'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from packaging import version

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


__lowerCAmelCase	:       int						       =	logging.get_logger(__name__)

__lowerCAmelCase	:       List[Any]						       =	{
    "microsoft/beit-base-patch16-224-pt22k": (
        "https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}






class 						A   (   UpperCAmelCase   ):
							a_        =      '''beit'''





							def __init__(      self				:							Any     ,		__a				:							int=8_1_9_2     ,		__a				:							Optional[Any]=7_6_8     ,		__a				:							Optional[Any]=1_2     ,		__a				:							Any=1_2     ,		__a				:							List[str]=3_0_7_2     ,		__a				:							str="gelu"     ,		__a				:							Union[str, Any]=0.0     ,		__a				:							Tuple=0.0     ,		__a				:							Optional[int]=0.0_2     ,		__a				:							Union[str, Any]=1e-12     ,		__a				:							str=2_2_4     ,		__a				:							Tuple=1_6     ,		__a				:							Union[str, Any]=3     ,		__a				:							Union[str, Any]=False     ,		__a				:							List[str]=False     ,		__a				:							int=False     ,		__a				:							Union[str, Any]=False     ,		__a				:							Any=0.1     ,		__a				:							Any=0.1     ,		__a				:							List[Any]=True     ,		__a				:							Optional[int]=[3, 5, 7, 1_1]     ,		__a				:							Any=[1, 2, 3, 6]     ,		__a				:							str=True     ,		__a				:							Optional[int]=0.4     ,		__a				:							List[Any]=2_5_6     ,		__a				:							List[Any]=1     ,		__a				:							str=False     ,		__a				:							Any=2_5_5     ,		**__a				:							Optional[Any]     ,		)							->	Union[str, Any]:
								super().__init__(**__a	)

								__UpperCAmelCase							=			vocab_size
								__UpperCAmelCase							=			hidden_size
								__UpperCAmelCase							=			num_hidden_layers
								__UpperCAmelCase							=			num_attention_heads
								__UpperCAmelCase							=			intermediate_size
								__UpperCAmelCase							=			hidden_act
								__UpperCAmelCase							=			hidden_dropout_prob
								__UpperCAmelCase							=			attention_probs_dropout_prob
								__UpperCAmelCase							=			initializer_range
								__UpperCAmelCase							=			layer_norm_eps

								__UpperCAmelCase							=			image_size
								__UpperCAmelCase							=			patch_size
								__UpperCAmelCase							=			num_channels
								__UpperCAmelCase							=			use_mask_token
								__UpperCAmelCase							=			use_absolute_position_embeddings
								__UpperCAmelCase							=			use_relative_position_bias
								__UpperCAmelCase							=			use_shared_relative_position_bias
								__UpperCAmelCase							=			layer_scale_init_value
								__UpperCAmelCase							=			drop_path_rate
								__UpperCAmelCase							=			use_mean_pooling
								# decode head attributes (semantic segmentation)
								__UpperCAmelCase							=			out_indices
								__UpperCAmelCase							=			pool_scales
								# auxiliary head attributes (semantic segmentation)
								__UpperCAmelCase							=			use_auxiliary_head
								__UpperCAmelCase							=			auxiliary_loss_weight
								__UpperCAmelCase							=			auxiliary_channels
								__UpperCAmelCase							=			auxiliary_num_convs
								__UpperCAmelCase							=			auxiliary_concat_input
								__UpperCAmelCase							=			semantic_loss_ignore_index






class 						A   (   UpperCAmelCase   ):
							a_        =      version.parse('''1.11'''   )





							@property
							def       snake_case__						(      self				:							Tuple	)							->	Mapping[str, Mapping[int, str]]:
								return OrderedDict(
								    [
								        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
								    ]	)






							@property
							def       snake_case__						(      self				:							str	)							->	float:
								return 1e-4

'''simple docstring'''


from __future__ import annotations

from statistics import mean





def       lowerCAmelCase					(		UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   int       ):


	"""simple docstring"""
	__UpperCAmelCase							=			[0] * no_of_processes
	__UpperCAmelCase							=			[0] * no_of_processes

	# Initialize remaining_time to waiting_time.

	for i in range(UpperCamelCase__       ):
		__UpperCAmelCase							=			burst_time[i]
	__UpperCAmelCase							=			[]

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

	return waiting_time





def       lowerCAmelCase					(		UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   int    ,					UpperCamelCase__				:   list[int]       ):


	"""simple docstring"""
	__UpperCAmelCase							=			[0] * no_of_processes
	for i in range(UpperCamelCase__       ):
		__UpperCAmelCase							=			burst_time[i] + waiting_time[i]
	return turn_around_time


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

					__lowerCAmelCase	:       List[Any]						       =	4
					__lowerCAmelCase	:       List[Any]						       =	[2, 5, 3, 7]
					__lowerCAmelCase	:       Tuple						       =	[0, 0, 0, 0]
					__lowerCAmelCase	:       Optional[int]						       =	calculate_waitingtime(arrival_time, burst_time, no_of_processes)
					__lowerCAmelCase	:       Dict						       =	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}""")
