code: 
  
  
  """simple docstring"""
  
  
  
  
  __SCREAMING_SNAKE_CASE					=						float("""inf""")
  
  
  
  
  
  class __snake_case		:
  
  
  
  
  
  
  
  			"""simple docstring"""
  
  
  
  
  			def __init__(		self							:int				,  UpperCamelCase__							:Any       ):
  										_a          =				[0] * n
  										_a          =				[0] * n
  										_a          =				[0] * n
  										_a          =				[[] for _ in range(__UpperCamelCase       )]
  
  
  
  
  			def SCREAMING_SNAKE_CASE_      (		self							:Optional[Any]				,  UpperCamelCase__							:Optional[Any]				,  UpperCamelCase__							:Union[str, Any]				,  UpperCamelCase__							:List[str]				,  UpperCamelCase__							:Optional[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 SCREAMING_SNAKE_CASE_      (		self							:Union[str, Any]				,  UpperCamelCase__							:Dict				,  UpperCamelCase__							:List[str]				,  UpperCamelCase__							:Optional[int]       ):
  
  
  										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]				,  __UpperCamelCase				,  min(__UpperCamelCase				,  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 SCREAMING_SNAKE_CASE_      (		self							:List[Any]				,  UpperCamelCase__							:List[str]				,  UpperCamelCase__							:str       ):
  										_a          =				0, source
  										for l in range(31       ):  # noqa: E741  l = 30 maybe faster for random data
  																	while True:
  																								_a          =				[0] * len(self.q       ), [0] * len(self.q       )
  																								_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]) >> (30 - l):
  																																													_a          =				e[0]
  																																													qe += 1
  																																													_a          =				self.lvl[v] + 1
  
  																								_a          =				self.depth_first_search(__UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase       )
  																								while p:
  																															flow += p
  																															_a          =				self.depth_first_search(__UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase       )
  
  																								if not self.lvl[sink]:
  																															break
  
  										return flow
  
  
  
  
  
  
  __SCREAMING_SNAKE_CASE					=						Dinic(10)
  __SCREAMING_SNAKE_CASE					=						0
  __SCREAMING_SNAKE_CASE					=						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))
  
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  # Copyright 2022 The HuggingFace Team. All rights reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  import os
  from typing import List
  
  
  
  def 						__a      (  a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         if name != "training_function" and name != "main":
                raise ValueError(F'Incorrect function name passed: {name}, choose either \'main\' or \'training_function\''					)
         _a   , _a          =				[], False
         for line in lines:
                if not found_start and F'def {name}' in line:
                       _a          =				True
                       good_lines.append(a					)
                       continue
                if found_start:
                       if name == "training_function" and "def main" in line:
                              return good_lines
                       if name == "main" and "if __name__" in line:
                              return good_lines
                       good_lines.append(a					)
  
  
  
  def 						__a      (  a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         return [line for line in lines if not line.lstrip().startswith("#"					) and line != "\n"]
  
  
  
  def 						__a      (  a,		a,		a,		a = None					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         with open(a,		"r"					) as f:
                _a          =				f.readlines()
         with open(os.path.abspath(os.path.join("examples",		"nlp_example.py"					)					),		"r"					) as f:
                _a          =				f.readlines()
         with open(a,		"r"					) as f:
                _a          =				f.readlines()
         if secondary_filename is not None:
                with open(a,		"r"					) as f:
                       _a          =				f.readlines()
  
      # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
         if parser_only:
                _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
                if secondary_filename is not None:
                       _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
         else:
                _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
                if secondary_filename is not None:
                       _a          =				clean_lines(
                           get_function_contents_by_name(a,		"training_function"					)					)
  
         _a          =				"train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n"
  
         # Specific code in our script that differs from the full version, aka what is new
         _a          =				[]
         _a          =				[]  # We keep track of the idxs just in case it's a repeated statement
         _a          =				iter(a					)
         for i in range(len(a					) - 1					):
                if i not in passed_idxs:
                       _a          =				next(a					)
                       if (line not in full_file_func) and (line.lstrip() != _dl_line):
                              if "TESTING_MOCKED_DATALOADERS" not in line:
                                     new_feature_code.append(a					)
                                     passed_idxs.append(a					)
                              else:
                                     # Skip over the `config['num_epochs'] = 2` statement
                                     _a          =				next(a					)
  
      # Extract out just the new parts from the full_file_training_func
         _a          =				[]
         _a          =				[]  # We keep track of the idxs just in case it's a repeated statement
         for i, line in enumerate(a					):
                if i not in passed_idxs:
                       if (line not in full_file_func) and (line.lstrip() != _dl_line):
                              if "TESTING_MOCKED_DATALOADERS" not in line:
                                     new_full_example_parts.append(a					)
                                     passed_idxs.append(a					)
  
      # Finally, get the overall diff
         _a          =				[line for line in new_feature_code if line not in new_full_example_parts]
         if secondary_filename is not None:
                _a          =				[line for line in full_file_contents if line not in secondary_file_func]
                _a          =				[line for line in diff_from_example if line not in diff_from_two]
  
         return diff_from_example
  