



'''simple docstring'''

import copy
from typing import Dict, List, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


UpperCAmelCase     		=   {
    'facebook/mask2former-swin-small-coco-instance': (
        'https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json'
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

UpperCAmelCase     		=   logging.get_logger(__name__)

class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						UpperCAmelCase							:   Dict									=		"mask2former"
						UpperCAmelCase							:   Union[str, Any]									=		["swin"]
						UpperCAmelCase							:   Optional[Any]									=		{"hidden_size": "hidden_dim"}


						def __init__( self     ,	A_ = None     ,	A_ = 256     ,	A_ = 256     ,	A_ = 256     ,	A_ = 1024     ,	A_ = "relu"     ,	A_ = 6     ,	A_ = 10     ,	A_ = 8     ,	A_ = 0.0     ,	A_ = 2048     ,	A_ = False     ,	A_ = False     ,	A_ = 4     ,	A_ = 255     ,	A_ = 100     ,	A_ = 0.1     ,	A_ = 2.0     ,	A_ = 5.0     ,	A_ = 5.0     ,	A_ = 1_2544     ,	A_ = 3.0     ,	A_ = 0.7_5     ,	A_ = 0.0_2     ,	A_ = 1.0     ,	A_ = True     ,	A_ = [4, 8, 16, 32]     ,	A_ = None     ,	**A_     ,	)     ->     List[Any]:
							if backbone_config is None:
								logger.info("""`backbone_config` is `None`. Initializing the config with the default `Swin` backbone."""				)
								lowerCAmelCase   =     CONFIG_MAPPING["""swin"""](
								    image_size=224     ,	in_channels=3     ,	patch_size=4     ,	embed_dim=96     ,	depths=[2, 2, 18, 2]     ,	num_heads=[3, 6, 12, 24]     ,	window_size=7     ,	drop_path_rate=0.3     ,	use_absolute_embeddings=A_     ,	out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]     ,	)

							if isinstance(A_     ,	A_				):
								lowerCAmelCase   =     backbone_config.pop("""model_type"""				)
								lowerCAmelCase   =     CONFIG_MAPPING[backbone_model_type]
								lowerCAmelCase   =     config_class.from_dict(A_				)

							# verify that the backbone is supported
							if backbone_config.model_type not in self.backbones_supported:
								logger.warning_once(
								    f'Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. '
								    f'Supported model types: {",".join(self.backbones_supported				)}'				)

							lowerCAmelCase   =     backbone_config
							lowerCAmelCase   =     feature_size
							lowerCAmelCase   =     mask_feature_size
							lowerCAmelCase   =     hidden_dim
							lowerCAmelCase   =     encoder_feedforward_dim
							lowerCAmelCase   =     activation_function
							lowerCAmelCase   =     encoder_layers
							lowerCAmelCase   =     decoder_layers
							lowerCAmelCase   =     num_attention_heads
							lowerCAmelCase   =     dropout
							lowerCAmelCase   =     dim_feedforward
							lowerCAmelCase   =     pre_norm
							lowerCAmelCase   =     enforce_input_projection
							lowerCAmelCase   =     common_stride
							lowerCAmelCase   =     ignore_value
							lowerCAmelCase   =     num_queries
							lowerCAmelCase   =     no_object_weight
							lowerCAmelCase   =     class_weight
							lowerCAmelCase   =     mask_weight
							lowerCAmelCase   =     dice_weight
							lowerCAmelCase   =     train_num_points
							lowerCAmelCase   =     oversample_ratio
							lowerCAmelCase   =     importance_sample_ratio
							lowerCAmelCase   =     init_std
							lowerCAmelCase   =     init_xavier_std
							lowerCAmelCase   =     use_auxiliary_loss
							lowerCAmelCase   =     feature_strides
							lowerCAmelCase   =     output_auxiliary_logits
							lowerCAmelCase   =     decoder_layers

							super().__init__(**A_				)


						@classmethod
						def     __snake_case   ( cls     ,	A_     ,	**A_				)     ->     Tuple:
							return cls(
							    backbone_config=A_     ,	**A_     ,	)




						def     __snake_case   ( self				)     ->     Dict[str, any]:
							lowerCAmelCase   =     copy.deepcopy(self.__dict__				)
							lowerCAmelCase   =     self.backbone_config.to_dict()
							lowerCAmelCase   =     self.__class__.model_type
							return output




