




import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin







class a (     __SCREAMING_SNAKE_CASE       ,						unittest.TestCase  ):
						"""simple docstring"""

						UpperCamelCase_	:       int       	=		CanineTokenizer
						UpperCamelCase_	:       Optional[int]       	=		False






						def     UpperCAmelCase_      ( self :     int				)    ->						Optional[Any]:
													"""simple docstring"""


													super().setUp()
													__lowercase      =    CanineTokenizer()
													tokenizer.save_pretrained(self.tmpdirname				)






						@cached_property
						def     UpperCAmelCase_      ( self :     str				)    ->						List[str]:
													"""simple docstring"""


													return CanineTokenizer.from_pretrained('''google/canine-s'''				)






						def     UpperCAmelCase_      ( self :     List[str]				,							**lowerCamelCase__ :     Tuple				)    ->						CanineTokenizer:
													"""simple docstring"""


													__lowercase      =    self.tokenizer_class.from_pretrained(self.tmpdirname				,							**lowerCamelCase__				)
													__lowercase      =    1_024
													return tokenizer






						@require_torch
						def     UpperCAmelCase_      ( self :     int				)    ->						List[str]:
													"""simple docstring"""


													__lowercase      =    self.canine_tokenizer
													__lowercase      =    ['''Life is like a box of chocolates.''', '''You never know what you\'re gonna get.''']
													# fmt: off
													__lowercase      =    [57_344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57_345, 0, 0, 0, 0]
													# fmt: on
													__lowercase      =    tokenizer(lowerCamelCase__				,							padding=lowerCamelCase__				,							return_tensors='''pt'''				)
													self.assertIsInstance(lowerCamelCase__				,							lowerCamelCase__				)

													__lowercase      =    list(batch.input_ids.numpy()[0]				)

													self.assertListEqual(lowerCamelCase__				,							lowerCamelCase__				)

													self.assertEqual((2, 39)				,							batch.input_ids.shape				)
													self.assertEqual((2, 39)				,							batch.attention_mask.shape				)






						@require_torch
						def     UpperCAmelCase_      ( self :     Union[str, Any]				)    ->						Dict:
													"""simple docstring"""


													__lowercase      =    self.canine_tokenizer
													__lowercase      =    ['''Once there was a man.''', '''He wrote a test in HuggingFace Tranformers.''']
													__lowercase      =    tokenizer(lowerCamelCase__				,							padding=lowerCamelCase__				,							return_tensors='''pt'''				)
													# check if input_ids, attention_mask and token_type_ids are returned
													self.assertIn('''input_ids'''				,							lowerCamelCase__				)
													self.assertIn('''attention_mask'''				,							lowerCamelCase__				)
													self.assertIn('''token_type_ids'''				,							lowerCamelCase__				)






						@require_torch
						def     UpperCAmelCase_      ( self :     int				)    ->						List[Any]:
													"""simple docstring"""


													__lowercase      =    self.canine_tokenizer
													__lowercase      =    [
													    '''What\'s the weater?''',
													    '''It\'s about 25 degrees.''',
													]
													__lowercase      =    tokenizer(
													    text_target=lowerCamelCase__				,							max_length=32				,							padding='''max_length'''				,							truncation=lowerCamelCase__				,							return_tensors='''pt'''				)
													self.assertEqual(32				,							targets['''input_ids'''].shape[1]				)






						def     UpperCAmelCase_      ( self :     str				)    ->						int:
													"""simple docstring"""


													__lowercase      =    self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											self.assertNotEqual(tokenizer.model_max_length				,							42				)

        # Now let's start the test
													__lowercase      =    self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											# Isolate this from the other tests because we save additional tokens/etc
																											__lowercase      =    tempfile.mkdtemp()

																											__lowercase      =    ''' He is very happy, UNwant\u00E9d,running'''
																											__lowercase      =    tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											tokenizer.save_pretrained(lowerCamelCase__				)

																											__lowercase      =    tokenizer.__class__.from_pretrained(lowerCamelCase__				)
																											__lowercase      =    after_tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											self.assertListEqual(lowerCamelCase__				,							lowerCamelCase__				)

																											shutil.rmtree(lowerCamelCase__				)

													__lowercase      =    self.get_tokenizers(model_max_length=42				)
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											# Isolate this from the other tests because we save additional tokens/etc
																											__lowercase      =    tempfile.mkdtemp()

