

import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)


SCREAMING_SNAKE_CASE_        =      {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

SCREAMING_SNAKE_CASE_        =      {
    'vocab_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
    },
}

SCREAMING_SNAKE_CASE_        =      {
    'allenai/longformer-base-4096': 4096,
    'allenai/longformer-large-4096': 4096,
    'allenai/longformer-large-4096-finetuned-triviaqa': 4096,
    'allenai/longformer-base-4096-extra.pos.embd.only': 4096,
    'allenai/longformer-large-4096-extra.pos.embd.only': 4096,
}

@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 							__SCREAMING_SNAKE_CASE							(				)   ->       List[str]:
				_UpperCAmelCase       :		Union[str, Any] 		=    (
				    list(range(ord("!" )  ,      ord("~" ) + 1 ) ) + list(range(ord("¡" )  ,      ord("¬" ) + 1 ) ) + list(range(ord("®" )  ,      ord("ÿ" ) + 1 ) )
				)
				_UpperCAmelCase       :		Optional[int] 		=    bs[:]
				_UpperCAmelCase       :		Union[str, Any] 		=    0
				for b in range(2**8 ):
								if b not in bs:
												bs.append(lowerCAmelCase )
												cs.append(2**8 + n )
												n += 1
				_UpperCAmelCase       :		Any 		=    [chr(lowerCAmelCase ) for n in cs]
				return dict(zip(lowerCAmelCase  ,      lowerCAmelCase ) )

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  List[Any] )   ->       List[str]:
				_UpperCAmelCase       :		int 		=    set()
				_UpperCAmelCase       :		str 		=    word[0]
				for char in word[1:]:
								pairs.add((prev_char, char) )
								_UpperCAmelCase       :		List[str] 		=    char
				return pairs





class 				a  (	UpperCAmelCase				):
						_lowercase    						=			VOCAB_FILES_NAMES
						_lowercase    						=			PRETRAINED_VOCAB_FILES_MAP
						_lowercase    						=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowercase    						=			["input_ids", "attention_mask"]


						def __init__(       self						,					A_						,					A_						,					A_="replace"						,					A_="<s>"						,					A_="</s>"						,					A_="</s>"						,					A_="<s>"						,					A_="<unk>"						,					A_="<pad>"						,					A_="<mask>"						,					A_=False						,					**A_						,					):







										'''simple docstring'''


										_UpperCAmelCase       :		Any 		=    AddedToken(A_						,					lstrip=A_						,					rstrip=A_	) if isinstance(A_						,					A_	) else bos_token
										_UpperCAmelCase       :		Tuple 		=    AddedToken(A_						,					lstrip=A_						,					rstrip=A_	) if isinstance(A_						,					A_	) else eos_token
										_UpperCAmelCase       :		Union[str, Any] 		=    AddedToken(A_						,					lstrip=A_						,					rstrip=A_	) if isinstance(A_						,					A_	) else sep_token
										_UpperCAmelCase       :		Union[str, Any] 		=    AddedToken(A_						,					lstrip=A_						,					rstrip=A_	) if isinstance(A_						,					A_	) else cls_token
										_UpperCAmelCase       :		Tuple 		=    AddedToken(A_						,					lstrip=A_						,					rstrip=A_	) if isinstance(A_						,					A_	) else unk_token
										_UpperCAmelCase       :		List[Any] 		=    AddedToken(A_						,					lstrip=A_						,					rstrip=A_	) if isinstance(A_						,					A_	) else pad_token

										# Mask token behave like a normal word, i.e. include the space before it
										_UpperCAmelCase       :		Union[str, Any] 		=    AddedToken(A_						,					lstrip=A_						,					rstrip=A_	) if isinstance(A_						,					A_	) else mask_token

										super().__init__(
										    errors=A_						,					bos_token=A_						,					eos_token=A_						,					unk_token=A_						,					sep_token=A_						,					cls_token=A_						,					pad_token=A_						,					mask_token=A_						,					add_prefix_space=A_						,					**A_						,					)

										with open(A_						,					encoding="utf-8"	) as vocab_handle:
														_UpperCAmelCase       :		List[Any] 		=    json.load(A_	)
										_UpperCAmelCase       :		Optional[Any] 		=    {v: k for k, v in self.encoder.items()}
										_UpperCAmelCase       :		Tuple 		=    errors  # how to handle errors in decoding
										_UpperCAmelCase       :		Optional[Any] 		=    bytes_to_unicode()
										_UpperCAmelCase       :		Optional[int] 		=    {v: k for k, v in self.byte_encoder.items()}
										with open(A_						,					encoding="utf-8"	) as merges_handle:
														_UpperCAmelCase       :		Optional[int] 		=    merges_handle.read().split("\n"	)[1:-1]
										_UpperCAmelCase       :		Optional[Any] 		=    [tuple(merge.split()	) for merge in bpe_merges]
										_UpperCAmelCase       :		Tuple 		=    dict(zip(A_						,					range(len(A_	)	)	)	)
										_UpperCAmelCase       :		Dict 		=    {}
										_UpperCAmelCase       :		Dict 		=    add_prefix_space

										# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
										_UpperCAmelCase       :		Dict 		=    re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"	)


						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										return len(self.encoder	)


						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										return dict(self.encoder						,					**self.added_tokens_encoder	)


						def        _UpperCAmelCase				(       self						,					A_	):







										'''simple docstring'''


										if token in self.cache:
														return self.cache[token]
										_UpperCAmelCase       :		Dict 		=    tuple(A_	)
										_UpperCAmelCase       :		int 		=    get_pairs(A_	)

										if not pairs:
														return token

										while True:
														_UpperCAmelCase       :		Tuple 		=    min(A_						,					key=lambda A_	: self.bpe_ranks.get(A_						,					float("inf"	)	)	)
														if bigram not in self.bpe_ranks:
																		break
														_UpperCAmelCase       :		Dict 		=    bigram
														_UpperCAmelCase       :		Dict 		=    []
														_UpperCAmelCase       :		Tuple 		=    0
														while i < len(A_	):
																		try:
																						_UpperCAmelCase       :		Optional[Any] 		=    word.index(A_						,					A_	)
																		except ValueError:
																						new_word.extend(word[i:]	)
																						break
																		else:
																						new_word.extend(word[i:j]	)
																						_UpperCAmelCase       :		List[Any] 		=    j

																		if word[i] == first and i < len(A_	) - 1 and word[i + 1] == second:
																						new_word.append(first + second	)
																						i += 2
																		else:
																						new_word.append(word[i]	)
																						i += 1
														_UpperCAmelCase       :		Any 		=    tuple(A_	)
														_UpperCAmelCase       :		Optional[Any] 		=    new_word
														if len(A_	) == 1:
																		break
														else:
																		_UpperCAmelCase       :		Dict 		=    get_pairs(A_	)
										_UpperCAmelCase       :		Union[str, Any] 		=    " ".join(A_	)
										_UpperCAmelCase       :		Dict 		=    word
										return word


						def        _UpperCAmelCase				(       self						,					A_	):







										'''simple docstring'''


										_UpperCAmelCase       :		Optional[int] 		=    []
										for token in re.findall(self.pat						,					A_	):
														_UpperCAmelCase       :		Tuple 		=    "".join(
														    self.byte_encoder[b] for b in token.encode("utf-8"	)	)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
														bpe_tokens.extend(bpe_token for bpe_token in self.bpe(A_	).split(" "	)	)
										return bpe_tokens


						def        _UpperCAmelCase				(       self						,					A_	):







										'''simple docstring'''


										return self.encoder.get(A_						,					self.encoder.get(self.unk_token	)	)


						def        _UpperCAmelCase				(       self						,					A_	):







										'''simple docstring'''


										return self.decoder.get(A_	)


						def        _UpperCAmelCase				(       self						,					A_	):







										'''simple docstring'''


										_UpperCAmelCase       :		List[Any] 		=    "".join(A_	)
										_UpperCAmelCase       :		int 		=    bytearray([self.byte_decoder[c] for c in text]	).decode("utf-8"						,					errors=self.errors	)
										return text


						def        _UpperCAmelCase				(       self						,					A_						,					A_ = None	):







										'''simple docstring'''


										if not os.path.isdir(A_	):
														logger.error(f'Vocabulary path ({save_directory}) should be a directory'	)
														return
										_UpperCAmelCase       :		List[Any] 		=    os.path.join(
										    A_						,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)
										_UpperCAmelCase       :		Tuple 		=    os.path.join(
										    A_						,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]	)

										with open(A_						,					"w"						,					encoding="utf-8"	) as f:
														f.write(json.dumps(self.encoder						,					indent=2						,					sort_keys=A_						,					ensure_ascii=A_	) + "\n"	)

										_UpperCAmelCase       :		int 		=    0
										with open(A_						,					"w"						,					encoding="utf-8"	) as writer:
														writer.write("#version: 0.2\n"	)
														for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,					key=lambda A_	: kv[1]	):
																		if index != token_index:
																						logger.warning(
																						    f'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
																						    " Please check that the tokenizer is not corrupted!"	)
																						_UpperCAmelCase       :		int 		=    token_index
																		writer.write(" ".join(A_	) + "\n"	)
																		index += 1

										return vocab_file, merge_file


						def        _UpperCAmelCase				(       self						,					A_						,					A_ = None	):







