





"""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 				__lowercase			(			_UpperCamelCase   ,      unittest.TestCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  RobertaTokenizer
					__lowerCAmelCase  =  RobertaTokenizerFast
					__lowerCAmelCase  =  True
					__lowerCAmelCase  =  {'''cls_token''': '''<s>'''}







					def  _lowerCamelCase		(						self     ):
									super().setUp()

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

									__a :						List[Any]			       =  os.path.join(self.tmpdirname	,			VOCAB_FILES_NAMES['''vocab_file''']     )
									__a :						Tuple			       =  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(_UpperCAmelCase     ) + '''\n'''     )
									with open(self.merges_file	,			'''w'''	,			encoding='''utf-8'''     ) as fp:
													fp.write('''\n'''.join(_UpperCAmelCase     )     )







					def  _lowerCamelCase		(						self	,			**_UpperCAmelCase     ):
									kwargs.update(self.special_tokens_map     )
									return self.tokenizer_class.from_pretrained(self.tmpdirname	,			**_UpperCAmelCase     )







					def  _lowerCamelCase		(						self	,			**_UpperCAmelCase     ):
									kwargs.update(self.special_tokens_map     )
									return RobertaTokenizerFast.from_pretrained(self.tmpdirname	,			**_UpperCAmelCase     )







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						Dict			       =  '''lower newer'''
									__a :						List[str]			       =  '''lower newer'''
									return input_text, output_text







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

									__a :						Optional[Any]			       =  tokens + [tokenizer.unk_token]
									__a :						Optional[Any]			       =  [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase     )	,			_UpperCAmelCase     )







					def  _lowerCamelCase		(						self     ):
									__a :						List[Any]			       =  self.get_tokenizer()

									self.assertListEqual(tokenizer.encode('''Hello world!'''	,			add_special_tokens=_UpperCAmelCase     )	,			[0, 31414, 232, 328, 2]     )
									self.assertListEqual(
									    tokenizer.encode('''Hello world! cécé herlolip 418'''	,			add_special_tokens=_UpperCAmelCase     )	,			[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]	,			)







					@slow
					def  _lowerCamelCase		(						self     ):
									__a :						Tuple			       =  self.tokenizer_class.from_pretrained('''roberta-base'''     )

									__a :						List[str]			       =  tokenizer.encode('''sequence builders'''	,			add_special_tokens=_UpperCAmelCase     )
									__a :						Tuple			       =  tokenizer.encode('''multi-sequence build'''	,			add_special_tokens=_UpperCAmelCase     )

									__a :						Optional[int]			       =  tokenizer.encode(
									    '''sequence builders'''	,			add_special_tokens=_UpperCAmelCase	,			add_prefix_space=_UpperCAmelCase     )
									__a :						List[str]			       =  tokenizer.encode(
									    '''sequence builders'''	,			'''multi-sequence build'''	,			add_special_tokens=_UpperCAmelCase	,			add_prefix_space=_UpperCAmelCase     )

									__a :						Optional[int]			       =  tokenizer.build_inputs_with_special_tokens(_UpperCAmelCase     )
									__a :						List[str]			       =  tokenizer.build_inputs_with_special_tokens(_UpperCAmelCase	,			_UpperCAmelCase     )

									assert encoded_sentence == encoded_text_from_decode
									assert encoded_pair == encoded_pair_from_decode







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

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

									# Testing encoder arguments
									__a :						str			       =  tokenizer.encode(_UpperCAmelCase	,			add_special_tokens=_UpperCAmelCase	,			add_prefix_space=_UpperCAmelCase     )
									__a :						Union[str, Any]			       =  tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
									self.assertNotEqual(_UpperCAmelCase	,			_UpperCAmelCase     )

									__a :						Tuple			       =  tokenizer.encode(_UpperCAmelCase	,			add_special_tokens=_UpperCAmelCase	,			add_prefix_space=_UpperCAmelCase     )
									__a :						Optional[Any]			       =  tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
									self.assertEqual(_UpperCAmelCase	,			_UpperCAmelCase     )

									tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}     )
									__a :						str			       =  tokenizer.encode(_UpperCAmelCase	,			add_special_tokens=_UpperCAmelCase     )
									__a :						Tuple			       =  tokenizer.convert_ids_to_tokens(encoded[1]     )[0]
									self.assertNotEqual(_UpperCAmelCase	,			_UpperCAmelCase     )

									# Testing spaces after special tokens
									__a :						int			       =  '''<mask>'''
									tokenizer.add_special_tokens(
									    {'''mask_token''': AddedToken(_UpperCAmelCase	,			lstrip=_UpperCAmelCase	,			rstrip=_UpperCAmelCase     )}     )  # mask token has a left space
									__a :						List[Any]			       =  tokenizer.convert_tokens_to_ids(_UpperCAmelCase     )

