

"""simple docstring"""




from statistics import mean

import numpy as np
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  Any					   =					0
 # Number of processes finished
 UpperCAmelCase__					:  int					   =					0
 # Displays the finished process.
 # If it is 0, the performance is completed if it is 1, before the performance.
 UpperCAmelCase__					:  Optional[Any]					   =					[0] * no_of_process
 # List to include calculation results
 UpperCAmelCase__					:  int					   =					[0] * no_of_process

 # Sort by arrival time.
 UpperCAmelCase__					:  int					   =					[burst_time[i] for i in np.argsort(__UpperCamelCase      )]
 UpperCAmelCase__					:  Union[str, Any]					   =					[process_name[i] for i in np.argsort(__UpperCamelCase      )]
 arrival_time.sort()

 while no_of_process > finished_process_count:
  UpperCAmelCase__					:  List[str]					   =					0
  while finished_process[i] == 1:
   i += 1
  if current_time < arrival_time[i]:
   UpperCAmelCase__					:  Tuple					   =					arrival_time[i]

  UpperCAmelCase__					:  str					   =					0
  # Index showing the location of the process being performed
  UpperCAmelCase__					:  Tuple					   =					0
  # Saves the current response ratio.
  UpperCAmelCase__					:  Optional[Any]					   =					0
  for i in range(0							,    __UpperCamelCase      ):
   if finished_process[i] == 0 and arrival_time[i] <= current_time:
    UpperCAmelCase__					:  List[Any]					   =					(burst_time[i] + (current_time - arrival_time[i])) / burst_time[
        i
    ]
   if response_ratio < temp:
    UpperCAmelCase__					:  List[str]					   =					temp
    UpperCAmelCase__					:  List[str]					   =					i

        # Calculate the turn around time
  UpperCAmelCase__					:  int					   =					current_time + burst_time[loc] - arrival_time[loc]
  current_time += burst_time[loc]
  # Indicates that the process has been performed.
  UpperCAmelCase__					:  Optional[int]					   =					1
  # Increase finished_process_count by 1
  finished_process_count += 1

 return turn_around_time
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  List[str]					   =					[0] * no_of_process
 for i in range(0							,    __UpperCamelCase      ):
  UpperCAmelCase__					:  Tuple					   =					turn_around_time[i] - burst_time[i]
 return waiting_time


if __name__ == "__main__":
      __UpperCAmelCase =				5
      __UpperCAmelCase =				['A', 'B', 'C', 'D', 'E']
      __UpperCAmelCase =				[1, 2, 3, 4, 5]
      __UpperCAmelCase =				[1, 2, 3, 4, 5]

      __UpperCAmelCase =				calculate_turn_around_time(
          process_name, arrival_time, burst_time, no_of_process
      )
      __UpperCAmelCase =				calculate_waiting_time(
          process_name, turn_around_time, burst_time, no_of_process
      )

      print('Process name \tArrival time \tBurst time \tTurn around time \tWaiting time')
      for i in range(0, no_of_process):
            print(
                F"{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t"
                F"{turn_around_time[i]}\t\t\t{waiting_time[i]}"
            )

      print(F"average waiting time : {mean(waiting_time):.5f}")
      print(F"average turn around time : {mean(turn_around_time):.5f}")








"""simple docstring"""




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


__UpperCAmelCase =				logging.get_logger(__name__)

__UpperCAmelCase =				{
    'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
    'microsoft/markuplm-large': 'https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json',
}







class      __lowercase			(    __lowerCamelCase					):
  snake_case_				       =       """markuplm"""

  def __init__(  self		:			str					,A		:			List[Any]=30_522					,A		:			Tuple=768					,A		:			str=12					,A		:			int=12					,A		:			int=3_072					,A		:			Optional[int]="gelu"					,A		:			Optional[int]=0.1					,A		:			Optional[int]=0.1					,A		:			Any=512					,A		:			Any=2					,A		:			str=0.0_2					,A		:			int=1e-12					,A		:			int=0					,A		:			str=0					,A		:			List[Any]=2					,A		:			List[str]=256					,A		:			Union[str, Any]=1_024					,A		:			List[Any]=216					,A		:			Any=1_001					,A		:			Optional[int]=32					,A		:			Any=50					,A		:			int="absolute"					,A		:			Dict=True					,A		:			int=None					,**A		:			Optional[int]					,):






   '''simple docstring'''
   super().__init__(
       pad_token_id=A					,bos_token_id=A					,eos_token_id=A					,**A					,)
   UpperCAmelCase__					:  Dict					   =					vocab_size
   UpperCAmelCase__					:  Union[str, Any]					   =					hidden_size
   UpperCAmelCase__					:  Optional[int]					   =					num_hidden_layers
   UpperCAmelCase__					:  Tuple					   =					num_attention_heads
   UpperCAmelCase__					:  Optional[Any]					   =					hidden_act
   UpperCAmelCase__					:  Any					   =					intermediate_size
   UpperCAmelCase__					:  Dict					   =					hidden_dropout_prob
   UpperCAmelCase__					:  Optional[Any]					   =					attention_probs_dropout_prob
   UpperCAmelCase__					:  Optional[int]					   =					max_position_embeddings
   UpperCAmelCase__					:  Dict					   =					type_vocab_size
   UpperCAmelCase__					:  Optional[Any]					   =					initializer_range
   UpperCAmelCase__					:  str					   =					layer_norm_eps
   UpperCAmelCase__					:  Any					   =					position_embedding_type
   UpperCAmelCase__					:  int					   =					use_cache
   UpperCAmelCase__					:  List[str]					   =					classifier_dropout
   # additional properties
   UpperCAmelCase__					:  Optional[int]					   =					max_depth
   UpperCAmelCase__					:  List[str]					   =					max_xpath_tag_unit_embeddings
   UpperCAmelCase__					:  Any					   =					max_xpath_subs_unit_embeddings
   UpperCAmelCase__					:  str					   =					tag_pad_id
   UpperCAmelCase__					:  Dict					   =					subs_pad_id
   UpperCAmelCase__					:  List[str]					   =					xpath_unit_hidden_size