																											__lowercase      =    ''' He is very happy, UNwant\u00E9d,running'''

																											__lowercase      =    tokenizer.additional_special_tokens

																											# We can add a new special token for Canine as follows:
																											__lowercase      =    chr(0xe_0_0_7				)
																											additional_special_tokens.append(lowerCamelCase__				)
																											tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}				)
																											__lowercase      =    tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											tokenizer.save_pretrained(lowerCamelCase__				)

																											__lowercase      =    tokenizer.__class__.from_pretrained(lowerCamelCase__				)
																											__lowercase      =    after_tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											self.assertListEqual(lowerCamelCase__				,							lowerCamelCase__				)
																											self.assertIn(lowerCamelCase__				,							after_tokenizer.additional_special_tokens				)
																											self.assertEqual(after_tokenizer.model_max_length				,							42				)

																											__lowercase      =    tokenizer.__class__.from_pretrained(lowerCamelCase__				,							model_max_length=43				)
																											self.assertEqual(tokenizer.model_max_length				,							43				)

																											shutil.rmtree(lowerCamelCase__				)






						def     UpperCAmelCase_      ( self :     Optional[Any]				)    ->						int:
													"""simple docstring"""


													__lowercase      =    self.get_tokenizers(do_lower_case=lowerCamelCase__				)
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											__lowercase     ,     __lowercase      =    self.get_clean_sequence(lowerCamelCase__				)

																											# a special token for Canine can be defined as follows:
																											__lowercase      =    0xe_0_0_5
																											__lowercase      =    chr(lowerCamelCase__				)

																											tokenizer.add_special_tokens({'''cls_token''': special_token}				)
																											__lowercase      =    tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											self.assertEqual(len(lowerCamelCase__				)				,							1				)

																											__lowercase      =    tokenizer.decode(ids + encoded_special_token				,							clean_up_tokenization_spaces=lowerCamelCase__				)
																											__lowercase      =    tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)

																											__lowercase      =    tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											__lowercase      =    tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											self.assertEqual(lowerCamelCase__				,							input_encoded + special_token_id				)

																											__lowercase      =    tokenizer.decode(lowerCamelCase__				,							skip_special_tokens=lowerCamelCase__				)
																											self.assertTrue(special_token not in decoded				)






						def     UpperCAmelCase_      ( self :     List[Any]				)    ->						List[Any]:
													"""simple docstring"""


													__lowercase      =    self.get_tokenizers(do_lower_case=lowerCamelCase__				)
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											__lowercase      =    chr(0xe_0_0_5				)
																											__lowercase      =    chr(0xe_0_0_6				)

																											# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
																											tokenizer.add_tokens([SPECIAL_TOKEN_1]				,							special_tokens=lowerCamelCase__				)
																											# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
																											# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
																											tokenizer.add_special_tokens({'''additional_special_tokens''': [SPECIAL_TOKEN_2]}				)

																											__lowercase      =    tokenizer.tokenize(lowerCamelCase__				)
																											__lowercase      =    tokenizer.tokenize(lowerCamelCase__				)

																											self.assertEqual(len(lowerCamelCase__				)				,							1				)
																											self.assertEqual(len(lowerCamelCase__				)				,							1				)
																											self.assertEqual(token_a[0]				,							lowerCamelCase__				)
																											self.assertEqual(token_a[0]				,							lowerCamelCase__				)






						@require_tokenizers
						def     UpperCAmelCase_      ( self :     List[str]				)    ->						Dict:
													"""simple docstring"""


													__lowercase      =    self.get_tokenizers(do_lower_case=lowerCamelCase__				)
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											# a special token for Canine can be defined as follows:
																											__lowercase      =    0xe_0_0_6
																											__lowercase      =    chr(lowerCamelCase__				)

																											__lowercase      =    AddedToken(lowerCamelCase__				,							lstrip=lowerCamelCase__				)
																											tokenizer.add_special_tokens({'''additional_special_tokens''': [new_token]}				)

																											with tempfile.TemporaryDirectory() as tmp_dir_name:
																																		tokenizer.save_pretrained(lowerCamelCase__				)
																																		tokenizer.from_pretrained(lowerCamelCase__				)






						def     UpperCAmelCase_      ( self :     int				)    ->						Dict:
													"""simple docstring"""


													__lowercase      =    []
													if self.test_slow_tokenizer:
																				tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())				)

													if self.test_rust_tokenizer:
																				tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())				)

													for tokenizer_class, tokenizer_utils in tokenizer_list:
																				with tempfile.TemporaryDirectory() as tmp_dir:
																											tokenizer_utils.save_pretrained(lowerCamelCase__				)

