



"""simple docstring"""







__snake_case	:				Tuple  					=			float('inf')

class       UpperCamelCase  :





     """simple docstring"""






     def __init__(					self :							List[Any]	,      _lowerCamelCase :							Any ):
          A__				=   [0] * n
          A__				=   [0] * n
          A__				=   [0] * n
          A__				=   [[] for _ in range(_lowerCamelCase )]





     def 						A__  (					self :							Tuple	,      _lowerCamelCase :							Tuple	,      _lowerCamelCase :							List[str]	,      _lowerCamelCase :							Optional[Any]	,      _lowerCamelCase :							Any=0 ):
          self.adj[a].append([b, len(self.adj[b] ), c, 0] )
          self.adj[b].append([a, len(self.adj[a] ) - 1, rcap, 0] )





     def 						A__  (					self :							int	,      _lowerCamelCase :							int	,      _lowerCamelCase :							str	,      _lowerCamelCase :							Any ):
          if vertex == sink or not flow:
               return flow

          for i in range(self.ptr[vertex]	,      len(self.adj[vertex] ) ):
               A__				=   self.adj[vertex][i]
               if self.lvl[e[0]] == self.lvl[vertex] + 1:
                    A__				=   self.depth_first_search(e[0]	,      _lowerCamelCase	,      min(_lowerCamelCase	,      e[2] - e[3] ) )
                    if p:
                         self.adj[vertex][i][3] += p
                         self.adj[e[0]][e[1]][3] -= p
                         return p
               A__				=   self.ptr[vertex] + 1
          return 0





     def 						A__  (					self :							str	,      _lowerCamelCase :							Any	,      _lowerCamelCase :							Dict ):
          A__	,     A__				=   0, source
          for l in range(3_1 ):  # noqa: E741  l = 30 maybe faster for random data
               while True:
                    A__	,     A__				=   [0] * len(self.q ), [0] * len(self.q )
                    A__	,     A__	,     A__				=   0, 1, 1
                    while qi < qe and not self.lvl[sink]:
                         A__				=   self.q[qi]
                         qi += 1
                         for e in self.adj[v]:
                              if not self.lvl[e[0]] and (e[2] - e[3]) >> (3_0 - l):
                                   A__				=   e[0]
                                   qe += 1
                                   A__				=   self.lvl[v] + 1

                    A__				=   self.depth_first_search(_lowerCamelCase	,      _lowerCamelCase	,      _lowerCamelCase )
                    while p:
                         flow += p
                         A__				=   self.depth_first_search(_lowerCamelCase	,      _lowerCamelCase	,      _lowerCamelCase )

                    if not self.lvl[sink]:
                         break

          return flow
__snake_case	:				str  					=			Dinic(10)
__snake_case	:				List[str]  					=			0
__snake_case	:				Tuple  					=			9
for vertex in range(1, 5):
 graph.add_edge(source, vertex, 1)
for vertex in range(5, 9):
 graph.add_edge(vertex, sink, 1)
for vertex in range(1, 5):
 graph.add_edge(vertex, vertex + 4, 1)

# Now we can know that is the maximum flow(source -> sink)
print(graph.max_flow(source, sink))








"""simple docstring"""







import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class       UpperCamelCase  (					a      , unittest.TestCase				):





     """simple docstring"""






     _lowerCamelCase					: Dict				   =HerbertTokenizer
     _lowerCamelCase					: Optional[int]				   =HerbertTokenizerFast
     _lowerCamelCase					: Optional[Any]				   =True





     def 						A__  (					self :							Dict ):
          super().setUp()

          # Use a simpler test file without japanese/chinese characters
          with open(F'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''	,      encoding='''utf-8''' ) as f_data:
               A__				=   f_data.read().replace('''\n\n'''	,      '''\n''' ).strip()

          A__				=   [
              '''<s>''',
              '''</s>''',
              '''l''',
              '''o''',
              '''w''',
              '''e''',
              '''r''',
              '''s''',
              '''t''',
              '''i''',
              '''d''',
              '''n''',
              '''w</w>''',
              '''r</w>''',
              '''t</w>''',
              '''lo''',
              '''low''',
              '''er</w>''',
              '''low</w>''',
              '''lowest</w>''',
              '''newer</w>''',
              '''wider</w>''',
              ''',</w>''',
              '''<unk>''',
          ]
          A__				=   dict(zip(_lowerCamelCase	,      range(len(_lowerCamelCase ) ) ) )
          A__				=   ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

          A__				=   os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES['''vocab_file'''] )
          A__				=   os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES['''merges_file'''] )
          with open(self.vocab_file	,      '''w''' ) as fp:
               fp.write(json.dumps(_lowerCamelCase ) )
          with open(self.merges_file	,      '''w''' ) as fp:
               fp.write('''\n'''.join(_lowerCamelCase ) )





     def 						A__  (					self :							List[Any]	,      _lowerCamelCase :							Union[str, Any] ):
          A__				=   '''lower newer'''
          A__				=   '''lower newer'''
          return input_text, output_text





     def 						A__  (					self :							int ):
          A__				=   self.tokenizer_class(vocab_file=self.vocab_file	,      merges_file=self.merges_file )

          A__				=   '''lower'''
          A__				=   ['''low''', '''er</w>''']
          A__				=   tokenizer.tokenize(_lowerCamelCase )
          self.assertListEqual(_lowerCamelCase	,      _lowerCamelCase )

          A__				=   tokens + ['''<unk>''']
          A__				=   [1_6, 1_7, 2_3]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase )	,      _lowerCamelCase )





     def 						A__  (					self :							Optional[int] ):
          if not self.test_rust_tokenizer:
               return

          A__				=   self.get_tokenizer()
          A__				=   self.get_rust_tokenizer()

          A__				=   '''lower,newer'''

          A__				=   tokenizer.tokenize(_lowerCamelCase )
          A__				=   rust_tokenizer.tokenize(_lowerCamelCase )
          self.assertListEqual(_lowerCamelCase	,      _lowerCamelCase )

          A__				=   tokenizer.encode(_lowerCamelCase	,      add_special_tokens=_lowerCamelCase )
          A__				=   rust_tokenizer.encode(_lowerCamelCase	,      add_special_tokens=_lowerCamelCase )
          self.assertListEqual(_lowerCamelCase	,      _lowerCamelCase )

          A__				=   self.get_rust_tokenizer()
          A__				=   tokenizer.encode(_lowerCamelCase )
          A__				=   rust_tokenizer.encode(_lowerCamelCase )
          self.assertListEqual(_lowerCamelCase	,      _lowerCamelCase )





     @slow
     def 						A__  (					self :							Any ):
          A__				=   self.tokenizer_class.from_pretrained('''allegro/herbert-base-cased''' )

          A__				=   tokenizer.encode('''konstruowanie sekwencji'''	,      add_special_tokens=_lowerCamelCase )
          A__				=   tokenizer.encode('''konstruowanie wielu sekwencji'''	,      add_special_tokens=_lowerCamelCase )

          A__				=   tokenizer.build_inputs_with_special_tokens(_lowerCamelCase )
          A__				=   tokenizer.build_inputs_with_special_tokens(_lowerCamelCase	,      _lowerCamelCase )

          assert encoded_sentence == [0] + text + [2]
          assert encoded_pair == [0] + text + [2] + text_a + [2]



