



import argparse
import copy






def      lowerCAmelCase__		(   lowerCamelCase_		:		Optional[Any]):





				'''simple docstring'''

				lowerCAmelCase__					:    Union[str, Any]												=					{}

				with open(lowerCamelCase_) as f:
								for line in f:
												if line.split()[0] not in dict_of_neighbours:
																lowerCAmelCase__					:    Dict												=					[]
																_list.append([line.split()[1], line.split()[2]])
																lowerCAmelCase__					:    List[str]												=					_list
												else:
																dict_of_neighbours[line.split()[0]].append(
																    [line.split()[1], line.split()[2]])
												if line.split()[1] not in dict_of_neighbours:
																lowerCAmelCase__					:    str												=					[]
																_list.append([line.split()[0], line.split()[2]])
																lowerCAmelCase__					:    Union[str, Any]												=					_list
												else:
																dict_of_neighbours[line.split()[1]].append(
																    [line.split()[0], line.split()[2]])

				return dict_of_neighbours






def      lowerCAmelCase__		(   lowerCamelCase_		:		Dict	,lowerCamelCase_		:		str):





				'''simple docstring'''

				with open(lowerCamelCase_) as f:
								lowerCAmelCase__					:    Any												=					f.read(1)
				lowerCAmelCase__					:    Dict												=					start_node

				lowerCAmelCase__					:    Dict												=					[]

				lowerCAmelCase__					:    List[Any]												=					start_node

				lowerCAmelCase__					:    List[str]												=					0
				while visiting not in first_solution:
								lowerCAmelCase__					:    Dict												=					10000
								for k in dict_of_neighbours[visiting]:
												if int(k[1]) < int(lowerCamelCase_) and k[0] not in first_solution:
																lowerCAmelCase__					:    int												=					k[1]
																lowerCAmelCase__					:    Optional[int]												=					k[0]

								first_solution.append(lowerCamelCase_)
								lowerCAmelCase__					:    Tuple												=					distance_of_first_solution + int(lowerCamelCase_)
								lowerCAmelCase__					:    str												=					best_node

				first_solution.append(lowerCamelCase_)

				lowerCAmelCase__					:    List[Any]												=					0
				for k in dict_of_neighbours[first_solution[-2]]:
								if k[0] == start_node:
												break
								position += 1

				lowerCAmelCase__					:    Union[str, Any]												=					(
				    distance_of_first_solution
				    + int(dict_of_neighbours[first_solution[-2]][position][1])
				    - 10000
				)
				return first_solution, distance_of_first_solution






def      lowerCAmelCase__		(   lowerCamelCase_		:		str	,lowerCamelCase_		:		Any):





				'''simple docstring'''

				lowerCAmelCase__					:    Union[str, Any]												=					[]

				for n in solution[1:-1]:
								lowerCAmelCase__					:    Optional[Any]												=					solution.index(lowerCamelCase_)
								for kn in solution[1:-1]:
												lowerCAmelCase__					:    Any												=					solution.index(lowerCamelCase_)
												if n == kn:
																continue

												lowerCAmelCase__					:    int												=					copy.deepcopy(lowerCamelCase_)
												lowerCAmelCase__					:    List[Any]												=					kn
												lowerCAmelCase__					:    Any												=					n

												lowerCAmelCase__					:    List[Any]												=					0

												for k in _tmp[:-1]:
																lowerCAmelCase__					:    str												=					_tmp[_tmp.index(lowerCamelCase_) + 1]
																for i in dict_of_neighbours[k]:
																				if i[0] == next_node:
																								lowerCAmelCase__					:    List[Any]												=					distance + int(i[1])
												_tmp.append(lowerCamelCase_)

												if _tmp not in neighborhood_of_solution:
																neighborhood_of_solution.append(_tmp)

				lowerCAmelCase__					:    List[Any]												=					len(neighborhood_of_solution[0]) - 1

				neighborhood_of_solution.sort(key=lambda lowerCamelCase_: x[index_of_last_item_in_the_list])
				return neighborhood_of_solution






def      lowerCAmelCase__		(   lowerCamelCase_		:		List[Any]	,lowerCamelCase_		:		List[str]	,lowerCamelCase_		:		Tuple	,lowerCamelCase_		:		Optional[int]	,lowerCamelCase_		:		Tuple):





