





'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase            =       logging.get_logger(__name__)

__UpperCAmelCase            =       {
    """EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json""",
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}




class      UpperCamelCase__					(					lowercase_			):




					"""simple docstring"""
					SCREAMING_SNAKE_CASE__				=	'''gpt_neox'''


					def __init__(						self				:			int      ,						lowerCamelCase_				:			Dict=5_04_32      ,						lowerCamelCase_				:			Tuple=61_44      ,						lowerCamelCase_				:			Any=44      ,						lowerCamelCase_				:			Optional[int]=64      ,						lowerCamelCase_				:			List[str]=2_45_76      ,						lowerCamelCase_				:			Tuple="gelu"      ,						lowerCamelCase_				:			Tuple=0.25      ,						lowerCamelCase_				:			Optional[int]=1_00_00      ,						lowerCamelCase_				:			Dict=0.0      ,						lowerCamelCase_				:			int=0.0      ,						lowerCamelCase_				:			Union[str, Any]=0.1      ,						lowerCamelCase_				:			str=20_48      ,						lowerCamelCase_				:			List[str]=0.02      ,						lowerCamelCase_				:			str=1e-5      ,						lowerCamelCase_				:			List[Any]=True      ,						lowerCamelCase_				:			str=0      ,						lowerCamelCase_				:			Dict=2      ,						lowerCamelCase_				:			Any=False      ,						lowerCamelCase_				:			Optional[int]=True      ,						lowerCamelCase_				:			Dict=None      ,						**lowerCamelCase_				:			Tuple      ,						):

							'''simple docstring'''



							super().__init__(bos_token_id=lowerCamelCase_      ,						eos_token_id=lowerCamelCase_      ,						**lowerCamelCase_						)
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			vocab_size
							SCREAMING_SNAKE_CASE :				Dict		=			max_position_embeddings
							SCREAMING_SNAKE_CASE :				List[str]		=			hidden_size
							SCREAMING_SNAKE_CASE :				Tuple		=			num_hidden_layers
							SCREAMING_SNAKE_CASE :				int		=			num_attention_heads
							SCREAMING_SNAKE_CASE :				int		=			intermediate_size
							SCREAMING_SNAKE_CASE :				Dict		=			hidden_act
							SCREAMING_SNAKE_CASE :				Optional[Any]		=			rotary_pct
							SCREAMING_SNAKE_CASE :				List[str]		=			rotary_emb_base
							SCREAMING_SNAKE_CASE :				str		=			attention_dropout
							SCREAMING_SNAKE_CASE :				Dict		=			hidden_dropout
							SCREAMING_SNAKE_CASE :				Any		=			classifier_dropout
							SCREAMING_SNAKE_CASE :				List[Any]		=			initializer_range
							SCREAMING_SNAKE_CASE :				Any		=			layer_norm_eps
							SCREAMING_SNAKE_CASE :				Tuple		=			use_cache
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			tie_word_embeddings
							SCREAMING_SNAKE_CASE :				Tuple		=			use_parallel_residual
							SCREAMING_SNAKE_CASE :				str		=			rope_scaling
							self._rope_scaling_validation()

							if self.hidden_size % self.num_attention_heads != 0:
									raise ValueError(
									    """The hidden size is not divisble by the number of attention heads! Make sure to update them!"""						)



					def lowerCamelCase_			(						self				:			List[Any]						):

							'''simple docstring'''



							if self.rope_scaling is None:
									return

							if not isinstance(self.rope_scaling      ,						lowerCamelCase_						) or len(self.rope_scaling						) != 2:
									raise ValueError(
									    """`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, """
									    f'''got {self.rope_scaling}'''						)
							SCREAMING_SNAKE_CASE :				str		=			self.rope_scaling.get("""type"""      ,						lowerCamelCase_						)
							SCREAMING_SNAKE_CASE :				List[Any]		=			self.rope_scaling.get("""factor"""      ,						lowerCamelCase_						)
							if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
									raise ValueError(
									    f'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''						)
							if rope_scaling_factor is None or not isinstance(lowerCamelCase_      ,						lowerCamelCase_						) or rope_scaling_factor <= 1.0:
									raise ValueError(f'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''						)










'''simple docstring'''




from __future__ import annotations

from statistics import mean



def 		__A		(  lowerCamelCase_			,			lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				List[Any]		=			[0] * no_of_processes
		SCREAMING_SNAKE_CASE :				int		=			[0] * no_of_processes

		# Initialize remaining_time to waiting_time.

		for i in range(lowerCamelCase_	):
				SCREAMING_SNAKE_CASE :				Optional[int]		=			burst_time[i]
		SCREAMING_SNAKE_CASE :				list[int]		=			[]

		SCREAMING_SNAKE_CASE :				List[str]		=			0
		SCREAMING_SNAKE_CASE :				List[Any]		=			0

		# When processes are not completed,
		# A process whose arrival time has passed \
		# and has remaining execution time is put into the ready_process.
		# The shortest process in the ready_process, target_process is executed.

		while completed != no_of_processes:
				SCREAMING_SNAKE_CASE :				Optional[int]		=			[]
				SCREAMING_SNAKE_CASE :				Any		=			-1

				for i in range(lowerCamelCase_	):
						if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
								ready_process.append(lowerCamelCase_	)

				if len(lowerCamelCase_	) > 0:
						SCREAMING_SNAKE_CASE :				Union[str, Any]		=			ready_process[0]
						for i in ready_process:
								if remaining_time[i] < remaining_time[target_process]:
										SCREAMING_SNAKE_CASE :				Any		=			i
						total_time += burst_time[target_process]
						completed += 1
						SCREAMING_SNAKE_CASE :				Any		=			0
						SCREAMING_SNAKE_CASE :				Optional[int]		=			(
						    total_time - arrival_time[target_process] - burst_time[target_process]
						)
				else:
						total_time += 1

		return waiting_time



def 		__A		(  lowerCamelCase_			,			lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Any		=			[0] * no_of_processes
		for i in range(lowerCamelCase_	):
				SCREAMING_SNAKE_CASE :				Union[str, Any]		=			burst_time[i] + waiting_time[i]
		return turn_around_time


if __name__ == "__main__":
							print("""[TEST CASE 01]""")

							__UpperCAmelCase            =       4
							__UpperCAmelCase            =       [2, 5, 3, 7]
							__UpperCAmelCase            =       [0, 0, 0, 0]
							__UpperCAmelCase            =       calculate_waitingtime(arrival_time, burst_time, no_of_processes)
							__UpperCAmelCase            =       calculate_turnaroundtime(
							    burst_time, no_of_processes, waiting_time
							)

							# Printing the Result
							print("""PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time""")
							for i, process_id in enumerate(list(range(1, 5))):
														print(
														    f'''{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t'''
														    f'''{waiting_time[i]}\t\t\t\t{turn_around_time[i]}'''
														)
							print(f'''\nAverage waiting time = {mean(waiting_time):.5f}''')
							print(f'''Average turnaround time = {mean(turn_around_time):.5f}''')



