
'''simple docstring'''

from __future__ import annotations







def 					A       ( UpperCamelCase_   :       Union[str, Any] )   ->    list[int]:







			'''simple docstring'''



			lowerCAmelCase__									=							[0] * len(A__ )
			for i in range(1  ,		len(A__ ) ):
						lowerCAmelCase__									=							duration_times[i - 1] + waiting_times[i - 1]
			return waiting_times







def 					A       ( UpperCamelCase_   :       List[Any]  ,		UpperCamelCase_   :       Optional[Any] )   ->    list[int]:







			'''simple docstring'''



			return [
			    duration_time + waiting_times[i]
			    for i, duration_time in enumerate(A__ )
			]







def 					A       ( UpperCamelCase_   :       Optional[int] )   ->    float:







			'''simple docstring'''



			return sum(A__ ) / len(A__ )







def 					A       ( UpperCamelCase_   :       List[str] )   ->    float:







			'''simple docstring'''



			return sum(A__ ) / len(A__ )


if __name__ == "__main__":
		# process id's
		UpperCAmelCase__				:	Any					=						[1, 2, 3]

		# ensure that we actually have processes
		if len(processes) == 0:
				print("Zero amount of processes")
				raise SystemExit(0)

		# duration time of all processes
		UpperCAmelCase__				:	Optional[Any]					=						[19, 8, 9]

		# ensure we can match each id to a duration time
		if len(duration_times) != len(processes):
				print("Unable to match all id\'s with their duration time")
				raise SystemExit(0)

		# get the waiting times and the turnaround times
		UpperCAmelCase__				:	Optional[Any]					=						calculate_waiting_times(duration_times)
		UpperCAmelCase__				:	Any					=						calculate_turnaround_times(duration_times, waiting_times)

		# get the average times
		UpperCAmelCase__				:	List[str]					=						calculate_average_waiting_time(waiting_times)
		UpperCAmelCase__				:	List[str]					=						calculate_average_turnaround_time(turnaround_times)

		# print all the results
		print("Process ID\tDuration Time\tWaiting Time\tTurnaround Time")
		for i, process in enumerate(processes):
				print(
				    F"{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t"
				    F"{turnaround_times[i]}"
				)
		print(F"Average waiting time = {average_waiting_time}")
		print(F"Average turn around time = {average_turnaround_time}")







'''simple docstring'''

# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    "--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000"
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/





