




'''simple docstring'''

from collections import OrderedDict
from typing import List, Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a       :						Dict								=		logging.get_logger(__name__)

a       :						Union[str, Any]								=		{
    '''google/efficientnet-b7''': '''https://huggingface.co/google/efficientnet-b7/resolve/main/config.json''',
}



class 		SCREAMING_SNAKE_CASE__  (			_UpperCamelCase	):
			__SCREAMING_SNAKE_CASE    =			"""efficientnet"""





			def __init__(      self						:    Optional[int]      ,		a_						:    int = 3      ,		a_						:    int = 600      ,		a_						:    float = 2.0      ,		a_						:    float = 3.1      ,		a_						:    int = 8      ,		a_						:    List[int] = [3, 3, 5, 3, 5, 5, 3]      ,		a_						:    List[int] = [32, 16, 24, 40, 80, 112, 192]      ,		a_						:    List[int] = [16, 24, 40, 80, 112, 192, 320]      ,		a_						:    List[int] = []      ,		a_						:    List[int] = [1, 2, 2, 2, 1, 2, 1]      ,		a_						:    List[int] = [1, 2, 2, 3, 3, 4, 1]      ,		a_						:    List[int] = [1, 6, 6, 6, 6, 6, 6]      ,		a_						:    float = 0.25      ,		a_						:    str = "swish"      ,		a_						:    int = 2_560      ,		a_						:    str = "mean"      ,		a_						:    float = 0.02      ,		a_						:    float = 0.001      ,		a_						:    float = 0.99      ,		a_						:    float = 0.5      ,		a_						:    float = 0.2      ,		**a_						:    Union[str, Any]      ,		):



						"""simple docstring"""




						super().__init__(**a_							)

						__snake_case			=		num_channels
						__snake_case			=		image_size
						__snake_case			=		width_coefficient
						__snake_case			=		depth_coefficient
						__snake_case			=		depth_divisor
						__snake_case			=		kernel_sizes
						__snake_case			=		in_channels
						__snake_case			=		out_channels
						__snake_case			=		depthwise_padding
						__snake_case			=		strides
						__snake_case			=		num_block_repeats
						__snake_case			=		expand_ratios
						__snake_case			=		squeeze_expansion_ratio
						__snake_case			=		hidden_act
						__snake_case			=		hidden_dim
						__snake_case			=		pooling_type
						__snake_case			=		initializer_range
						__snake_case			=		batch_norm_eps
						__snake_case			=		batch_norm_momentum
						__snake_case			=		dropout_rate
						__snake_case			=		drop_connect_rate
						__snake_case			=		sum(a_							) * 4







class 		SCREAMING_SNAKE_CASE__  (			_UpperCamelCase	):
			__SCREAMING_SNAKE_CASE    =			version.parse("""1.11"""	)





			@property
			def 							A (      self						:    str							):



						"""simple docstring"""




						return OrderedDict(
						    [
						        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
						    ]							)






			@property
			def 							A (      self						:    List[str]							):



						"""simple docstring"""




						return 1e-5









from __future__ import annotations

from statistics import mean







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase							,   __lowerCAmelCase							,   __lowerCAmelCase				)    ->				list[int]:
  snake_case__						= [0] * no_of_processes
  snake_case__						= [0] * no_of_processes

  # Initialize remaining_time to waiting_time.

  for i in range(__lowerCAmelCase				):
    snake_case__						= burst_time[i]
  snake_case__						= []

  snake_case__						= 0
  snake_case__						= 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:
    snake_case__						= []
    snake_case__						= -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:
      snake_case__						= ready_process[0]
      for i in ready_process:
        if remaining_time[i] < remaining_time[target_process]:
          snake_case__						= i
      total_time += burst_time[target_process]
      completed += 1
      snake_case__						= 0
      snake_case__						= (
          total_time - arrival_time[target_process] - burst_time[target_process]
      )
    else:
      total_time += 1

  return waiting_time







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase							,   __lowerCAmelCase							,   __lowerCAmelCase				)    ->				list[int]:
  snake_case__						= [0] * no_of_processes
  for i in range(__lowerCAmelCase				):
    snake_case__						= burst_time[i] + waiting_time[i]
  return turn_around_time


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

   lowerCamelCase__							:						Tuple							     =   4
   lowerCamelCase__							:						Union[str, Any]							     =   [2, 5, 3, 7]
   lowerCamelCase__							:						Optional[Any]							     =   [0, 0, 0, 0]
   lowerCamelCase__							:						Dict							     =   calculate_waitingtime(arrival_time, burst_time, no_of_processes)
   lowerCamelCase__							:						Union[str, Any]							     =   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}""")

