






import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer







def 	_UpperCamelCase   (    UpperCamelCase_       :					Tuple    ,       UpperCamelCase_       :					Optional[int]    ,       UpperCamelCase_       :					Union[str, Any]    ,       UpperCamelCase_       :					Optional[Any]    ,       UpperCamelCase_       :					List[Any]=True    ,       UpperCamelCase_       :					List[str]="pt"		)  ->   Dict:

						"""simple docstring"""



						lowerCAmelCase__    						=						{'add_prefix_space': True} if isinstance(UpperCamelCase_    ,       UpperCamelCase_		) and not line.startswith(' '		) else {}
						lowerCAmelCase__    						=						padding_side
						return tokenizer(
						    [line]    ,       max_length=UpperCamelCase_    ,       padding='max_length' if pad_to_max_length else None    ,       truncation=UpperCamelCase_    ,       return_tensors=UpperCamelCase_    ,       add_special_tokens=UpperCamelCase_    ,       **UpperCamelCase_    ,       )







def 	_UpperCamelCase   (    UpperCamelCase_       :					Tuple    ,       UpperCamelCase_       :					Optional[int]    ,       UpperCamelCase_       :					Optional[Any]=None    ,       )  ->   Optional[Any]:

						"""simple docstring"""



						lowerCAmelCase__    						=						input_ids.ne(UpperCamelCase_		).any(dim=0		)
						if attention_mask is None:
												return input_ids[:, keep_column_mask]
						else:
												return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])


class     __SCREAMING_SNAKE_CASE					(   _UpperCAmelCase):






						def __init__(	self     ,						_UpperCamelCase     ,						_UpperCamelCase     ,						_UpperCamelCase     ,						_UpperCamelCase     ,						_UpperCamelCase="train"     ,						_UpperCamelCase=None     ,						_UpperCamelCase=None     ,						_UpperCamelCase=None     ,						_UpperCamelCase=""     ,						):






												"""simple docstring"""
												super().__init__()
												lowerCAmelCase__    						=						Path(A_   ).joinpath(type_path + '.source'   )
												lowerCAmelCase__    						=						Path(A_   ).joinpath(type_path + '.target'   )
												lowerCAmelCase__    						=						self.get_char_lens(self.src_file   )
												lowerCAmelCase__    						=						max_source_length
												lowerCAmelCase__    						=						max_target_length
												assert min(self.src_lens   ) > 0, F"found empty line in {self.src_file}"
												lowerCAmelCase__    						=						tokenizer
												lowerCAmelCase__    						=						prefix
												if n_obs is not None:
																		lowerCAmelCase__    						=						self.src_lens[:n_obs]
												lowerCAmelCase__    						=						src_lang
												lowerCAmelCase__    						=						tgt_lang






						def __len__(	self   ):






												"""simple docstring"""
												return len(self.src_lens   )






						def __getitem__(	self     ,						_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						index + 1  # linecache starts at 1
												lowerCAmelCase__    						=						self.prefix + linecache.getline(str(self.src_file   )     ,						A_   ).rstrip('\n'   )
												lowerCAmelCase__    						=						linecache.getline(str(self.tgt_file   )     ,						A_   ).rstrip('\n'   )
												assert source_line, F"empty source line for index {index}"
												assert tgt_line, F"empty tgt line for index {index}"

												# Need to add eos token manually for T5
												if isinstance(self.tokenizer     ,						A_   ):
																		source_line += self.tokenizer.eos_token
																		tgt_line += self.tokenizer.eos_token

												# Pad source and target to the right
												lowerCAmelCase__    						=						(
												    self.tokenizer.question_encoder if isinstance(self.tokenizer     ,						A_   ) else self.tokenizer
												)
												lowerCAmelCase__    						=						self.tokenizer.generator if isinstance(self.tokenizer     ,						A_   ) else self.tokenizer

												lowerCAmelCase__    						=						encode_line(A_     ,						A_     ,						self.max_source_length     ,						'right'   )
												lowerCAmelCase__    						=						encode_line(A_     ,						A_     ,						self.max_target_length     ,						'right'   )

												lowerCAmelCase__    						=						source_inputs['input_ids'].squeeze()
												lowerCAmelCase__    						=						target_inputs['input_ids'].squeeze()
												lowerCAmelCase__    						=						source_inputs['attention_mask'].squeeze()
												return {
												    "input_ids": source_ids,
												    "attention_mask": src_mask,
												    "decoder_input_ids": target_ids,
												}