									__a :						List[str]			       =  '''Encode <mask> sequence'''
									__a :						Tuple			       =  '''Encode <mask>sequence'''

									__a :						Dict			       =  tokenizer.encode(_UpperCAmelCase     )
									__a :						Optional[Any]			       =  encoded.index(_UpperCAmelCase     )
									__a :						List[str]			       =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
									self.assertEqual(_UpperCAmelCase	,			_UpperCAmelCase     )

									__a :						str			       =  tokenizer.encode(_UpperCAmelCase     )
									__a :						Optional[Any]			       =  encoded.index(_UpperCAmelCase     )
									__a :						int			       =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
									self.assertNotEqual(_UpperCAmelCase	,			_UpperCAmelCase     )







					def  _lowerCamelCase		(						self     ):
									pass







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

																	# 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''']     )	,			)

																	__a :						List[Any]			       =  tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']     )
																	__a :						int			       =  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, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]     )
																	self.assertSequenceEqual(tokens_r['''input_ids''']	,			[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]     )

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







					def  _lowerCamelCase		(						self     ):
									for trim_offsets, add_prefix_space in itertools.product([True, False]	,			repeat=2     ):
													__a :						Optional[int]			       =  self.rust_tokenizer_class.from_pretrained(
													    self.tmpdirname	,			use_fast=_UpperCAmelCase	,			add_prefix_space=_UpperCAmelCase	,			trim_offsets=_UpperCAmelCase     )

													__a :						List[Any]			       =  json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()     )
													__a :						str			       =  json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()     )

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

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







					def  _lowerCamelCase		(						self     ):
									# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
									# `trim_offsets`
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
																	__a :						str			       =  '''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
																	__a :						Union[str, Any]			       =  f"""{text_of_1_token} {text_of_1_token}"""

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

																	__a :						List[str]			       =  self.rust_tokenizer_class.from_pretrained(
																	    _UpperCAmelCase	,			use_fast=_UpperCAmelCase	,			add_prefix_space=_UpperCAmelCase	,			trim_offsets=_UpperCAmelCase     )
																	__a :						Tuple			       =  tokenizer_r(_UpperCAmelCase	,			return_offsets_mapping=_UpperCAmelCase	,			add_special_tokens=_UpperCAmelCase     )
																	self.assertEqual(encoding.offset_mapping[0]	,			(0, len(_UpperCAmelCase     ))     )
																	self.assertEqual(
																	    encoding.offset_mapping[1]	,			(len(_UpperCAmelCase     ) + 1, len(_UpperCAmelCase     ) + 1 + len(_UpperCAmelCase     ))	,			)

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

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

																	__a :						Optional[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)),
																	# )

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

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

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






"""simple docstring"""






from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass




@dataclass
class 				__lowercase			:







					'''simple docstring'''




					__lowerCAmelCase  =  42
					__lowerCAmelCase  =  42






class 				__lowercase			:







					'''simple docstring'''




					def __init__(						self	,			_UpperCAmelCase     ):
									__a :						list[list[Edge]]			       =  [[] for _ in range(_UpperCAmelCase     )]
									__a :						Dict			       =  size







					def __getitem__(						self	,			_UpperCAmelCase     ):
									return iter(self._graph[vertex]     )







					@property
					def  _lowerCamelCase		(						self     ):
									return self._size







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									if weight not in (0, 1):
													raise ValueError('''Edge weight must be either 0 or 1.'''     )

									if to_vertex < 0 or to_vertex >= self.size:
													raise ValueError('''Vertex indexes must be in [0; size).'''     )

									self._graph[from_vertex].append(Edge(_UpperCAmelCase	,			_UpperCAmelCase     )     )







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									__a :						List[str]			       =  deque([start_vertex]     )
									__a :						list[int | None]			       =  [None] * self.size
									__a :						int			       =  0

									while queue:
													__a :						Any			       =  queue.popleft()
													__a :						Tuple			       =  distances[current_vertex]
													if current_distance is None:
																	continue

													for edge in self[current_vertex]:
																	__a :						List[str]			       =  current_distance + edge.weight
																	__a :						str			       =  distances[edge.destination_vertex]
																	if (
																	    isinstance(_UpperCAmelCase	,			_UpperCAmelCase     )
																	    and new_distance >= dest_vertex_distance
																	):
																					continue
																	__a :						str			       =  new_distance
																	if edge.weight == 0:
																					queue.appendleft(edge.destination_vertex     )
																	else:
																					queue.append(edge.destination_vertex     )

									if distances[finish_vertex] is None:
													raise ValueError('''No path from start_vertex to finish_vertex.'''     )

									return distances[finish_vertex]


if __name__ == "__main__":
		import doctest

		doctest.testmod()