



"""simple docstring"""






import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 			__snake_case			(      _lowercase    ,	unittest.TestCase):
  snake_case__							:  Optional[Any]         =		RobertaTokenizer
  snake_case__							:  int         =		RobertaTokenizerFast
  snake_case__							:  List[Any]         =		True
  snake_case__							:  Optional[Any]         =		{"cls_token": "<s>"}




  def 		SCREAMING_SNAKE_CASE							(					self	:		Dict						):






         """simple docstring"""






         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         _lowerCamelCase		:							Union[str, Any]            =					[
             '''l''',
             '''o''',
             '''w''',
             '''e''',
             '''r''',
             '''s''',
             '''t''',
             '''i''',
             '''d''',
             '''n''',
             '''\u0120''',
             '''\u0120l''',
             '''\u0120n''',
             '''\u0120lo''',
             '''\u0120low''',
             '''er''',
             '''\u0120lowest''',
             '''\u0120newer''',
             '''\u0120wider''',
             '''<unk>''',
         ]
         _lowerCamelCase		:							Dict            =					dict(zip(__lowerCAmelCase		,   range(len(__lowerCAmelCase						)						)						)						)
         _lowerCamelCase		:							Any            =					['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
         _lowerCamelCase		:							Tuple            =					{'''unk_token''': '''<unk>'''}

         _lowerCamelCase		:							List[str]            =					os.path.join(self.tmpdirname		,   VOCAB_FILES_NAMES['''vocab_file''']						)
         _lowerCamelCase		:							Dict            =					os.path.join(self.tmpdirname		,   VOCAB_FILES_NAMES['''merges_file''']						)
         with open(self.vocab_file		,   '''w'''		,   encoding='''utf-8'''						) as fp:
                fp.write(json.dumps(__lowerCAmelCase						) + '''\n'''						)
         with open(self.merges_file		,   '''w'''		,   encoding='''utf-8'''						) as fp:
                fp.write('''\n'''.join(__lowerCAmelCase						)						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple		,   **__lowerCAmelCase	:		Union[str, Any]						):






         """simple docstring"""






         kwargs.update(self.special_tokens_map						)
         return self.tokenizer_class.from_pretrained(self.tmpdirname		,   **__lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Optional[Any]		,   **__lowerCAmelCase	:		Optional[Any]						):






         """simple docstring"""






         kwargs.update(self.special_tokens_map						)
         return RobertaTokenizerFast.from_pretrained(self.tmpdirname		,   **__lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple		,   __lowerCAmelCase	:		Dict						):






         """simple docstring"""






         _lowerCamelCase		:							Optional[int]            =					'''lower newer'''
         _lowerCamelCase		:							List[Any]            =					'''lower newer'''
         return input_text, output_text




  def 		SCREAMING_SNAKE_CASE							(					self	:		List[Any]						):






         """simple docstring"""






         _lowerCamelCase		:							Union[str, Any]            =					self.tokenizer_class(self.vocab_file		,   self.merges_file		,   **self.special_tokens_map						)
         _lowerCamelCase		:							Optional[Any]            =					'''lower newer'''
         _lowerCamelCase		:							str            =					['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
         _lowerCamelCase		:							List[str]            =					tokenizer.tokenize(__lowerCAmelCase						)  # , add_prefix_space=True)
         self.assertListEqual(__lowerCAmelCase		,   __lowerCAmelCase						)

         _lowerCamelCase		:							Optional[Any]            =					tokens + [tokenizer.unk_token]
         _lowerCamelCase		:							Optional[Any]            =					[0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase						)		,   __lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		int						):






         """simple docstring"""






         _lowerCamelCase		:							List[str]            =					self.get_tokenizer()

         self.assertListEqual(tokenizer.encode('''Hello world!'''		,   add_special_tokens=__lowerCAmelCase						)		,   [0, 3_1_4_1_4, 2_3_2, 3_2_8, 2]						)
         self.assertListEqual(
             tokenizer.encode('''Hello world! cécé herlolip 418'''		,   add_special_tokens=__lowerCAmelCase						)		,   [0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]		,   )




