



import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_snake_case		=  get_tests_dir("fixtures/test_sentencepiece_bpe.model")



class   UpperCAmelCase_    (       a   ,					unittest.TestCase):
							lowerCamelCase__   			=		BartphoTokenizer
							lowerCamelCase__   			=		False
							lowerCamelCase__   			=		True







							def    snake_case__      (   self):

														'''simple docstring'''

														super().setUp()

														_lowerCAmelCase     :							str    =    ["▁This", "▁is", "▁a", "▁t", "est"]
														_lowerCAmelCase     :							List[str]    =    dict(zip(__a,			range(len(__a))))
														_lowerCAmelCase     :							Optional[Any]    =    {"unk_token": "<unk>"}

														_lowerCAmelCase     :							Optional[int]    =    os.path.join(self.tmpdirname,			VOCAB_FILES_NAMES["monolingual_vocab_file"])
														with open(self.monolingual_vocab_file,			"w",			encoding="utf-8") as fp:
																					for token in vocab_tokens:
																												fp.write(f"{token} {vocab_tokens[token]}\n")

														_lowerCAmelCase     :							Optional[Any]    =    BartphoTokenizer(__a,			self.monolingual_vocab_file,			**self.special_tokens_map)
														tokenizer.save_pretrained(self.tmpdirname)







							def    snake_case__      (   self,			**__a):

														'''simple docstring'''

														kwargs.update(self.special_tokens_map)
														return BartphoTokenizer.from_pretrained(self.tmpdirname,			**__a)







							def    snake_case__      (   self,			__a):

														'''simple docstring'''

														_lowerCAmelCase     :							Union[str, Any]    =    "This is a là test"
														_lowerCAmelCase     :							Optional[int]    =    "This is a<unk><unk> test"
														return input_text, output_text







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[int]    =    BartphoTokenizer(__a,			self.monolingual_vocab_file,			**self.special_tokens_map)
														_lowerCAmelCase     :							List[Any]    =    "This is a là test"
														_lowerCAmelCase     :							str    =    "▁This ▁is ▁a ▁l à ▁t est".split()
														_lowerCAmelCase     :							str    =    tokenizer.tokenize(__a)
														self.assertListEqual(__a,			__a)

														_lowerCAmelCase     :							Tuple    =    tokens + [tokenizer.unk_token]
														_lowerCAmelCase     :							List[str]    =    [4, 5, 6, 3, 3, 7, 8, 3]
														self.assertListEqual(tokenizer.convert_tokens_to_ids(__a),			__a)







"""simple docstring"""
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.






def 					A__				(			UpperCamelCase       ):
							A		=  [False] * len(UpperCamelCase       )
							A		=  [-1] * len(UpperCamelCase       )

							def dfs(UpperCamelCase					,  UpperCamelCase       ):
														A		=  True
														A		=  c
														for u in graph[v]:
																					if not visited[u]:
																												dfs(UpperCamelCase					,  1 - c       )

							for i in range(len(UpperCamelCase       )       ):
														if not visited[i]:
																					dfs(UpperCamelCase					,  0       )

							for i in range(len(UpperCamelCase       )       ):
														for j in graph[i]:
																					if color[i] == color[j]:
																												return False

							return True


# Adjacency list of graph
_snake_case     :		str       						= {0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}
print(check_bipartite_dfs(graph))


