




"""simple docstring"""

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


UpperCamelCase__			:     List[str]			       =				logging.get_logger(__name__)

UpperCamelCase__			:     Optional[int]			       =				{
    "facebook/opt-125m": "https://huggingface.co/facebook/opt-125m/blob/main/config.json",
    "facebook/opt-350m": "https://huggingface.co/facebook/opt-350m/blob/main/config.json",
    "facebook/opt-1.3b": "https://huggingface.co/facebook/opt-1.3b/blob/main/config.json",
    "facebook/opt-2.7b": "https://huggingface.co/facebook/opt-2.7b/blob/main/config.json",
    "facebook/opt-6.7b": "https://huggingface.co/facebook/opt-6.7b/blob/main/config.json",
    "facebook/opt-13b": "https://huggingface.co/facebook/opt-13b/blob/main/config.json",
}
class      A__   (   lowercase_  ):
	A_				:					Tuple      =   """opt"""
	A_				:					Union[str, Any]      =   ["""past_key_values"""]




	def __init__( self	:						Optional[int]   ,     lowercase	:						Optional[int]=50_272   ,     lowercase	:						Optional[int]=768   ,     lowercase	:						Any=12   ,     lowercase	:						Dict=3_072   ,     lowercase	:						Union[str, Any]=2_048   ,     lowercase	:						Optional[int]=True   ,     lowercase	:						Tuple=False   ,     lowercase	:						Optional[Any]=None   ,     lowercase	:						Dict=0.1   ,     lowercase	:						Dict=0.0   ,     lowercase	:						Any=12   ,     lowercase	:						Tuple="relu"   ,     lowercase	:						str=0.0   ,     lowercase	:						Tuple=0.02   ,     lowercase	:						List[Any]=True   ,     lowercase	:						Any=1   ,     lowercase	:						List[Any]=2   ,     lowercase	:						Any=2   ,     lowercase	:						List[str]=True   ,     lowercase	:						Tuple=True   ,     **lowercase	:						int   ,     )       ->			Dict:
						super().__init__(
						    pad_token_id=lowercase   ,     bos_token_id=lowercase   ,     eos_token_id=lowercase   ,     **lowercase   ,     )
						__snake_case        =						vocab_size
						__snake_case        =						max_position_embeddings
						__snake_case        =						num_attention_heads
						__snake_case        =						word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
						__snake_case        =						ffn_dim
						__snake_case        =						hidden_size
						__snake_case        =						num_hidden_layers
						__snake_case        =						dropout
						__snake_case        =						attention_dropout
						__snake_case        =						activation_function
						__snake_case        =						init_std
						__snake_case        =						layerdrop
						__snake_case        =						use_cache
						__snake_case        =						do_layer_norm_before
						# We keep these variables at `True` for backward compatibility.
						__snake_case        =						enable_bias
						__snake_case        =						layer_norm_elementwise_affine

						# Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
						# with checkpoints that have been fine-tuned before transformers v4.20.1
						# see https://github.com/facebookresearch/metaseq/pull/164
						__snake_case        =						_remove_final_layer_norm








"""simple docstring"""

from __future__ import annotations




def    snake_case__						(							lowerCAmelCase :		list[int]		):
					__snake_case        =						[0] * len(lowerCAmelCase		)
					for i in range(1					,       len(lowerCAmelCase		)		):
										__snake_case        =						duration_times[i - 1] + waiting_times[i - 1]
					return waiting_times




def    snake_case__						(							lowerCAmelCase :		list[int]					,       lowerCAmelCase :		list[int]		):
					return [
					    duration_time + waiting_times[i]
					    for i, duration_time in enumerate(lowerCAmelCase		)
					]




def    snake_case__						(							lowerCAmelCase :		list[int]		):
					return sum(lowerCAmelCase		) / len(lowerCAmelCase		)




def    snake_case__						(							lowerCAmelCase :		list[int]		):
					return sum(lowerCAmelCase		) / len(lowerCAmelCase		)


if __name__ == "__main__":
		# process id's
		UpperCamelCase__			:     str			       =				[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__			:     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[int]			       =				calculate_waiting_times(duration_times)
		UpperCamelCase__			:     Any			       =				calculate_turnaround_times(duration_times, waiting_times)

		# get the average times
		UpperCamelCase__			:     Optional[Any]			       =				calculate_average_waiting_time(waiting_times)
		UpperCamelCase__			:     Dict			       =				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}')


