






"""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       __A		(   SCREAMING_SNAKE_CASE_     ,unittest.TestCase			):
					UpperCAmelCase__								=				RobertaTokenizer
					UpperCAmelCase__								=				RobertaTokenizerFast
					UpperCAmelCase__								=				True
					UpperCAmelCase__								=				{"cls_token": "<s>"}

					def   lowerCamelCase__   (			self  :      List[str]					)			->							Dict:
											super().setUp()

											# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
											__magic_name__:	List[Any]							=       [
											    """l""",
											    """o""",
											    """w""",
											    """e""",
											    """r""",
											    """s""",
											    """t""",
											    """i""",
											    """d""",
											    """n""",
											    """\u0120""",
											    """\u0120l""",
											    """\u0120n""",
											    """\u0120lo""",
											    """\u0120low""",
											    """er""",
											    """\u0120lowest""",
											    """\u0120newer""",
											    """\u0120wider""",
											    """<unk>""",
											]
											__magic_name__:	List[str]							=       dict(zip(__snake_case     ,		range(len(__snake_case					)					)					)					)
											__magic_name__:	Tuple							=       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
											__magic_name__:	Optional[int]							=       {"""unk_token""": """<unk>"""}

											__magic_name__:	List[Any]							=       os.path.join(self.tmpdirname     ,		VOCAB_FILES_NAMES["""vocab_file"""]					)
											__magic_name__:	int							=       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(__snake_case					) + """\n"""					)
											with open(self.merges_file     ,		"""w"""     ,		encoding="""utf-8"""					) as fp:
																	fp.write("""\n""".join(__snake_case					)					)

					def   lowerCamelCase__   (			self  :      Optional[Any]     ,		**__snake_case  :      str					)			->							str:
											kwargs.update(self.special_tokens_map					)
											return self.tokenizer_class.from_pretrained(self.tmpdirname     ,		**__snake_case					)

					def   lowerCamelCase__   (			self  :      Any     ,		**__snake_case  :      Optional[Any]					)			->							Optional[Any]:
											kwargs.update(self.special_tokens_map					)
											return RobertaTokenizerFast.from_pretrained(self.tmpdirname     ,		**__snake_case					)

					def   lowerCamelCase__   (			self  :      List[str]     ,		__snake_case  :      Optional[Any]					)			->							List[Any]:
											__magic_name__:	List[str]							=       """lower newer"""
											__magic_name__:	Optional[int]							=       """lower newer"""
											return input_text, output_text

					def   lowerCamelCase__   (			self  :      List[str]					)			->							Optional[Any]:
											__magic_name__:	List[str]							=       self.tokenizer_class(self.vocab_file     ,		self.merges_file     ,		**self.special_tokens_map					)
											__magic_name__:	List[Any]							=       """lower newer"""
											__magic_name__:	List[str]							=       ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
											__magic_name__:	Optional[int]							=       tokenizer.tokenize(__snake_case					)  # , add_prefix_space=True)
											self.assertListEqual(__snake_case     ,		__snake_case					)

											__magic_name__:	int							=       tokens + [tokenizer.unk_token]
											__magic_name__:	Tuple							=       [0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case					)     ,		__snake_case					)

					def   lowerCamelCase__   (			self  :      List[str]					)			->							Optional[int]:
											__magic_name__:	int							=       self.get_tokenizer()

											self.assertListEqual(tokenizer.encode("""Hello world!"""     ,		add_special_tokens=__snake_case					)     ,		[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=__snake_case					)     ,		[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   lowerCamelCase__   (			self  :      Any					)			->							List[str]:
											__magic_name__:	Any							=       self.tokenizer_class.from_pretrained("""roberta-base"""					)

											__magic_name__:	List[str]							=       tokenizer.encode("""sequence builders"""     ,		add_special_tokens=__snake_case					)
											__magic_name__:	Union[str, Any]							=       tokenizer.encode("""multi-sequence build"""     ,		add_special_tokens=__snake_case					)

											__magic_name__:	Optional[Any]							=       tokenizer.encode(
											    """sequence builders"""     ,		add_special_tokens=__snake_case     ,		add_prefix_space=__snake_case					)
											__magic_name__:	List[str]							=       tokenizer.encode(
											    """sequence builders"""     ,		"""multi-sequence build"""     ,		add_special_tokens=__snake_case     ,		add_prefix_space=__snake_case					)

											__magic_name__:	Union[str, Any]							=       tokenizer.build_inputs_with_special_tokens(__snake_case					)
											__magic_name__:	Optional[Any]							=       tokenizer.build_inputs_with_special_tokens(__snake_case     ,		__snake_case					)

											assert encoded_sentence == encoded_text_from_decode
											assert encoded_pair == encoded_pair_from_decode

					def   lowerCamelCase__   (			self  :      int					)			->							str:
											__magic_name__:	int							=       self.get_tokenizer()

											__magic_name__:	Tuple							=       """Encode this sequence."""
											__magic_name__:	List[str]							=       tokenizer.byte_encoder[""" """.encode("""utf-8"""					)[0]]