  @slow
  def 		SCREAMING_SNAKE_CASE							(					self	:		Union[str, Any]						):






         """simple docstring"""






         _lowerCamelCase		:							int            =					self.tokenizer_class.from_pretrained('''roberta-base'''						)

         _lowerCamelCase		:							int            =					tokenizer.encode('''sequence builders'''		,   add_special_tokens=__lowerCAmelCase						)
         _lowerCamelCase		:							Dict            =					tokenizer.encode('''multi-sequence build'''		,   add_special_tokens=__lowerCAmelCase						)

         _lowerCamelCase		:							Dict            =					tokenizer.encode(
             '''sequence builders'''		,   add_special_tokens=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase						)
         _lowerCamelCase		:							List[str]            =					tokenizer.encode(
             '''sequence builders'''		,   '''multi-sequence build'''		,   add_special_tokens=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase						)

         _lowerCamelCase		:							Union[str, Any]            =					tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase						)
         _lowerCamelCase		:							Tuple            =					tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase		,   __lowerCAmelCase						)

         assert encoded_sentence == encoded_text_from_decode
         assert encoded_pair == encoded_pair_from_decode




  def 		SCREAMING_SNAKE_CASE							(					self	:		List[Any]						):






         """simple docstring"""






         _lowerCamelCase		:							Tuple            =					self.get_tokenizer()

         _lowerCamelCase		:							List[str]            =					'''Encode this sequence.'''
         _lowerCamelCase		:							str            =					tokenizer.byte_encoder[''' '''.encode('''utf-8'''						)[0]]

         # Testing encoder arguments
         _lowerCamelCase		:							Any            =					tokenizer.encode(__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase						)
         _lowerCamelCase		:							Dict            =					tokenizer.convert_ids_to_tokens(encoded[0]						)[0]
         self.assertNotEqual(__lowerCAmelCase		,   __lowerCAmelCase						)

         _lowerCamelCase		:							Tuple            =					tokenizer.encode(__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase						)
         _lowerCamelCase		:							Any            =					tokenizer.convert_ids_to_tokens(encoded[0]						)[0]
         self.assertEqual(__lowerCAmelCase		,   __lowerCAmelCase						)

         tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}						)
         _lowerCamelCase		:							Optional[Any]            =					tokenizer.encode(__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
         _lowerCamelCase		:							Any            =					tokenizer.convert_ids_to_tokens(encoded[1]						)[0]
         self.assertNotEqual(__lowerCAmelCase		,   __lowerCAmelCase						)

         # Testing spaces after special tokens
         _lowerCamelCase		:							Tuple            =					'''<mask>'''
         tokenizer.add_special_tokens(
             {'''mask_token''': AddedToken(__lowerCAmelCase		,   lstrip=__lowerCAmelCase		,   rstrip=__lowerCAmelCase						)}						)  # mask token has a left space
         _lowerCamelCase		:							Union[str, Any]            =					tokenizer.convert_tokens_to_ids(__lowerCAmelCase						)

         _lowerCamelCase		:							Union[str, Any]            =					'''Encode <mask> sequence'''
         _lowerCamelCase		:							List[str]            =					'''Encode <mask>sequence'''

         _lowerCamelCase		:							str            =					tokenizer.encode(__lowerCAmelCase						)
         _lowerCamelCase		:							Tuple            =					encoded.index(__lowerCAmelCase						)
         _lowerCamelCase		:							Tuple            =					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]						)[0]
         self.assertEqual(__lowerCAmelCase		,   __lowerCAmelCase						)

         _lowerCamelCase		:							List[Any]            =					tokenizer.encode(__lowerCAmelCase						)
         _lowerCamelCase		:							Optional[Any]            =					encoded.index(__lowerCAmelCase						)
         _lowerCamelCase		:							Dict            =					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]						)[0]
         self.assertNotEqual(__lowerCAmelCase		,   __lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Union[str, Any]						):






