






import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
    from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
    import torch_xla.core.xla_model as xm
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	List[str]				)->Optional[int]:
      if is_torch_version('''<'''     ,				'''2.0.0'''				) or not hasattr(__lowerCAmelCase     ,				'''_dynamo'''				):
            return False
      return isinstance(__lowerCAmelCase     ,				torch._dynamo.eval_frame.OptimizedModule				)
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Optional[Any]     ,				_SCREAMING_SNAKE_CASE   :	int = True				)->List[str]:
      _lowerCAmelCase 			=  (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

      _lowerCAmelCase 			=  is_compiled_module(__lowerCAmelCase				)
      if is_compiled:
            _lowerCAmelCase 			=  model
            _lowerCAmelCase 			=  model._orig_mod

      if is_deepspeed_available():
            options += (DeepSpeedEngine,)

      while isinstance(__lowerCAmelCase     ,				__lowerCAmelCase				):
            _lowerCAmelCase 			=  model.module

      if not keep_fpaa_wrapper:
            _lowerCAmelCase 			=  getattr(__lowerCAmelCase     ,				'''forward'''				)
            _lowerCAmelCase 			=  model.__dict__.pop('''_original_forward'''     ,				__lowerCAmelCase				)
            if original_forward is not None:
                  while hasattr(__lowerCAmelCase     ,				'''__wrapped__'''				):
                        _lowerCAmelCase 			=  forward.__wrapped__
                        if forward == original_forward:
                              break
                  _lowerCAmelCase 			=  forward
            if getattr(__lowerCAmelCase     ,				'''_converted_to_transformer_engine'''     ,				__lowerCAmelCase				):
                  convert_model(__lowerCAmelCase     ,				to_transformer_engine=__lowerCAmelCase				)

      if is_compiled:
            _lowerCAmelCase 			=  model
            _lowerCAmelCase 			=  compiled_model

      return model
def 							UpperCAmelCase__		(				)->Dict:
      PartialState().wait_for_everyone()
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	str     ,				_SCREAMING_SNAKE_CASE   :	Optional[int]				)->str:
      if PartialState().distributed_type == DistributedType.TPU:
            xm.save(__lowerCAmelCase     ,				__lowerCAmelCase				)
      elif PartialState().local_process_index == 0:
            torch.save(__lowerCAmelCase     ,				__lowerCAmelCase				)
@contextmanager
def 							UpperCAmelCase__		(				**_SCREAMING_SNAKE_CASE   :	List[Any]				)->Optional[Any]:
      for key, value in kwargs.items():
            _lowerCAmelCase 			=  str(__lowerCAmelCase				)

      yield

      for key in kwargs:
            if key.upper() in os.environ:
                  del os.environ[key.upper()]
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Optional[int]				)->str:
      if not hasattr(__lowerCAmelCase     ,				'''__qualname__'''				) and not hasattr(__lowerCAmelCase     ,				'''__name__'''				):
            _lowerCAmelCase 			=  getattr(__lowerCAmelCase     ,				'''__class__'''     ,				__lowerCAmelCase				)
      if hasattr(__lowerCAmelCase     ,				'''__qualname__'''				):
            return obj.__qualname__
      if hasattr(__lowerCAmelCase     ,				'''__name__'''				):
            return obj.__name__
      return str(__lowerCAmelCase				)
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	List[str]     ,				_SCREAMING_SNAKE_CASE   :	List[str]				)->Dict:
      for key, value in source.items():
            if isinstance(__lowerCAmelCase     ,				__lowerCAmelCase				):
                  _lowerCAmelCase 			=  destination.setdefault(__lowerCAmelCase     ,				{}				)
                  merge_dicts(__lowerCAmelCase     ,				__lowerCAmelCase				)
            else:
                  _lowerCAmelCase 			=  value

      return destination


def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Dict = None				)->List[str]:
      if port is None:
            _lowerCAmelCase 			=  2_9_5_0_0
      with socket.socket(socket.AF_INET     ,				socket.SOCK_STREAM				) as s:
            return s.connect_ex(('''localhost''', port)				) == 0




def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Optional[Any]				)->Any:  # noqa: E741
      _lowerCAmelCase 			=  len(_SCREAMING_SNAKE_CASE				)
      _lowerCAmelCase 			=  0
      _lowerCAmelCase 			=  [0] * n
      _lowerCAmelCase 			=  [False] * n
      _lowerCAmelCase 			=  [False] * n

      def dfs(_SCREAMING_SNAKE_CASE   :	List[str]     ,				_SCREAMING_SNAKE_CASE   :	List[Any]     ,				_SCREAMING_SNAKE_CASE   :	Optional[int]     ,				_SCREAMING_SNAKE_CASE   :	int				):
            if parent == root:
                  out_edge_count += 1
            _lowerCAmelCase 			=  True
            _lowerCAmelCase 			=  at

            for to in l[at]:
                  if to == parent:
                        pass
                  elif not visited[to]:
                        _lowerCAmelCase 			=  dfs(_SCREAMING_SNAKE_CASE     ,				_SCREAMING_SNAKE_CASE     ,				_SCREAMING_SNAKE_CASE     ,				_SCREAMING_SNAKE_CASE				)
                        _lowerCAmelCase 			=  min(low[at]     ,				low[to]				)

                        # AP found via bridge
                        if at < low[to]:
                              _lowerCAmelCase 			=  True
                        # AP found via cycle
                        if at == low[to]:
                              _lowerCAmelCase 			=  True
                  else:
                        _lowerCAmelCase 			=  min(low[at]     ,				_SCREAMING_SNAKE_CASE				)
            return out_edge_count

      for i in range(_SCREAMING_SNAKE_CASE				):
            if not visited[i]:
                  _lowerCAmelCase 			=  0
                  _lowerCAmelCase 			=  dfs(_SCREAMING_SNAKE_CASE     ,				_SCREAMING_SNAKE_CASE     ,				-1     ,				_SCREAMING_SNAKE_CASE				)
                  _lowerCAmelCase 			=  out_edge_count > 1

      for x in range(len(_SCREAMING_SNAKE_CASE				)				):
            if is_art[x] is True:
                  print(_SCREAMING_SNAKE_CASE				)


# Adjacency list of graph
UpperCAmelCase_									=							{
    0: [1, 2],
    1: [0, 2],
    2: [0, 1, 3, 5],
    3: [2, 4],
    4: [3],
    5: [2, 6, 8],
    6: [5, 7],
    7: [6, 8],
    8: [5, 7],
}


compute_ap(data)