				'''simple docstring'''

				lowerCAmelCase__					:    str												=					1
				lowerCAmelCase__					:    Tuple												=					first_solution
				lowerCAmelCase__					:    Union[str, Any]												=					[]
				lowerCAmelCase__					:    Optional[Any]												=					distance_of_first_solution
				lowerCAmelCase__					:    Optional[Any]												=					solution

				while count <= iters:
								lowerCAmelCase__					:    Union[str, Any]												=					find_neighborhood(lowerCamelCase_	,lowerCamelCase_)
								lowerCAmelCase__					:    int												=					0
								lowerCAmelCase__					:    Optional[Any]												=					neighborhood[index_of_best_solution]
								lowerCAmelCase__					:    int												=					len(lowerCamelCase_) - 1

								lowerCAmelCase__					:    int												=					False
								while not found:
												lowerCAmelCase__					:    Any												=					0
												while i < len(lowerCamelCase_):
																if best_solution[i] != solution[i]:
																				lowerCAmelCase__					:    List[str]												=					best_solution[i]
																				lowerCAmelCase__					:    List[Any]												=					solution[i]
																				break
																lowerCAmelCase__					:    int												=					i + 1

												if [first_exchange_node, second_exchange_node] not in tabu_list and [
												    second_exchange_node,
												    first_exchange_node,
												] not in tabu_list:
																tabu_list.append([first_exchange_node, second_exchange_node])
																lowerCAmelCase__					:    Optional[int]												=					True
																lowerCAmelCase__					:    Dict												=					best_solution[:-1]
																lowerCAmelCase__					:    Optional[int]												=					neighborhood[index_of_best_solution][best_cost_index]
																if cost < best_cost:
																				lowerCAmelCase__					:    List[str]												=					cost
																				lowerCAmelCase__					:    Union[str, Any]												=					solution
												else:
																lowerCAmelCase__					:    Optional[Any]												=					index_of_best_solution + 1
																lowerCAmelCase__					:    Union[str, Any]												=					neighborhood[index_of_best_solution]

								if len(lowerCamelCase_) >= size:
												tabu_list.pop(0)

								lowerCAmelCase__					:    Optional[int]												=					count + 1

				return best_solution_ever, best_cost






def      lowerCAmelCase__		(   lowerCamelCase_		:		int=None):





				'''simple docstring'''

				lowerCAmelCase__					:    Union[str, Any]												=					generate_neighbours(args.File)

				lowerCAmelCase__						,		lowerCAmelCase__					:    List[str]												=					generate_first_solution(
				    args.File	,lowerCamelCase_)

				lowerCAmelCase__						,		lowerCAmelCase__					:    List[Any]												=					tabu_search(
				    lowerCamelCase_	,lowerCamelCase_	,lowerCamelCase_	,args.Iterations	,args.Size	,)

				print(f"""Best solution: {best_sol}, with total distance: {best_cost}.""")


if __name__ == "__main__":
							__snake_case    :		List[Any]  =argparse.ArgumentParser(description='Tabu Search')
							parser.add_argument(
							    '-f',
							    '--File',
							    type=str,
							    help='Path to the file containing the data',
							    required=True,
							)
							parser.add_argument(
							    '-i',
							    '--Iterations',
							    type=int,
							    help='How many iterations the algorithm should perform',
							    required=True,
							)
							parser.add_argument(
							    '-s', '--Size', type=int, help='Size of the tabu list', required=True
							)

							# Pass the arguments to main method
							main(parser.parse_args())






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


__snake_case    :		Any  =logging.get_logger(__name__)

__snake_case    :		Tuple  ={
    'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}



class 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_     ="""vit_msn"""



		def __init__(self		,__lowerCamelCase=7_68		,__lowerCamelCase=12		,__lowerCamelCase=12		,__lowerCamelCase=30_72		,__lowerCamelCase="gelu"		,__lowerCamelCase=0.0		,__lowerCamelCase=0.0		,__lowerCamelCase=0.02		,__lowerCamelCase=1e-06		,__lowerCamelCase=2_24		,__lowerCamelCase=16		,__lowerCamelCase=3		,__lowerCamelCase=True		,**__lowerCamelCase		,)					->      Any:

						"""simple docstring"""






						super().__init__(**__lowerCamelCase			)

						lowerCAmelCase__					:    List[Any]												=					hidden_size
						lowerCAmelCase__					:    str												=					num_hidden_layers
						lowerCAmelCase__					:    List[str]												=					num_attention_heads
						lowerCAmelCase__					:    Optional[int]												=					intermediate_size
						lowerCAmelCase__					:    List[Any]												=					hidden_act
						lowerCAmelCase__					:    Tuple												=					hidden_dropout_prob
						lowerCAmelCase__					:    List[Any]												=					attention_probs_dropout_prob
						lowerCAmelCase__					:    int												=					initializer_range
						lowerCAmelCase__					:    Union[str, Any]												=					layer_norm_eps
						lowerCAmelCase__					:    List[str]												=					image_size
						lowerCAmelCase__					:    str												=					patch_size
						lowerCAmelCase__					:    Optional[int]												=					num_channels
						lowerCAmelCase__					:    int												=					qkv_bias

