



"""simple docstring"""







from statistics import mean

import numpy as np

def       _lowerCamelCase				(							UpperCAmelCase_ :       list,	UpperCAmelCase_ :       list,	UpperCAmelCase_ :       list,	UpperCAmelCase_ :       int     )	-> list:






	"""simple docstring"""





	A__											=					0
	# Number of processes finished
	A__											=					0
	# Displays the finished process.
	# If it is 0, the performance is completed if it is 1, before the performance.
	A__											=					[0] * no_of_process
	# List to include calculation results
	A__											=					[0] * no_of_process

	# Sort by arrival time.
	A__											=					[burst_time[i] for i in np.argsort(UpperCAmelCase_     )]
	A__											=					[process_name[i] for i in np.argsort(UpperCAmelCase_     )]
	arrival_time.sort()

	while no_of_process > finished_process_count:
		A__											=					0
		while finished_process[i] == 1:
			i += 1
		if current_time < arrival_time[i]:
			A__											=					arrival_time[i]

		A__											=					0
		# Index showing the location of the process being performed
		A__											=					0
		# Saves the current response ratio.
		A__											=					0
		for i in range(0,	UpperCAmelCase_     ):
			if finished_process[i] == 0 and arrival_time[i] <= current_time:
				A__											=					(burst_time[i] + (current_time - arrival_time[i])) / burst_time[
				    i
				]
			if response_ratio < temp:
				A__											=					temp
				A__											=					i

        # Calculate the turn around time
		A__											=					current_time + burst_time[loc] - arrival_time[loc]
		current_time += burst_time[loc]
		# Indicates that the process has been performed.
		A__											=					1
		# Increase finished_process_count by 1
		finished_process_count += 1

	return turn_around_time

def       _lowerCamelCase				(							UpperCAmelCase_ :       list,	UpperCAmelCase_ :       list,	UpperCAmelCase_ :       list,	UpperCAmelCase_ :       int     )	-> list:






	"""simple docstring"""





	A__											=					[0] * no_of_process
	for i in range(0,	UpperCAmelCase_     ):
		A__											=					turn_around_time[i] - burst_time[i]
	return waiting_time


if __name__ == "__main__":
			UpperCamelCase     =							5
			UpperCamelCase     =							["""A""", """B""", """C""", """D""", """E"""]
			UpperCamelCase     =							[1, 2, 3, 4, 5]
			UpperCamelCase     =							[1, 2, 3, 4, 5]

			UpperCamelCase     =							calculate_turn_around_time(
			    process_name, arrival_time, burst_time, no_of_process
			)
			UpperCamelCase     =							calculate_waiting_time(
			    process_name, turn_around_time, burst_time, no_of_process
			)

			print("""Process name \tArrival time \tBurst time \tTurn around time \tWaiting time""")
			for i in range(0, no_of_process):
						print(
						    f'{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'
						    f'{turn_around_time[i]}\t\t\t{waiting_time[i]}'
						)

			print(f'average waiting time : {mean(waiting_time):.5f}')
			print(f'average turn around time : {mean(turn_around_time):.5f}')









"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase     =							{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase     =							[
			    """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """WavLMForAudioFrameClassification""",
			    """WavLMForCTC""",
			    """WavLMForSequenceClassification""",
			    """WavLMForXVector""",
			    """WavLMModel""",
			    """WavLMPreTrainedModel""",
			]

if TYPE_CHECKING:
			from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_wavlm import (
						    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
						    WavLMForAudioFrameClassification,
						    WavLMForCTC,
						    WavLMForSequenceClassification,
						    WavLMForXVector,
						    WavLMModel,
						    WavLMPreTrainedModel,
						)

else:
			import sys

			UpperCamelCase     =							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