         """simple docstring"""






         pass




  def 		SCREAMING_SNAKE_CASE							(					self	:		List[Any]						):






         """simple docstring"""






         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
                       _lowerCamelCase		:							Tuple            =					self.rust_tokenizer_class.from_pretrained(__lowerCAmelCase		,   **__lowerCAmelCase						)
                       _lowerCamelCase		:							Optional[int]            =					self.tokenizer_class.from_pretrained(__lowerCAmelCase		,   **__lowerCAmelCase						)
                       _lowerCamelCase		:							Optional[Any]            =					'''A, <mask> AllenNLP sentence.'''
                       _lowerCamelCase		:							Optional[Any]            =					tokenizer_r.encode_plus(__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase		,   return_token_type_ids=__lowerCAmelCase						)
                       _lowerCamelCase		:							Optional[int]            =					tokenizer_p.encode_plus(__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase		,   return_token_type_ids=__lowerCAmelCase						)

                       # token_type_ids should put 0 everywhere
                       self.assertEqual(sum(tokens_r['''token_type_ids''']						)		,   sum(tokens_p['''token_type_ids''']						)						)

                       # attention_mask should put 1 everywhere, so sum over length should be 1
                       self.assertEqual(
                           sum(tokens_r['''attention_mask''']						) / len(tokens_r['''attention_mask''']						)		,   sum(tokens_p['''attention_mask''']						) / len(tokens_p['''attention_mask''']						)		,   )

                       _lowerCamelCase		:							Union[str, Any]            =					tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']						)
                       _lowerCamelCase		:							Union[str, Any]            =					tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']						)

                       # Rust correctly handles the space before the mask while python doesnt
                       self.assertSequenceEqual(tokens_p['''input_ids''']		,   [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]						)
                       self.assertSequenceEqual(tokens_r['''input_ids''']		,   [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]						)

                       self.assertSequenceEqual(
                           __lowerCAmelCase		,   ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']						)
                       self.assertSequenceEqual(
                           __lowerCAmelCase		,   ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Union[str, Any]						):






         """simple docstring"""






         for trim_offsets, add_prefix_space in itertools.product([True, False]		,   repeat=2						):
                _lowerCamelCase		:							Dict            =					self.rust_tokenizer_class.from_pretrained(
                    self.tmpdirname		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)

                _lowerCamelCase		:							Any            =					json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()						)
                _lowerCamelCase		:							Optional[int]            =					json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()						)

                self.assertEqual(pre_tokenizer_state['''add_prefix_space''']		,   __lowerCAmelCase						)

                self.assertEqual(post_processor_state['''add_prefix_space''']		,   __lowerCAmelCase						)
                self.assertEqual(post_processor_state['''trim_offsets''']		,   __lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Optional[Any]						):






         """simple docstring"""






         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
                       _lowerCamelCase		:							int            =					'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
                       _lowerCamelCase		:							Any            =					f'''{text_of_1_token} {text_of_1_token}'''

                       _lowerCamelCase		:							int            =					self.rust_tokenizer_class.from_pretrained(
                           __lowerCAmelCase		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)
                       _lowerCamelCase		:							Optional[Any]            =					tokenizer_r(__lowerCAmelCase		,   return_offsets_mapping=__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
                       self.assertEqual(encoding.offset_mapping[0]		,   (0, len(__lowerCAmelCase						))						)
                       self.assertEqual(
                           encoding.offset_mapping[1]		,   (len(__lowerCAmelCase						) + 1, len(__lowerCAmelCase						) + 1 + len(__lowerCAmelCase						))		,   )

