCase     :		str							     =		[0] * no_of_processes
							# Copy the burst time into remaining_time[]
							for i in range(_lowercase		):
														UpperCAmelCase     :		Optional[Any]							     =		burst_time[i]

							UpperCAmelCase     :		Union[str, Any]							     =		0
							UpperCAmelCase     :		Optional[int]							     =		0
							UpperCAmelCase     :		int							     =		9_9_9_9_9_9_9_9_9
							UpperCAmelCase     :		Optional[int]							     =		0
							UpperCAmelCase     :		Optional[int]							     =		False

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

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

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

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

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

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

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

        # Increment time
														increment_time += 1
							return waiting_time



def       __lowerCamelCase  (					_lowercase	,				_lowercase	,				_lowercase		)      ->			list[int]:
							UpperCAmelCase     :		str							     =		[0] * no_of_processes
							for i in range(_lowercase		):
														UpperCAmelCase     :		str							     =		burst_time[i] + waiting_time[i]
							return turn_around_time



def       __lowerCamelCase  (					_lowercase	,				_lowercase	,				_lowercase		)      ->			None:
							UpperCAmelCase     :		Union[str, Any]							     =		0
							UpperCAmelCase     :		List[Any]							     =		0
							for i in range(_lowercase		):
														UpperCAmelCase     :		Optional[int]							     =		total_waiting_time + waiting_time[i]
														UpperCAmelCase     :		Union[str, 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""")
							a   :			Optional[Any]					  =    int(input())
							a   :			Union[str, Any]					  =    [0] * no_of_processes
							a   :			int					  =    [0] * no_of_processes
							a   :			List[str]					  =    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   :			Tuple					  =    map(int, input().split())

							a   :			Dict					  =    calculate_waitingtime(arrival_time, burst_time, no_of_processes)

							a   :			Union[str, Any]					  =    burst_time
							a   :			Optional[Any]					  =    no_of_processes
							a   :			Tuple					  =    waiting_time
							a   :			Tuple					  =    calculate_turnaroundtime(bt, n, wt)

							calculate_average_times(waiting_time, turn_around_time, no_of_processes)

							a   :			Optional[int]					  =    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)






'''simple docstring'''




import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
							from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
							from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
							from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


a   :			str					  =    DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

a   :			int					  =    """main"""
# Default branch name
a   :			Any					  =    """f2c752cfc5c0ab6f4bdec59acea69eefbee381c2"""
# One particular commit (not the top of `main`)
a   :			str					  =    """aaaaaaa"""
# This commit does not exist, so we should 404.

a   :			int					  =    """d9e9f15bc825e4b2c9249e9578f884bbcb5e3684"""
# Sha-1 of config.json on the top of `main`, for checking purposes
a   :			Any					  =    """4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3"""



@contextlib.contextmanager
def       __lowerCamelCase  (					)      ->			List[str]:
							print("""Welcome!"""		)
							yield
							print("""Bye!"""		)



@contextlib.contextmanager
def       __lowerCamelCase  (					)      ->			Optional[int]:
							print("""Bonjour!"""		)
							yield
							print("""Au revoir!"""		)

class 			UpperCamelCase_ (							unittest.TestCase			):





	def  _lowercase(  self    )			->			List[Any]:
								# If the spec is missing, importlib would not be able to import the module dynamically.
								assert transformers.__spec__ is not None
								assert importlib.util.find_spec("""transformers"""    ) is not None




class 			UpperCamelCase_ (							unittest.TestCase			):





	@unittest.mock.patch("""sys.stdout"""		,		new_callable=io.StringIO    )
	def  _lowercase(  self		,		A    )			->			Tuple:
								with ContextManagers([]    ):
															print("""Transformers are awesome!"""    )
								# The print statement adds a new line at the end of the output
								self.assertEqual(mock_stdout.getvalue()		,		"""Transformers are awesome!\n"""    )





	@unittest.mock.patch("""sys.stdout"""		,		new_callable=io.StringIO    )
	def  _lowercase(  self		,		A    )			->			Dict:
								with ContextManagers([context_en()]    ):
															print("""Transformers are awesome!"""    )
								# The output should be wrapped with an English welcome and goodbye
								self.assertEqual(mock_stdout.getvalue()		,		"""Welcome!\nTransformers are awesome!\nBye!\n"""    )





	@unittest.mock.patch("""sys.stdout"""		,		new_callable=io.StringIO    )
	def  _lowercase(  self		,		A    )			->			Union[str, Any]:
								with ContextManagers([context_fr(), context_en()]    ):
															print("""Transformers are awesome!"""    )
								# The output should be wrapped with an English and French welcome and goodbye
								self.assertEqual(mock_stdout.getvalue()		,		"""Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n"""    )





	@require_torch
	def  _lowercase(  self    )			->			Optional[int]:
								self.assertEqual(find_labels(A    )		,		["""labels"""]    )
								self.assertEqual(find_labels(A    )		,		["""labels""", """next_sentence_label"""]    )
								self.assertEqual(find_labels(A    )		,		["""start_positions""", """end_positions"""]    )

								class 			UpperCamelCase_ (							__magic_name__			):
									pass




								self.assertEqual(find_labels(A    )		,		["""labels"""]    )





	@require_tf
	def  _lowercase(  self    )			->			int:
								self.assertEqual(find_labels(A    )		,		["""labels"""]    )
								self.assertEqual(find_labels(A    )		,		["""labels""", """next_sentence_label"""]    )
								self.assertEqual(find_labels(A    )		,		["""start_positions""", """end_positions"""]    )

								class 			UpperCamelCase_ (							__magic_name__			):
									pass




								self.assertEqual(find_labels(A    )		,		["""labels"""]    )






	@require_flax
	def  _lowercase(  self    )			->			Any:
								# Flax models don't have labels
								self.assertEqual(find_labels(A    )		,		[]    )
								self.assertEqual(find_labels(A    )		,		[]    )
								self.assertEqual(find_labels(A    )		,		[]    )

								class 			UpperCamelCase_ (							__magic_name__			):
									pass




								self.assertEqual(find_labels(A    )		,		[]    )

