

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE		:int				  =    {"""configuration_hubert""": ["""HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """HubertConfig"""]}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:Tuple				  =    [
     """HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """HubertForCTC""",
     """HubertForSequenceClassification""",
     """HubertModel""",
     """HubertPreTrainedModel""",
 ]


try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:Optional[int]				  =    [
     """TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFHubertForCTC""",
     """TFHubertModel""",
     """TFHubertPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_hubert import (
      HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      HubertForCTC,
      HubertForSequenceClassification,
      HubertModel,
      HubertPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_hubert import (
      TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFHubertForCTC,
      TFHubertModel,
      TFHubertPreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE		:int				  =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



from __future__ import annotations




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	str:



    """simple docstring"""






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




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	Dict:



    """simple docstring"""






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




def  lowerCAmelCase(			)->	Dict:



    """simple docstring"""






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


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

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

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