




'''simple docstring'''


import argparse
import copy
def 						snake_case_       (UpperCamelCase			:    Tuple ):





							'''simple docstring'''


							_a      	=							{}

							with open(UpperCamelCase ) as f:
														for line in f:
																					if line.split()[0] not in dict_of_neighbours:
																												_a      	=							[]
																												_list.append([line.split()[1], line.split()[2]] )
																												_a      	=							_list
																					else:
																												dict_of_neighbours[line.split()[0]].append(
																												    [line.split()[1], line.split()[2]] )
																					if line.split()[1] not in dict_of_neighbours:
																												_a      	=							[]
																												_list.append([line.split()[0], line.split()[2]] )
																												_a      	=							_list
																					else:
																												dict_of_neighbours[line.split()[1]].append(
																												    [line.split()[0], line.split()[2]] )

							return dict_of_neighbours
def 						snake_case_       (UpperCamelCase			:    List[Any]					,		UpperCamelCase			:    List[str] ):





							'''simple docstring'''


							with open(UpperCamelCase ) as f:
														_a      	=							f.read(1 )
							_a      	=							start_node

							_a      	=							[]

							_a      	=							start_node

							_a      	=							0
							while visiting not in first_solution:
														_a      	=							1_0000
														for k in dict_of_neighbours[visiting]:
																					if int(k[1] ) < int(UpperCamelCase ) and k[0] not in first_solution:
																												_a      	=							k[1]
																												_a      	=							k[0]

														first_solution.append(UpperCamelCase )
														_a      	=							distance_of_first_solution + int(UpperCamelCase )
														_a      	=							best_node

							first_solution.append(UpperCamelCase )

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

							_a      	=							(
							    distance_of_first_solution
							    + int(dict_of_neighbours[first_solution[-2]][position][1] )
							    - 1_0000
							)
							return first_solution, distance_of_first_solution
def 						snake_case_       (UpperCamelCase			:    Tuple					,		UpperCamelCase			:    List[str] ):





							'''simple docstring'''


							_a      	=							[]

							for n in solution[1:-1]:
														_a      	=							solution.index(UpperCamelCase )
														for kn in solution[1:-1]:
																					_a      	=							solution.index(UpperCamelCase )
																					if n == kn:
																												continue

																					_a      	=							copy.deepcopy(UpperCamelCase )
																					_a      	=							kn
																					_a      	=							n

																					_a      	=							0

																					for k in _tmp[:-1]:
																												_a      	=							_tmp[_tmp.index(UpperCamelCase ) + 1]
																												for i in dict_of_neighbours[k]:
																																			if i[0] == next_node:
																																										_a      	=							distance + int(i[1] )
																					_tmp.append(UpperCamelCase )

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

							_a      	=							len(neighborhood_of_solution[0] ) - 1

							neighborhood_of_solution.sort(key=lambda UpperCamelCase : x[index_of_last_item_in_the_list] )
							return neighborhood_of_solution
def 						snake_case_       (UpperCamelCase			:    List[Any]					,		UpperCamelCase			:    List[Any]					,		UpperCamelCase			:    Union[str, Any]					,		UpperCamelCase			:    Union[str, Any]					,		UpperCamelCase			:    Dict ):





							'''simple docstring'''


							_a      	=							1
							_a      	=							first_solution
							_a      	=							[]
							_a      	=							distance_of_first_solution
							_a      	=							solution

							while count <= iters:
														_a      	=							find_neighborhood(UpperCamelCase					,		UpperCamelCase )
														_a      	=							0
														_a      	=							neighborhood[index_of_best_solution]
														_a      	=							len(UpperCamelCase ) - 1

														_a      	=							False
														while not found:
																					_a      	=							0
																					while i < len(UpperCamelCase ):
																												if best_solution[i] != solution[i]:
																																			_a      	=							best_solution[i]
																																			_a      	=							solution[i]
																																			break
																												_a      	=							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] )
																												_a      	=							True
																												_a      	=							best_solution[:-1]
																												_a      	=							neighborhood[index_of_best_solution][best_cost_index]
																												if cost < best_cost:
																																			_a      	=							cost
																																			_a      	=							solution
																					else:
																												_a      	=							index_of_best_solution + 1
																												_a      	=							neighborhood[index_of_best_solution]

