

import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
    '''kwargs, expected'''				,		[
        ({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
        ({'''num_shards''': 10, '''max_num_jobs''': 1}, [range(10    )]),
        ({'''num_shards''': 10, '''max_num_jobs''': 10}, [range(__snake_case				,		i + 1    ) for i in range(10    )]),
        ({'''num_shards''': 1, '''max_num_jobs''': 10}, [range(1    )]),
        ({'''num_shards''': 10, '''max_num_jobs''': 3}, [range(0				,		4    ), range(4				,		7    ), range(7				,		10    )]),
        ({'''num_shards''': 3, '''max_num_jobs''': 10}, [range(0				,		1    ), range(1				,		2    ), range(2				,		3    )]),
    ]				,		)
def     UpperCAmelCase_       (						_A				,		_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   _distribute_shards(**__snake_case    )
     assert out == expected
@pytest.mark.parametrize(
    '''gen_kwargs, max_num_jobs, expected'''				,		[
        ({'''foo''': 0}, 10, [{'''foo''': 0}]),
        ({'''shards''': [0, 1, 2, 3]}, 1, [{'''shards''': [0, 1, 2, 3]}]),
        ({'''shards''': [0, 1, 2, 3]}, 4, [{'''shards''': [0]}, {'''shards''': [1]}, {'''shards''': [2]}, {'''shards''': [3]}]),
        ({'''shards''': [0, 1]}, 4, [{'''shards''': [0]}, {'''shards''': [1]}]),
        ({'''shards''': [0, 1, 2, 3]}, 2, [{'''shards''': [0, 1]}, {'''shards''': [2, 3]}]),
    ]				,		)
def     UpperCAmelCase_       (						_A				,		_A				,		_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   _split_gen_kwargs(__snake_case				,		__snake_case    )
     assert out == expected







@pytest.mark.parametrize(
    '''gen_kwargs, expected'''				,		[
        ({'''foo''': 0}, 1),
        ({'''shards''': [0]}, 1),
        ({'''shards''': [0, 1, 2, 3]}, 4),
        ({'''shards''': [0, 1, 2, 3], '''foo''': 0}, 4),
        ({'''shards''': [0, 1, 2, 3], '''other''': (0, 1)}, 4),
        ({'''shards''': [0, 1, 2, 3], '''shards2''': [0, 1]}, RuntimeError),
    ]				,		)
def     UpperCAmelCase_       (						_A				,		_A    ):





     '''simple docstring'''




     if expected is RuntimeError:
          with pytest.raises(__snake_case    ):
               _number_of_shards_in_gen_kwargs(__snake_case    )
     else:
          SCREAMING_SNAKE_CASE__   =   _number_of_shards_in_gen_kwargs(__snake_case    )
          assert out == expected





import argparse
import copy
def     UpperCAmelCase_       (						_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   {}

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

     return dict_of_neighbours
def     UpperCAmelCase_       (						_A				,		_A    ):





     '''simple docstring'''




     with open(_A    ) as f:
          SCREAMING_SNAKE_CASE__   =   f.read(1    )
     SCREAMING_SNAKE_CASE__   =   start_node

     SCREAMING_SNAKE_CASE__   =   []

     SCREAMING_SNAKE_CASE__   =   start_node

     SCREAMING_SNAKE_CASE__   =   0
     while visiting not in first_solution:
          SCREAMING_SNAKE_CASE__   =   1_00_00
          for k in dict_of_neighbours[visiting]:
               if int(k[1]    ) < int(_A    ) and k[0] not in first_solution:
                    SCREAMING_SNAKE_CASE__   =   k[1]
                    SCREAMING_SNAKE_CASE__   =   k[0]

          first_solution.append(_A    )
          SCREAMING_SNAKE_CASE__   =   distance_of_first_solution + int(_A    )
          SCREAMING_SNAKE_CASE__   =   best_node

     first_solution.append(_A    )

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

     SCREAMING_SNAKE_CASE__   =   (
         distance_of_first_solution
         + int(dict_of_neighbours[first_solution[-2]][position][1]    )
         - 1_00_00
     )
     return first_solution, distance_of_first_solution
def     UpperCAmelCase_       (						_A				,		_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   []

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

               SCREAMING_SNAKE_CASE__   =   copy.deepcopy(_A    )
               SCREAMING_SNAKE_CASE__   =   kn
               SCREAMING_SNAKE_CASE__   =   n

               SCREAMING_SNAKE_CASE__   =   0

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

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

     SCREAMING_SNAKE_CASE__   =   len(neighborhood_of_solution[0]    ) - 1

     neighborhood_of_solution.sort(key=lambda _A    : x[index_of_last_item_in_the_list]    )
     return neighborhood_of_solution
def     UpperCAmelCase_       (						_A				,		_A				,		_A				,		_A				,		_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   1
     SCREAMING_SNAKE_CASE__   =   first_solution
     SCREAMING_SNAKE_CASE__   =   []
     SCREAMING_SNAKE_CASE__   =   distance_of_first_solution
     SCREAMING_SNAKE_CASE__   =   solution

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

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

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

          SCREAMING_SNAKE_CASE__   =   count + 1

     return best_solution_ever, best_cost
def     UpperCAmelCase_       (						_A=None    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   generate_neighbours(args.File    )

     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__   =   generate_first_solution(
         args.File				,		_A    )

     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__   =   tabu_search(
         _A				,		_A				,		_A				,		args.Iterations				,		args.Size				,		)

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


if __name__ == "__main__":
       _SCREAMING_SNAKE_CASE					:  Tuple             =      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())