                       _lowerCamelCase		:							Any            =					self.rust_tokenizer_class.from_pretrained(
                           __lowerCAmelCase		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)
                       _lowerCamelCase		:							Tuple            =					tokenizer_r(__lowerCAmelCase		,   return_offsets_mapping=__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
                       self.assertEqual(encoding.offset_mapping[0]		,   (0, len(__lowerCAmelCase						))						)
                       self.assertEqual(
                           encoding.offset_mapping[1]		,   (len(__lowerCAmelCase						) + 1, len(__lowerCAmelCase						) + 1 + len(__lowerCAmelCase						))		,   )

                       _lowerCamelCase		:							Dict            =					self.rust_tokenizer_class.from_pretrained(
                           __lowerCAmelCase		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)
                       _lowerCamelCase		:							int            =					tokenizer_r(__lowerCAmelCase		,   return_offsets_mapping=__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
                       self.assertEqual(encoding.offset_mapping[0]		,   (0, len(__lowerCAmelCase						))						)
                       self.assertEqual(
                           encoding.offset_mapping[1]		,   (len(__lowerCAmelCase						), len(__lowerCAmelCase						) + 1 + len(__lowerCAmelCase						))		,   )

                       _lowerCamelCase		:							List[Any]            =					self.rust_tokenizer_class.from_pretrained(
                           __lowerCAmelCase		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)
                       _lowerCamelCase		:							Dict            =					tokenizer_r(__lowerCAmelCase		,   return_offsets_mapping=__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
                       self.assertEqual(encoding.offset_mapping[0]		,   (0, len(__lowerCAmelCase						))						)
                       self.assertEqual(
                           encoding.offset_mapping[1]		,   (len(__lowerCAmelCase						), len(__lowerCAmelCase						) + 1 + len(__lowerCAmelCase						))		,   )

                       _lowerCamelCase		:							int            =					f''' {text}'''

                       # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                       #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
                       # )
                       # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
                       # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
                       # self.assertEqual(
                       #     encoding.offset_mapping[1],
                       #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
                       # )

                       _lowerCamelCase		:							Union[str, Any]            =					self.rust_tokenizer_class.from_pretrained(
                           __lowerCAmelCase		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)
                       _lowerCamelCase		:							Optional[int]            =					tokenizer_r(__lowerCAmelCase		,   return_offsets_mapping=__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
                       self.assertEqual(encoding.offset_mapping[0]		,   (1, 1 + len(__lowerCAmelCase						))						)
                       self.assertEqual(
                           encoding.offset_mapping[1]		,   (1 + len(__lowerCAmelCase						) + 1, 1 + len(__lowerCAmelCase						) + 1 + len(__lowerCAmelCase						))		,   )

                       _lowerCamelCase		:							Any            =					self.rust_tokenizer_class.from_pretrained(
                           __lowerCAmelCase		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)
                       _lowerCamelCase		:							str            =					tokenizer_r(__lowerCAmelCase		,   return_offsets_mapping=__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
                       self.assertEqual(encoding.offset_mapping[0]		,   (0, 1 + len(__lowerCAmelCase						))						)
                       self.assertEqual(
                           encoding.offset_mapping[1]		,   (1 + len(__lowerCAmelCase						), 1 + len(__lowerCAmelCase						) + 1 + len(__lowerCAmelCase						))		,   )

                       _lowerCamelCase		:							Dict            =					self.rust_tokenizer_class.from_pretrained(
                           __lowerCAmelCase		,   use_fast=__lowerCAmelCase		,   add_prefix_space=__lowerCAmelCase		,   trim_offsets=__lowerCAmelCase						)
                       _lowerCamelCase		:							Tuple            =					tokenizer_r(__lowerCAmelCase		,   return_offsets_mapping=__lowerCAmelCase		,   add_special_tokens=__lowerCAmelCase						)
                       self.assertEqual(encoding.offset_mapping[0]		,   (0, 1 + len(__lowerCAmelCase						))						)
                       self.assertEqual(
                           encoding.offset_mapping[1]		,   (1 + len(__lowerCAmelCase						), 1 + len(__lowerCAmelCase						) + 1 + len(__lowerCAmelCase						))		,   )





import argparse
import copy

def 		UpperCamelCase   (lowercase_:					Any   )	-> Union[str, Any]:
	A__				:       int	  =						{}

