




"""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}')








"""simple docstring"""

import copy

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


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

UpperCamelCase__			:     List[str]			       =				{}
class      A__   (   lowercase_  ):
	A_				:					Dict      =   """fsmt_decoder"""




	def __init__( self	:						List[Any]   ,     lowercase	:						Any=0   ,     lowercase	:						Dict=0						)       ->			str:
						super().__init__()
						__snake_case        =						vocab_size
						__snake_case        =						bos_token_id

class      A__   (   lowercase_  ):
	A_				:					Union[str, Any]      =   """fsmt"""
	A_				:					int      =   {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}




	def __init__( self	:						Optional[Any]   ,     lowercase	:						Any=["en", "de"]   ,     lowercase	:						Optional[int]=42_024   ,     lowercase	:						Optional[int]=42_024   ,     lowercase	:						Tuple="relu"   ,     lowercase	:						Tuple=1_024   ,     lowercase	:						Union[str, Any]=200   ,     lowercase	:						List[str]=1_024   ,     lowercase	:						Tuple=4_096   ,     lowercase	:						int=12   ,     lowercase	:						Any=16   ,     lowercase	:						List[Any]=0.0   ,     lowercase	:						str=4_096   ,     lowercase	:						str=12   ,     lowercase	:						Optional[int]=16   ,     lowercase	:						Dict=0.0   ,     lowercase	:						Any=0.0   ,     lowercase	:						Union[str, Any]=0.1   ,     lowercase	:						Tuple=0.0   ,     lowercase	:						List[str]=0.02   ,     lowercase	:						int=2   ,     lowercase	:						Any=True   ,     lowercase	:						int=True   ,     lowercase	:						int=False   ,     lowercase	:						List[str]=5   ,     lowercase	:						List[Any]=1.0   ,     lowercase	:						Union[str, Any]=False   ,     lowercase	:						Optional[Any]=True   ,     lowercase	:						int=1   ,     lowercase	:						Any=0   ,     lowercase	:						Optional[Any]=2   ,     lowercase	:						Any=2   ,     **lowercase	:						List[Any]   ,     )       ->			Union[str, Any]:
						__snake_case        =						langs
						__snake_case        =						src_vocab_size
						__snake_case        =						tgt_vocab_size
						__snake_case        =						d_model  # encoder_embed_dim and decoder_embed_dim

						__snake_case        =						encoder_ffn_dim
						__snake_case        =						__snake_case        =						encoder_layers
						__snake_case        =						encoder_attention_heads
						__snake_case        =						encoder_layerdrop
						__snake_case        =						decoder_layerdrop
						__snake_case        =						decoder_ffn_dim
						__snake_case        =						decoder_layers
						__snake_case        =						decoder_attention_heads
						__snake_case        =						max_position_embeddings
						__snake_case        =						init_std  # Normal(0, this parameter)
						__snake_case        =						activation_function

						__snake_case        =						DecoderConfig(vocab_size=lowercase   ,     bos_token_id=lowercase						)
						if "decoder" in common_kwargs:
											del common_kwargs["decoder"]

						__snake_case        =						scale_embedding  # scale factor will be sqrt(d_model) if True

						# 3 Types of Dropout
						__snake_case        =						attention_dropout
						__snake_case        =						activation_dropout
						__snake_case        =						dropout

						__snake_case        =						use_cache
						super().__init__(
						    pad_token_id=lowercase   ,     bos_token_id=lowercase   ,     eos_token_id=lowercase   ,     decoder_start_token_id=lowercase   ,     is_encoder_decoder=lowercase   ,     tie_word_embeddings=lowercase   ,     forced_eos_token_id=lowercase   ,     max_length=lowercase   ,     num_beams=lowercase   ,     length_penalty=lowercase   ,     early_stopping=lowercase   ,     **lowercase   ,     )




	def 				a_		( self	:						Union[str, Any]						)       ->			Dict:
						__snake_case        =						copy.deepcopy(self.__dict__						)
						__snake_case        =						self.decoder.to_dict()
						__snake_case        =						self.__class__.model_type
						return output