						@staticmethod
						def       UpperCamelCase__      (	_UpperCamelCase   ):






												"""simple docstring"""
												return [len(A_   ) for x in Path(A_   ).open().readlines()]







						def       UpperCamelCase__      (	self     ,						_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						torch.stack([x['input_ids'] for x in batch]   )
												lowerCAmelCase__    						=						torch.stack([x['attention_mask'] for x in batch]   )
												lowerCAmelCase__    						=						torch.stack([x['decoder_input_ids'] for x in batch]   )
												lowerCAmelCase__    						=						(
												    self.tokenizer.generator.pad_token_id
												    if isinstance(self.tokenizer     ,						A_   )
												    else self.tokenizer.pad_token_id
												)
												lowerCAmelCase__    						=						(
												    self.tokenizer.question_encoder.pad_token_id
												    if isinstance(self.tokenizer     ,						A_   )
												    else self.tokenizer.pad_token_id
												)
												lowerCAmelCase__    						=						trim_batch(A_     ,						A_   )
												lowerCAmelCase__						,       lowerCAmelCase__    						=						trim_batch(A_     ,						A_     ,						attention_mask=A_   )
												lowerCAmelCase__    						=						{
												    'input_ids': source_ids,
												    'attention_mask': source_mask,
												    'decoder_input_ids': y,
												}
												return batch




__snake_case    :    Optional[Any]         =     getLogger(__name__)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Union[str, Any]		)  ->   List[str]:

						"""simple docstring"""



						return list(itertools.chain.from_iterable(UpperCamelCase_		)		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Dict		)  ->   List[str]:

						"""simple docstring"""



						lowerCAmelCase__    						=						get_git_info()
						save_json(UpperCamelCase_    ,       os.path.join(UpperCamelCase_    ,       'git_log.json'		)		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Union[str, Any]    ,       UpperCamelCase_       :					int    ,       UpperCamelCase_       :					List[Any]=4    ,       **UpperCamelCase_       :					str		)  ->   Dict:

						"""simple docstring"""



						with open(UpperCamelCase_    ,       'w'		) as f:
												json.dump(UpperCamelCase_    ,       UpperCamelCase_    ,       indent=UpperCamelCase_    ,       **UpperCamelCase_		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[int]		)  ->   Union[str, Any]:

						"""simple docstring"""



						with open(UpperCamelCase_		) as f:
												return json.load(UpperCamelCase_		)







def 	_UpperCamelCase   (    )  ->   List[Any]:

						"""simple docstring"""



						lowerCAmelCase__    						=						git.Repo(search_parent_directories=UpperCamelCase_		)
						lowerCAmelCase__    						=						{
						    'repo_id': str(UpperCamelCase_		),
						    'repo_sha': str(repo.head.object.hexsha		),
						    'repo_branch': str(repo.active_branch		),
						    'hostname': str(socket.gethostname()		),
						}
						return repo_infos







def 	_UpperCamelCase   (    UpperCamelCase_       :					List[str]    ,       UpperCamelCase_       :					Optional[int]		)  ->   str:

						"""simple docstring"""



						return list(map(UpperCamelCase_    ,       UpperCamelCase_		)		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[Any]    ,       UpperCamelCase_       :					Any		)  ->   Union[str, Any]:

						"""simple docstring"""



						with open(UpperCamelCase_    ,       'wb'		) as f:
												return pickle.dump(UpperCamelCase_    ,       UpperCamelCase_		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					List[Any]		)  ->   Dict:

						"""simple docstring"""



						def remove_articles(UpperCamelCase_       :					str		):
												return re.sub(r'\b(a|an|the)\b'    ,       ' '    ,       UpperCamelCase_		)

						def white_space_fix(UpperCamelCase_       :					Tuple		):
												return " ".join(text.split()		)

						def remove_punc(UpperCamelCase_       :					Optional[Any]		):
												lowerCAmelCase__    						=						set(string.punctuation		)
												return "".join(ch for ch in text if ch not in exclude		)

						def lower(UpperCamelCase_       :					Union[str, Any]		):
												return text.lower()

						return white_space_fix(remove_articles(remove_punc(lower(UpperCamelCase_		)		)		)		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Union[str, Any]    ,       UpperCamelCase_       :					int		)  ->   Optional[int]:

						"""simple docstring"""



						lowerCAmelCase__    						=						normalize_answer(UpperCamelCase_		).split()
						lowerCAmelCase__    						=						normalize_answer(UpperCamelCase_		).split()
						lowerCAmelCase__    						=						Counter(UpperCamelCase_		) & Counter(UpperCamelCase_		)
						lowerCAmelCase__    						=						sum(common.values()		)
						if num_same == 0:
												return 0
						lowerCAmelCase__    						=						1.0 * num_same / len(UpperCamelCase_		)
						lowerCAmelCase__    						=						1.0 * num_same / len(UpperCamelCase_		)
						lowerCAmelCase__    						=						(2 * precision * recall) / (precision + recall)
						return fa







def 	_UpperCamelCase   (    UpperCamelCase_       :					List[str]    ,       UpperCamelCase_       :					List[str]		)  ->   Any:

						"""simple docstring"""



						return normalize_answer(UpperCamelCase_		) == normalize_answer(UpperCamelCase_		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Dict    ,       UpperCamelCase_       :					List[Any]		)  ->   Union[str, Any]:

						"""simple docstring"""



						assert len(UpperCamelCase_		) == len(UpperCamelCase_		)
						lowerCAmelCase__    						=						0
						for hypo, pred in zip(UpperCamelCase_    ,       UpperCamelCase_		):
												em += exact_match_score(UpperCamelCase_    ,       UpperCamelCase_		)
						if len(UpperCamelCase_		) > 0:
												em /= len(UpperCamelCase_		)
						return {"em": em}







def 	_UpperCamelCase   (    UpperCamelCase_       :					List[str]		)  ->   List[str]:

						"""simple docstring"""



						return model_prefix.startswith('rag'		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[Any]    ,       UpperCamelCase_       :					Optional[int]    ,       UpperCamelCase_       :					List[str]		)  ->   int:

						"""simple docstring"""



						lowerCAmelCase__    						=						{p: p for p in extra_params}
						# T5 models don't have `dropout` param, they have `dropout_rate` instead
						lowerCAmelCase__    						=						'dropout_rate'
						for p in extra_params:
												if getattr(UpperCamelCase_    ,       UpperCamelCase_    ,       UpperCamelCase_		):
																		if not hasattr(UpperCamelCase_    ,       UpperCamelCase_		) and not hasattr(UpperCamelCase_    ,       equivalent_param[p]		):
																								logger.info('config doesn\'t have a `{}` attribute'.format(UpperCamelCase_		)		)
																								delattr(UpperCamelCase_    ,       UpperCamelCase_		)
																								continue
																		lowerCAmelCase__    						=						p if hasattr(UpperCamelCase_    ,       UpperCamelCase_		) else equivalent_param[p]
																		setattr(UpperCamelCase_    ,       UpperCamelCase_    ,       getattr(UpperCamelCase_    ,       UpperCamelCase_		)		)
																		delattr(UpperCamelCase_    ,       UpperCamelCase_		)
						return hparams, config













from __future__ import annotations

import pandas as pd







def 	_UpperCamelCase   (    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 	_UpperCamelCase   (    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 	_UpperCamelCase   (    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""")
					__snake_case    :    Dict         =     int(input())
					__snake_case    :    List[Any]         =     [0] * no_of_processes
					__snake_case    :    str         =     [0] * no_of_processes
					__snake_case    :    Optional[int]         =     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    :    Any         =     map(int, input().split())

					__snake_case    :    str         =     calculate_waitingtime(arrival_time, burst_time, no_of_processes)

					__snake_case    :    Dict         =     burst_time
					__snake_case    :    Optional[int]         =     no_of_processes
					__snake_case    :    str         =     waiting_time
					__snake_case    :    int         =     calculate_turnaroundtime(bt, n, wt)

					calculate_average_times(waiting_time, turn_around_time, no_of_processes)

					__snake_case    :    Dict         =     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)