	with open(lowercase_   ) as f:
		for line in f:
			if line.split()[0] not in dict_of_neighbours:
				A__				:       int	  =						[]
				_list.append([line.split()[1], line.split()[2]]   )
				A__				:       Any	  =						_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__				:       Optional[int]	  =						[]
				_list.append([line.split()[0], line.split()[2]]   )
				A__				:       Any	  =						_list
			else:
				dict_of_neighbours[line.split()[1]].append(
				    [line.split()[0], line.split()[2]]   )

	return dict_of_neighbours

def 		UpperCamelCase   (lowercase_:					Tuple       , lowercase_:					List[str]   )	-> Tuple:

	with open(lowercase_   ) as f:
		A__				:       List[Any]	  =						f.read(1   )
	A__				:       Union[str, Any]	  =						start_node

	A__				:       List[Any]	  =						[]

	A__				:       str	  =						start_node

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

		first_solution.append(lowercase_   )
		A__				:       Optional[int]	  =						distance_of_first_solution + int(lowercase_   )
		A__				:       str	  =						best_node

	first_solution.append(lowercase_   )

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

	A__				:       int	  =						(
	    distance_of_first_solution
	    + int(dict_of_neighbours[first_solution[-2]][position][1]   )
	    - 10000
	)
	return first_solution, distance_of_first_solution

def 		UpperCamelCase   (lowercase_:					Any       , lowercase_:					str   )	-> Any:
	A__				:       int	  =						[]

	for n in solution[1:-1]:
		A__				:       Union[str, Any]	  =						solution.index(lowercase_   )
		for kn in solution[1:-1]:
			A__				:       List[Any]	  =						solution.index(lowercase_   )
			if n == kn:
				continue

			A__				:       Union[str, Any]	  =						copy.deepcopy(lowercase_   )
			A__				:       int	  =						kn
			A__				:       Optional[int]	  =						n

			A__				:       Dict	  =						0

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

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

	A__				:       Optional[Any]	  =						len(neighborhood_of_solution[0]   ) - 1

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

def 		UpperCamelCase   (lowercase_:					List[str]       , lowercase_:					Tuple       , lowercase_:					Dict       , lowercase_:					Dict       , lowercase_:					Tuple   )	-> Union[str, Any]:
	A__				:       Union[str, Any]	  =						1
	A__				:       List[str]	  =						first_solution
	A__				:       Dict	  =						[]
	A__				:       Union[str, Any]	  =						distance_of_first_solution
	A__				:       Any	  =						solution

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

		A__				:       List[str]	  =						False
		while not found:
			A__				:       Dict	  =						0
			while i < len(lowercase_   ):
				if best_solution[i] != solution[i]:
					A__				:       Any	  =						best_solution[i]
					A__				:       Optional[int]	  =						solution[i]
					break
				A__				:       Any	  =						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__				:       List[str]	  =						True
				A__				:       List[Any]	  =						best_solution[:-1]
				A__				:       Optional[Any]	  =						neighborhood[index_of_best_solution][best_cost_index]
				if cost < best_cost:
					A__				:       Tuple	  =						cost
					A__				:       int	  =						solution
			else:
				A__				:       List[Any]	  =						index_of_best_solution + 1
				A__				:       Tuple	  =						neighborhood[index_of_best_solution]

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

		A__				:       Any	  =						count + 1

	return best_solution_ever, best_cost

def 		UpperCamelCase   (lowercase_:					Union[str, Any]=None   )	-> List[str]:
	A__				:       Union[str, Any]	  =						generate_neighbours(args.File   )

	A__  ,  A__				:       int	  =						generate_first_solution(
	    args.File       , lowercase_   )

	A__  ,  A__				:       str	  =						tabu_search(
	    lowercase_       , lowercase_       , lowercase_       , args.Iterations       , args.Size       , )

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


if __name__ == "__main__":
	A_			:					str    			=     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())