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

														_a      	=							count + 1

							return best_solution_ever, best_cost
def 						snake_case_       (UpperCamelCase			:    str=None ):





							'''simple docstring'''


							_a      	=							generate_neighbours(args.File )

							_a	,				_a      	=							generate_first_solution(
							    args.File					,		UpperCamelCase )

							_a	,				_a      	=							tabu_search(
							    UpperCamelCase					,		UpperCamelCase					,		UpperCamelCase					,		args.Iterations					,		args.Size					,		)

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


if __name__ == "__main__":
				_snake_case : Dict  				=						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())







'''simple docstring'''


import os
import re
import shutil
import sys
import tempfile
import unittest

import black


_snake_case : str  				=						os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
_snake_case : List[str]  				=						'    \"""\n    Output class for the scheduler\'s step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"""\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n'

class      A       (						unittest.TestCase       ):







							def   __lowerCAmelCase     (    self			:    int   )     ->				List[Any]:


														"""simple docstring"""


														_a      	=							tempfile.mkdtemp()
														os.makedirs(os.path.join(self.diffusers_dir				,     '''schedulers/'''   )   )
														_a      	=							self.diffusers_dir
														shutil.copy(
														    os.path.join(lowerCAmelCase_				,     '''src/diffusers/schedulers/scheduling_ddpm.py'''   )				,     os.path.join(self.diffusers_dir				,     '''schedulers/scheduling_ddpm.py'''   )				,     )







							def   __lowerCAmelCase     (    self			:    Dict   )     ->				int:


														"""simple docstring"""


														_a      	=							'''src/diffusers'''
														shutil.rmtree(self.diffusers_dir   )







							def   __lowerCAmelCase     (    self			:    int				,     lowerCAmelCase_			:    str				,     lowerCAmelCase_			:    List[Any]				,     lowerCAmelCase_			:    Union[str, Any]				,     lowerCAmelCase_			:    str=None   )     ->				Union[str, Any]:


														"""simple docstring"""


														_a      	=							comment + F'\nclass {class_name}(nn.Module):\n' + class_code
														if overwrite_result is not None:
																					_a      	=							comment + F'\nclass {class_name}(nn.Module):\n' + overwrite_result
														_a      	=							black.Mode(target_versions={black.TargetVersion.PYaa}				,     line_length=1_19   )
														_a      	=							black.format_str(lowerCAmelCase_				,     mode=lowerCAmelCase_   )
														_a      	=							os.path.join(self.diffusers_dir				,     '''new_code.py'''   )
														with open(lowerCAmelCase_				,     '''w'''				,     newline='''\n'''   ) as f:
																					f.write(lowerCAmelCase_   )
														if overwrite_result is None:
																					self.assertTrue(len(check_copies.is_copy_consistent(lowerCAmelCase_   )   ) == 0   )
														else:
																					check_copies.is_copy_consistent(f.name				,     overwrite=lowerCAmelCase_   )
																					with open(lowerCAmelCase_				,     '''r'''   ) as f:
																												self.assertTrue(f.read()				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Optional[Any]   )     ->				Union[str, Any]:


														"""simple docstring"""


														_a      	=							check_copies.find_code_in_diffusers('''schedulers.scheduling_ddpm.DDPMSchedulerOutput'''   )
														self.assertEqual(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Dict   )     ->				Union[str, Any]:


														"""simple docstring"""


														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''				,     '''DDPMSchedulerOutput'''				,     REFERENCE_CODE + '''\n'''				,     )

														# With no empty line at the end
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''				,     '''DDPMSchedulerOutput'''				,     lowerCAmelCase_				,     )

														# Copy consistency with rename
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''				,     '''TestSchedulerOutput'''				,     re.sub('''DDPM'''				,     '''Test'''				,     lowerCAmelCase_   )				,     )

														# Copy consistency with a really long name
														_a      	=							'''TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason'''
														self.check_copy_consistency(
														    F'# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}'				,     F'{long_class_name}SchedulerOutput'				,     re.sub('''Bert'''				,     lowerCAmelCase_				,     lowerCAmelCase_   )				,     )

														# Copy consistency with overwrite
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''				,     '''TestSchedulerOutput'''				,     lowerCAmelCase_				,     overwrite_result=re.sub('''DDPM'''				,     '''Test'''				,     lowerCAmelCase_   )				,     )