										'''simple docstring'''


										if token_ids_a is None:
														return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										_UpperCAmelCase       :		List[Any] 		=    [self.cls_token_id]
										_UpperCAmelCase       :		str 		=    [self.sep_token_id]
										return cls + token_ids_a + sep + sep + token_ids_a + sep


						def        _UpperCAmelCase				(       self						,					A_						,					A_ = None						,					A_ = False	):







										'''simple docstring'''


										if already_has_special_tokens:
														return super().get_special_tokens_mask(
														    token_ids_a=A_						,					token_ids_a=A_						,					already_has_special_tokens=A_	)

										if token_ids_a is None:
														return [1] + ([0] * len(A_	)) + [1]
										return [1] + ([0] * len(A_	)) + [1, 1] + ([0] * len(A_	)) + [1]


						def        _UpperCAmelCase				(       self						,					A_						,					A_ = None	):







										'''simple docstring'''


										_UpperCAmelCase       :		Any 		=    [self.sep_token_id]
										_UpperCAmelCase       :		Dict 		=    [self.cls_token_id]

										if token_ids_a is None:
														return len(cls + token_ids_a + sep	) * [0]
										return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]





						def        _UpperCAmelCase				(       self						,					A_						,					A_=False						,					**A_	):







										'''simple docstring'''


										_UpperCAmelCase       :		int 		=    kwargs.pop("add_prefix_space"						,					self.add_prefix_space	)
										if (is_split_into_words or add_prefix_space) and (len(A_	) > 0 and not text[0].isspace()):
														_UpperCAmelCase       :		Dict 		=    " " + text
										return (text, kwargs)





from __future__ import annotations

import pandas as pd

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  list[int]  ,      lowerCAmelCase:  list[int]  ,      lowerCAmelCase:  int )   ->       list[int]:
				_UpperCAmelCase       :		List[Any] 		=    [0] * no_of_processes
				_UpperCAmelCase       :		Dict 		=    [0] * no_of_processes
				# Copy the burst time into remaining_time[]
				for i in range(lowerCAmelCase ):
								_UpperCAmelCase       :		List[str] 		=    burst_time[i]

				_UpperCAmelCase       :		Any 		=    0
				_UpperCAmelCase       :		Union[str, Any] 		=    0
				_UpperCAmelCase       :		str 		=    9_9999_9999
				_UpperCAmelCase       :		List[Any] 		=    0
				_UpperCAmelCase       :		Any 		=    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:
																				_UpperCAmelCase       :		Optional[int] 		=    remaining_time[j]
																				_UpperCAmelCase       :		int 		=    j
																				_UpperCAmelCase       :		Tuple 		=    True

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

								_UpperCAmelCase       :		List[Any] 		=    remaining_time[short]
								if minm == 0:
												_UpperCAmelCase       :		List[Any] 		=    9_9999_9999

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

												# Find finish time of current process
												_UpperCAmelCase       :		Optional[int] 		=    increment_time + 1

												# Calculate waiting time
												_UpperCAmelCase       :		str 		=    finish_time - arrival_time[short]
												_UpperCAmelCase       :		Union[str, Any] 		=    finar - burst_time[short]

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

        # Increment time
								increment_time += 1
				return waiting_time

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

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  list[int]  ,      lowerCAmelCase:  list[int]  ,      lowerCAmelCase:  int )   ->       None:
				_UpperCAmelCase       :		Dict 		=    0
				_UpperCAmelCase       :		List[str] 		=    0
				for i in range(lowerCAmelCase ):
								_UpperCAmelCase       :		Union[str, Any] 		=    total_waiting_time + waiting_time[i]
								_UpperCAmelCase       :		int 		=    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')
					SCREAMING_SNAKE_CASE_        =      int(input())
					SCREAMING_SNAKE_CASE_        =      [0] * no_of_processes
					SCREAMING_SNAKE_CASE_        =      [0] * no_of_processes
					SCREAMING_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))
										SCREAMING_SNAKE_CASE_    ,SCREAMING_SNAKE_CASE_        =      map(int, input().split())

					SCREAMING_SNAKE_CASE_        =      calculate_waitingtime(arrival_time, burst_time, no_of_processes)

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

					calculate_average_times(waiting_time, turn_around_time, no_of_processes)

					SCREAMING_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)


