



"""simple docstring"""




from __future__ import annotations


def   lowercase__     (			_UpperCAmelCase				)     ->			int:






      '''simple docstring'''


      global graph, reversed_graph, scc, component, visit, stack
      if visit[u]:
            return
      lowercase  :      Tuple					=   True
      for v in graph[u]:
            dfs(_UpperCAmelCase				)
      stack.append(_UpperCAmelCase				)


def   lowercase__     (			_UpperCAmelCase				)     ->			List[Any]:






      '''simple docstring'''


      global graph, reversed_graph, scc, component, visit, stack
      if visit[u]:
            return
      lowercase  :      str					=   True
      component.append(_UpperCAmelCase				)
      for v in reversed_graph[u]:
            dfsa(_UpperCAmelCase				)


def   lowercase__     (			)     ->			Optional[int]:






      '''simple docstring'''


      global graph, reversed_graph, scc, component, visit, stack
      for i in range(_UpperCAmelCase				):
            dfs(_UpperCAmelCase				)
      lowercase  :      Dict					=   [False] * n
      for i in stack[::-1]:
            if visit[i]:
                  continue
            lowercase  :      Dict					=   []
            dfsa(_UpperCAmelCase				)
            scc.append(_UpperCAmelCase				)
      return scc


if __name__ == "__main__":
     # n - no of nodes, m - no of edges
     _UpperCamelCase:				Tuple    							=  list(map(int, input().strip().split()))

     _UpperCamelCase:				list[list[int]]    							=  [[] for _ in range(n)]  # graph
     _UpperCamelCase:				list[list[int]]    							=  [[] for i in range(n)]  # reversed graph
     # input graph data (edges)
     for _ in range(m):
          _UpperCamelCase:				Optional[int]    							=  list(map(int, input().strip().split()))
          graph[u].append(v)
          reversed_graph[v].append(u)

     _UpperCamelCase:				list[int]    							=  []
     _UpperCamelCase:				list[bool]    							=  [False] * n
     _UpperCamelCase:				list[int]    							=  []
     _UpperCamelCase:				list[int]    							=  []
     print(kosaraju())





"""simple docstring"""




import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata


def   lowercase__     (			_UpperCAmelCase				)     ->			str:






      '''simple docstring'''


      lowercase  :      List[str]					=   min(re.search('^ +'	,      _UpperCAmelCase				).end() if t.startswith(' '				) else 0 for t in string.splitlines()				)
      return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(_UpperCAmelCase				)]				)


_UpperCamelCase:				Any    							=  '\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n'

_UpperCamelCase:				Dict    							=  '\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n'


_UpperCamelCase:				Dict    							=  '\\n# Begin of markdown\n\nSome cool dataset card\n'





class   a__		(						unittest.TestCase     ):


   def        lowercase				(							self      :							int			)    ->       Dict:
         with tempfile.TemporaryDirectory() as tmp_dir:
               lowercase  :      Tuple					=   Path(lowerCAmelCase			) / 'README.md'
               with open(lowerCAmelCase,     'w+'			) as readme_file:
                     readme_file.write(lowerCAmelCase			)
               lowercase  :      List[str]					=   DatasetMetadata.from_readme(lowerCAmelCase			)
               self.assertDictEqual(lowerCAmelCase,     {'language': ['zh', 'en'], 'task_ids': ['sentiment-classification']}			)

               with open(lowerCAmelCase,     'w+'			) as readme_file:
                     readme_file.write(lowerCAmelCase			)
               lowercase  :      str					=   DatasetMetadata.from_readme(lowerCAmelCase			)
               self.assertDictEqual(lowerCAmelCase,     {}			)

               with open(lowerCAmelCase,     'w+'			) as readme_file:
                     readme_file.write(lowerCAmelCase			)
               lowercase  :      Optional[Any]					=   DatasetMetadata.from_readme(lowerCAmelCase			)
               self.assertEqual(lowerCAmelCase,     {}			)






   def        lowercase				(							self      :							Optional[Any]			)    ->       List[Any]:
         lowercase  :      Union[str, Any]					=   _dedent(
             '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            '			)
         assert DatasetMetadata.from_yaml_string(lowerCAmelCase			)

         lowercase  :      Any					=   _dedent(
             '\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            '			)
         with self.assertRaises(lowerCAmelCase			):
               DatasetMetadata.from_yaml_string(lowerCAmelCase			)

         lowercase  :      int					=   _dedent(
             '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the "Researcher") has requested permission to use the ImageNet database (the "Database") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            '			)
         assert DatasetMetadata.from_yaml_string(lowerCAmelCase			)