											# Testing encoder arguments
											__magic_name__:	Optional[Any]							=       tokenizer.encode(__snake_case     ,		add_special_tokens=__snake_case     ,		add_prefix_space=__snake_case					)
											__magic_name__:	Optional[Any]							=       tokenizer.convert_ids_to_tokens(encoded[0]					)[0]
											self.assertNotEqual(__snake_case     ,		__snake_case					)

											__magic_name__:	Union[str, Any]							=       tokenizer.encode(__snake_case     ,		add_special_tokens=__snake_case     ,		add_prefix_space=__snake_case					)
											__magic_name__:	Optional[Any]							=       tokenizer.convert_ids_to_tokens(encoded[0]					)[0]
											self.assertEqual(__snake_case     ,		__snake_case					)

											tokenizer.add_special_tokens({"""bos_token""": """<s>"""}					)
											__magic_name__:	Union[str, Any]							=       tokenizer.encode(__snake_case     ,		add_special_tokens=__snake_case					)
											__magic_name__:	Optional[Any]							=       tokenizer.convert_ids_to_tokens(encoded[1]					)[0]
											self.assertNotEqual(__snake_case     ,		__snake_case					)

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

											__magic_name__:	int							=       """Encode <mask> sequence"""
											__magic_name__:	List[Any]							=       """Encode <mask>sequence"""

											__magic_name__:	Union[str, Any]							=       tokenizer.encode(__snake_case					)
											__magic_name__:	Optional[Any]							=       encoded.index(__snake_case					)
											__magic_name__:	Tuple							=       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]					)[0]
											self.assertEqual(__snake_case     ,		__snake_case					)

											__magic_name__:	List[str]							=       tokenizer.encode(__snake_case					)
											__magic_name__:	Any							=       encoded.index(__snake_case					)
											__magic_name__:	str							=       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]					)[0]
											self.assertNotEqual(__snake_case     ,		__snake_case					)

					def   lowerCamelCase__   (			self  :      str					)			->							int:
											pass

					def   lowerCamelCase__   (			self  :      str					)			->							Tuple:
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'					):
																							__magic_name__:	Tuple							=       self.rust_tokenizer_class.from_pretrained(__snake_case     ,		**__snake_case					)
																							__magic_name__:	List[Any]							=       self.tokenizer_class.from_pretrained(__snake_case     ,		**__snake_case					)
																							__magic_name__:	List[Any]							=       """A, <mask> AllenNLP sentence."""
																							__magic_name__:	Optional[Any]							=       tokenizer_r.encode_plus(__snake_case     ,		add_special_tokens=__snake_case     ,		return_token_type_ids=__snake_case					)
																							__magic_name__:	str							=       tokenizer_p.encode_plus(__snake_case     ,		add_special_tokens=__snake_case     ,		return_token_type_ids=__snake_case					)

																							# 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"""]					)     ,		)

																							__magic_name__:	List[str]							=       tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]					)
																							__magic_name__:	List[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(
																							    __snake_case     ,		["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]					)
																							self.assertSequenceEqual(
																							    __snake_case     ,		["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]					)

					def   lowerCamelCase__   (			self  :      Tuple					)			->							str:
											for trim_offsets, add_prefix_space in itertools.product([True, False]     ,		repeat=2					):
																	__magic_name__:	Union[str, Any]							=       self.rust_tokenizer_class.from_pretrained(
																	    self.tmpdirname     ,		use_fast=__snake_case     ,		add_prefix_space=__snake_case     ,		trim_offsets=__snake_case					)

																	__magic_name__:	Any							=       json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()					)
																	__magic_name__:	Any							=       json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()					)

																	self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]     ,		__snake_case					)

																	self.assertEqual(post_processor_state["""add_prefix_space"""]     ,		__snake_case					)
																	self.assertEqual(post_processor_state["""trim_offsets"""]     ,		__snake_case					)






					def   lowerCamelCase__   (			self  :      Any					)			->							Tuple:
											# 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})'					):
																							__magic_name__:	List[Any]							=       """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
																							__magic_name__:	Union[str, Any]							=       F'{text_of_1_token} {text_of_1_token}'

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

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

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

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

																							__magic_name__:	Dict							=       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)),
																							# )

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

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

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











"""simple docstring"""





def   a    (     __UpperCAmelCase      :    List[Any]  )    ->							str:
						__magic_name__:	Optional[int]							=       [0] * len(__UpperCAmelCase  )
						__magic_name__:	str							=       []
						__magic_name__:	Any							=       []
						__magic_name__:	Union[str, Any]							=       0

						for values in graph.values():
												for i in values:
																		indegree[i] += 1

						for i in range(len(__UpperCAmelCase  )  ):
												if indegree[i] == 0:
																		queue.append(__UpperCAmelCase  )

						while queue:
												__magic_name__:	Optional[Any]							=       queue.pop(0  )
												cnt += 1
												topo.append(__UpperCAmelCase  )
												for x in graph[vertex]:
																		indegree[x] -= 1
																		if indegree[x] == 0:
																								queue.append(__UpperCAmelCase  )

						if cnt != len(__UpperCAmelCase  ):
												print("""Cycle exists"""  )
						else:
												print(__UpperCAmelCase  )


# Adjacency List of Graph
__lowerCamelCase							=  {0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}

topological_sort(graph)