																											with open(os.path.join(lowerCamelCase__				,							'''special_tokens_map.json'''				)				,							encoding='''utf-8'''				) as json_file:
																																		__lowercase      =    json.load(lowerCamelCase__				)

																											with open(os.path.join(lowerCamelCase__				,							'''tokenizer_config.json'''				)				,							encoding='''utf-8'''				) as json_file:
																																		__lowercase      =    json.load(lowerCamelCase__				)

																											# a special token for Canine can be defined as follows:
																											__lowercase      =    0xe_0_0_6
																											__lowercase      =    chr(lowerCamelCase__				)

																											__lowercase      =    [new_token_a]
																											__lowercase      =    [new_token_a]

																											with open(os.path.join(lowerCamelCase__				,							'''special_tokens_map.json'''				)				,							'''w'''				,							encoding='''utf-8'''				) as outfile:
																																		json.dump(lowerCamelCase__				,							lowerCamelCase__				)
																											with open(os.path.join(lowerCamelCase__				,							'''tokenizer_config.json'''				)				,							'''w'''				,							encoding='''utf-8'''				) as outfile:
																																		json.dump(lowerCamelCase__				,							lowerCamelCase__				)

																											# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
																											# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
																											# "special_tokens_map.json" files
																											__lowercase      =    tokenizer_class.from_pretrained(lowerCamelCase__				,							extra_ids=0				)
																											self.assertIn(lowerCamelCase__				,							tokenizer_without_change_in_init.additional_special_tokens				)
																											# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
																											self.assertEqual(
																											    [new_token_a]				,							tokenizer_without_change_in_init.convert_ids_to_tokens(
																											        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]				)				)				,							)

																											__lowercase      =    0xe_0_0_7
																											__lowercase      =    chr(lowerCamelCase__				)
																											# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																											__lowercase      =    [AddedToken(lowerCamelCase__				,							lstrip=lowerCamelCase__				)]
																											__lowercase      =    tokenizer_class.from_pretrained(
																											    lowerCamelCase__				,							additional_special_tokens=lowerCamelCase__				,							extra_ids=0				)

																											self.assertIn(lowerCamelCase__				,							tokenizer.additional_special_tokens				)
																											# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
																											self.assertEqual(
																											    [new_token_a]				,							tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]				)				)				)






						@require_tokenizers
						def     UpperCAmelCase_      ( self :     int				)    ->						Dict:
													"""simple docstring"""


													__lowercase      =    self.get_tokenizers(do_lower_case=lowerCamelCase__				)
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											__lowercase      =    '''hello world'''
																											if self.space_between_special_tokens:
																																		__lowercase      =    '''[CLS] hello world [SEP]'''
																											else:
																																		__lowercase      =    input
																											__lowercase      =    tokenizer.encode(lowerCamelCase__				,							add_special_tokens=lowerCamelCase__				)
																											__lowercase      =    tokenizer.decode(lowerCamelCase__				,							spaces_between_special_tokens=self.space_between_special_tokens				)
																											self.assertIn(lowerCamelCase__				,							[output, output.lower()]				)






						def     UpperCAmelCase_      ( self :     List[Any]				)    ->						Optional[int]:
													"""simple docstring"""


													__lowercase      =    self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(f'{tokenizer.__class__.__name__}'				):
																											__lowercase      =    [
																											    '''bos_token''',
																											    '''eos_token''',
																											    '''unk_token''',
																											    '''sep_token''',
																											    '''pad_token''',
																											    '''cls_token''',
																											    '''mask_token''',
																											]

													__lowercase      =    '''a'''
													__lowercase      =    ord(lowerCamelCase__				)

													for attr in attributes_list:
																				setattr(lowerCamelCase__				,							attr + '''_id'''				,							lowerCamelCase__				)
																				self.assertEqual(getattr(lowerCamelCase__				,							lowerCamelCase__				)				,							lowerCamelCase__				)
																				self.assertEqual(getattr(lowerCamelCase__				,							attr + '''_id'''				)				,							lowerCamelCase__				)

																				setattr(lowerCamelCase__				,							attr + '''_id'''				,							lowerCamelCase__				)
																				self.assertEqual(getattr(lowerCamelCase__				,							lowerCamelCase__				)				,							lowerCamelCase__				)
																				self.assertEqual(getattr(lowerCamelCase__				,							attr + '''_id'''				)				,							lowerCamelCase__				)

													setattr(lowerCamelCase__				,							'''additional_special_tokens_ids'''				,							[]				)
													self.assertListEqual(getattr(lowerCamelCase__				,							'''additional_special_tokens'''				)				,							[]				)
													self.assertListEqual(getattr(lowerCamelCase__				,							'''additional_special_tokens_ids'''				)				,							[]				)

