code: 
  
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  lowerCamelCase										=  {
      '''configuration_mobilenet_v1''': [
          '''MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP''',
          '''MobileNetV1Config''',
          '''MobileNetV1OnnxConfig''',
      ],
  }
  
  try:
     if not is_vision_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     lowerCamelCase										=  ['''MobileNetV1FeatureExtractor''']
     lowerCamelCase										=  ['''MobileNetV1ImageProcessor''']
  
  try:
     if not is_torch_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     lowerCamelCase										=  [
         '''MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''MobileNetV1ForImageClassification''',
         '''MobileNetV1Model''',
         '''MobileNetV1PreTrainedModel''',
         '''load_tf_weights_in_mobilenet_v1''',
     ]
  
  
  if TYPE_CHECKING:
     from .configuration_mobilenet_va import (
         MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
         MobileNetVaConfig,
         MobileNetVaOnnxConfig,
     )
  
     try:
        if not is_vision_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
        from .image_processing_mobilenet_va import MobileNetVaImageProcessor
  
     try:
        if not is_torch_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .modeling_mobilenet_va import (
            MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
            MobileNetVaForImageClassification,
            MobileNetVaModel,
            MobileNetVaPreTrainedModel,
            load_tf_weights_in_mobilenet_va,
        )
  
  
  else:
     import sys
  
     lowerCamelCase										=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
style_context: 
  
  
  
  
  
  
  from __future__ import annotations
  def        UpperCAmelCase      (   _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      global graph, reversed_graph, scc, component, visit, stack
      if visit[u]:
          return
      _lowercase     =	True
      for v in graph[u]:
          dfs(_lowercase      )
      stack.append(_lowercase      )
  def        UpperCAmelCase      (   _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      global graph, reversed_graph, scc, component, visit, stack
      if visit[u]:
          return
      _lowercase     =	True
      component.append(_lowercase      )
      for v in reversed_graph[u]:
          dfsa(_lowercase      )
  def        UpperCAmelCase      (   ):
  
  
      '''simple docstring'''
  
  
  
      global graph, reversed_graph, scc, component, visit, stack
      for i in range(_lowercase      ):
          dfs(_lowercase      )
      _lowercase     =	[False] * n
      for i in stack[::-1]:
          if visit[i]:
              continue
          _lowercase     =	[]
          dfsa(_lowercase      )
          scc.append(_lowercase      )
      return scc
  
  
  if __name__ == "__main__":
     # n - no of nodes, m - no of edges
     lowerCamelCase						,		lowerCamelCase										=  list(map(int, input().strip().split()))
  
     lowerCamelCase										=  [[] for _ in range(n)]  # graph
     lowerCamelCase										=  [[] for i in range(n)]  # reversed graph
     # input graph data (edges)
     for _ in range(m):
        lowerCamelCase						,		lowerCamelCase										=  list(map(int, input().strip().split()))
        graph[u].append(v)
        reversed_graph[v].append(u)
  
     lowerCamelCase										=  []
     lowerCamelCase										=  [False] * n
     lowerCamelCase										=  []
     lowerCamelCase										=  []
     print(kosaraju())
  