'''simple docstring'''

from __future__ import annotations

import pandas as pd






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						list[int]							,		_SCREAMING_SNAKE_CASE					:						list[int]							,		_SCREAMING_SNAKE_CASE					:						int							)      ->						list[int]:







	"""simple docstring"""
	lowerCAmelCase   =     [0] * no_of_processes
	lowerCAmelCase   =     [0] * no_of_processes
	# Copy the burst time into remaining_time[]
	for i in range(_SCREAMING_SNAKE_CASE							):
		lowerCAmelCase   =     burst_time[i]

	lowerCAmelCase   =     0
	lowerCAmelCase   =     0
	lowerCAmelCase   =     999_999_999
	lowerCAmelCase   =     0
	lowerCAmelCase   =     False

	# Process until all processes are completed
	while complete != no_of_processes:
		for j in range(_SCREAMING_SNAKE_CASE							):
			if arrival_time[j] <= increment_time and remaining_time[j] > 0:
				if remaining_time[j] < minm:
					lowerCAmelCase   =     remaining_time[j]
					lowerCAmelCase   =     j
					lowerCAmelCase   =     True

		if not check:
			increment_time += 1
			continue
		remaining_time[short] -= 1

		lowerCAmelCase   =     remaining_time[short]
		if minm == 0:
			lowerCAmelCase   =     999_999_999

		if remaining_time[short] == 0:
			complete += 1
			lowerCAmelCase   =     False

			# Find finish time of current process
			lowerCAmelCase   =     increment_time + 1

			# Calculate waiting time
			lowerCAmelCase   =     finish_time - arrival_time[short]
			lowerCAmelCase   =     finar - burst_time[short]

			if waiting_time[short] < 0:
				lowerCAmelCase   =     0

        # Increment time
		increment_time += 1
	return waiting_time






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						list[int]							,		_SCREAMING_SNAKE_CASE					:						int							,		_SCREAMING_SNAKE_CASE					:						list[int]							)      ->						list[int]:







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






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						list[int]							,		_SCREAMING_SNAKE_CASE					:						list[int]							,		_SCREAMING_SNAKE_CASE					:						int							)      ->						None:







	"""simple docstring"""
	lowerCAmelCase   =     0
	lowerCAmelCase   =     0
	for i in range(_SCREAMING_SNAKE_CASE							):
		lowerCAmelCase   =     total_waiting_time + waiting_time[i]
		lowerCAmelCase   =     total_turn_around_time + turn_around_time[i]
	print(f'Average waiting time = {total_waiting_time / no_of_processes:.5f}'							)
	print("""Average turn around time ="""							,		total_turn_around_time / no_of_processes							)


if __name__ == "__main__":
				print('Enter how many process you want to analyze')
				UpperCAmelCase     		=   int(input())
				UpperCAmelCase     		=   [0] * no_of_processes
				UpperCAmelCase     		=   [0] * no_of_processes
				UpperCAmelCase     		=   list(range(1, no_of_processes + 1))

				for i in range(no_of_processes):
								print('Enter the arrival time and burst time for process:--' + str(i + 1))
								UpperCAmelCase		,       UpperCAmelCase     		=   map(int, input().split())

				UpperCAmelCase     		=   calculate_waitingtime(arrival_time, burst_time, no_of_processes)

				UpperCAmelCase     		=   burst_time
				UpperCAmelCase     		=   no_of_processes
				UpperCAmelCase     		=   waiting_time
				UpperCAmelCase     		=   calculate_turnaroundtime(bt, n, wt)

				calculate_average_times(waiting_time, turn_around_time, no_of_processes)

				UpperCAmelCase     		=   pd.DataFrame(
				    list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
				    columns=[
				        'Process',
				        'BurstTime',
				        'ArrivalTime',
				        'WaitingTime',
				        'TurnAroundTime',
				    ],
				)

				# Printing the dataFrame
				pd.set_option('display.max_rows', fcfs.shape[0] + 1)
				print(fcfs)