													__lowercase      =    0xe_0_0_6
													__lowercase      =    chr(lowerCamelCase__				)
													setattr(lowerCamelCase__				,							'''additional_special_tokens_ids'''				,							[additional_special_token_id]				)
													self.assertListEqual(getattr(lowerCamelCase__				,							'''additional_special_tokens'''				)				,							[additional_special_token]				)
													self.assertListEqual(getattr(lowerCamelCase__				,							'''additional_special_tokens_ids'''				)				,							[additional_special_token_id]				)






						def     UpperCAmelCase_      ( self :     List[Any]				)    ->						Optional[int]:
													"""simple docstring"""


													pass






						def     UpperCAmelCase_      ( self :     Dict				)    ->						Tuple:
													"""simple docstring"""


													pass






						def     UpperCAmelCase_      ( self :     List[Any]				)    ->						Any:
													"""simple docstring"""


													pass






						def     UpperCAmelCase_      ( self :     Tuple				)    ->						Dict:
													"""simple docstring"""


													pass






						def     UpperCAmelCase_      ( self :     List[Any]				)    ->						Tuple:
													"""simple docstring"""


													pass






						def     UpperCAmelCase_      ( self :     str				)    ->						Any:
													"""simple docstring"""


													pass






						def     UpperCAmelCase_      ( self :     str				)    ->						Dict:
													"""simple docstring"""


													pass






						def     UpperCAmelCase_      ( self :     List[Any]				)    ->						List[Any]:
													"""simple docstring"""


													pass












import argparse
import copy







def 		_A(       UpperCamelCase__							:			Union[str, Any]				)    -> Tuple:
							'''simple docstring'''


							__lowercase      =    {}

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

							return dict_of_neighbours







def 		_A(       UpperCamelCase__							:			Optional[int]				,       UpperCamelCase__							:			Optional[Any]				)    -> Dict:
							'''simple docstring'''


							with open(UpperCamelCase__				) as f:
														__lowercase      =    f.read(1				)
							__lowercase      =    start_node

							__lowercase      =    []

							__lowercase      =    start_node

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

														first_solution.append(UpperCamelCase__				)
														__lowercase      =    distance_of_first_solution + int(UpperCamelCase__				)
														__lowercase      =    best_node

							first_solution.append(UpperCamelCase__				)

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

							__lowercase      =    (
							    distance_of_first_solution
							    + int(dict_of_neighbours[first_solution[-2]][position][1]				)
							    - 1_0000
							)
							return first_solution, distance_of_first_solution







def 		_A(       UpperCamelCase__							:			int				,       UpperCamelCase__							:			Optional[Any]				)    -> Optional[int]:
							'''simple docstring'''


							__lowercase      =    []

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

																					__lowercase      =    copy.deepcopy(UpperCamelCase__				)
																					__lowercase      =    kn
																					__lowercase      =    n

																					__lowercase      =    0

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

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

							__lowercase      =    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 		_A(       UpperCamelCase__							:			List[Any]				,       UpperCamelCase__							:			List[str]				,       UpperCamelCase__							:			Optional[int]				,       UpperCamelCase__							:			Optional[int]				,       UpperCamelCase__							:			Optional[int]				)    -> List[str]:
							'''simple docstring'''


							__lowercase      =    1
							__lowercase      =    first_solution
							__lowercase      =    []
							__lowercase      =    distance_of_first_solution
							__lowercase      =    solution

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

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

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

														__lowercase      =    count + 1

							return best_solution_ever, best_cost







def 		_A(       UpperCamelCase__							:			List[Any]=None				)    -> int:
							'''simple docstring'''


							__lowercase      =    generate_neighbours(args.File				)

							__lowercase     ,     __lowercase      =    generate_first_solution(
							    args.File				,       UpperCamelCase__				)

							__lowercase     ,     __lowercase      =    tabu_search(
							    UpperCamelCase__				,       UpperCamelCase__				,       UpperCamelCase__				,       args.Iterations				,       args.Size				,       )

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


if __name__ == "__main__":
			UpperCAmelCase__				     = 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())






