






'''simple docstring'''







from __future__ import annotations

from statistics import mean





def  SCREAMING_SNAKE_CASE_       (UpperCamelCase				,			UpperCamelCase				,			UpperCamelCase      )      ->       list[int]:
							lowerCamelCase__					:	Any         =       [0] * no_of_processes
							lowerCamelCase__					:	Optional[int]         =       [0] * no_of_processes

							# Initialize remaining_time to waiting_time.

							for i in range(UpperCamelCase      ):
														lowerCamelCase__					:	Optional[Any]         =       burst_time[i]
							lowerCamelCase__					:	list[int]         =       []

							lowerCamelCase__					:	List[Any]         =       0
							lowerCamelCase__					:	Tuple         =       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:
														lowerCamelCase__					:	int         =       []
														lowerCamelCase__					:	Optional[int]         =       -1

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

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

							return waiting_time





def  SCREAMING_SNAKE_CASE_       (UpperCamelCase				,			UpperCamelCase				,			UpperCamelCase      )      ->       list[int]:
							lowerCamelCase__					:	Optional[int]         =       [0] * no_of_processes
							for i in range(UpperCamelCase      ):
														lowerCamelCase__					:	int         =       burst_time[i] + waiting_time[i]
							return turn_around_time


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

			_A	:			int         =4
			_A	:			Any         =[2, 5, 3, 7]
			_A	:			Dict         =[0, 0, 0, 0]
			_A	:			int         =calculate_waitingtime(arrival_time, burst_time, no_of_processes)
			_A	:			int         =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}')





"""simple docstring"""







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


lowerCAmelCase__      				=   logging.get_logger(__name__)

lowerCAmelCase__      				=   {}


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				str   ="llama"
       a  :				List[str]   =["past_key_values"]

       def __init__(						self		,     snake_case__=32_000		,     snake_case__=4_096		,     snake_case__=11_008		,     snake_case__=32		,     snake_case__=32		,     snake_case__=None		,     snake_case__="silu"		,     snake_case__=2_048		,     snake_case__=0.02		,     snake_case__=1e-6		,     snake_case__=True		,     snake_case__=0		,     snake_case__=1		,     snake_case__=2		,     snake_case__=1		,     snake_case__=False		,     snake_case__=None		,     **snake_case__		,     ):






         """simple docstring"""





         lowerCAmelCase     :     Optional[Any]								=							vocab_size
         lowerCAmelCase     :     str								=							max_position_embeddings
         lowerCAmelCase     :     str								=							hidden_size
         lowerCAmelCase     :     Optional[int]								=							intermediate_size
         lowerCAmelCase     :     Any								=							num_hidden_layers
         lowerCAmelCase     :     List[str]								=							num_attention_heads

         # for backward compatibility
         if num_key_value_heads is None:
           lowerCAmelCase     :     Tuple								=							num_attention_heads

         lowerCAmelCase     :     Dict								=							num_key_value_heads
         lowerCAmelCase     :     Optional[Any]								=							hidden_act
         lowerCAmelCase     :     Optional[Any]								=							initializer_range
         lowerCAmelCase     :     Any								=							rms_norm_eps
         lowerCAmelCase     :     List[Any]								=							pretraining_tp
         lowerCAmelCase     :     int								=							use_cache
         lowerCAmelCase     :     List[str]								=							rope_scaling
         self._rope_scaling_validation()

         super().__init__(
             pad_token_id=snake_case__		,     bos_token_id=snake_case__		,     eos_token_id=snake_case__		,     tie_word_embeddings=snake_case__		,     **snake_case__		,     )







       def        lowercase__							(						self						):






         """simple docstring"""





         if self.rope_scaling is None:
           return

         if not isinstance(self.rope_scaling		,     snake_case__						) 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}"""						)
         lowerCAmelCase     :     Optional[Any]								=							self.rope_scaling.get("type"		,     snake_case__						)
         lowerCAmelCase     :     int								=							self.rope_scaling.get("factor"		,     snake_case__						)
         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(snake_case__		,     snake_case__						) or rope_scaling_factor <= 1.0:
           raise ValueError(f"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"""						)





