





"""simple docstring"""






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      __A   (      a_    :Dict)		->		Tuple:
				if is_torch_version('''<''' ,							'''2.0.0''') or not hasattr(a_ ,							'''_dynamo'''):
								return False
				return isinstance(a_ ,							torch._dynamo.eval_frame.OptimizedModule)

def      __A   (      a_    :Any ,							a_    :bool = True)		->		List[str]:
				__a			:    Any      							=	(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

				__a			:    Tuple      							=	is_compiled_module(a_)
				if is_compiled:
								__a			:    Tuple      							=	model
								__a			:    Optional[int]      							=	model._orig_mod

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

				while isinstance(a_ ,							a_):
								__a			:    Tuple      							=	model.module

				if not keep_fpaa_wrapper:
								__a			:    Tuple      							=	getattr(a_ ,							'''forward''')
								__a			:    List[str]      							=	model.__dict__.pop('''_original_forward''' ,							a_)
								if original_forward is not None:
												while hasattr(a_ ,							'''__wrapped__'''):
																__a			:    int      							=	forward.__wrapped__
																if forward == original_forward:
																				break
												__a			:    Tuple      							=	forward
								if getattr(a_ ,							'''_converted_to_transformer_engine''' ,							a_):
												convert_model(a_ ,							to_transformer_engine=a_)

				if is_compiled:
								__a			:    str      							=	model
								__a			:    List[Any]      							=	compiled_model

				return model

def      __A   (      )		->		Union[str, Any]:
				PartialState().wait_for_everyone()

def      __A   (      a_    :List[str] ,							a_    :List[Any])		->		Union[str, Any]:
				if PartialState().distributed_type == DistributedType.TPU:
								xm.save(a_ ,							a_)
				elif PartialState().local_process_index == 0:
								torch.save(a_ ,							a_)

@contextmanager
def      __A   (      **a_    :Optional[int])		->		str:
				for key, value in kwargs.items():
								__a			:    int      							=	str(a_)

				yield

				for key in kwargs:
								if key.upper() in os.environ:
												del os.environ[key.upper()]

def      __A   (      a_    :Any)		->		str:
				if not hasattr(a_ ,							'''__qualname__''') and not hasattr(a_ ,							'''__name__'''):
								__a			:    int      							=	getattr(a_ ,							'''__class__''' ,							a_)
				if hasattr(a_ ,							'''__qualname__'''):
								return obj.__qualname__
				if hasattr(a_ ,							'''__name__'''):
								return obj.__name__
				return str(a_)

def      __A   (      a_    :Any ,							a_    :Any)		->		int:
				for key, value in source.items():
								if isinstance(a_ ,							a_):
												__a			:    Tuple      							=	destination.setdefault(a_ ,							{})
												merge_dicts(a_ ,							a_)
								else:
												__a			:    Tuple      							=	value

				return destination






def      __A   (      a_    :int = None)		->		bool:
				if port is None:
								__a			:    Dict      							=	2_95_00
				with socket.socket(socket.AF_INET ,							socket.SOCK_STREAM) as s:
								return s.connect_ex(('''localhost''', port)) == 0


'''simple docstring'''




def    lowerCamelCase__		(    SCREAMING_SNAKE_CASE   : list[int]							, SCREAMING_SNAKE_CASE   : list[int]							, SCREAMING_SNAKE_CASE   : int    ):
  return not any(
      neighbour == 1 and colored_vertices[i] == color
      for i, neighbour in enumerate(SCREAMING_SNAKE_CASE    )    )


def    lowerCamelCase__		(    SCREAMING_SNAKE_CASE   : list[list[int]]							, SCREAMING_SNAKE_CASE   : int							, SCREAMING_SNAKE_CASE   : list[int]							, SCREAMING_SNAKE_CASE   : int    ):

  # Base Case
  if index == len(SCREAMING_SNAKE_CASE    ):
    return True

  # Recursive Step
  for i in range(SCREAMING_SNAKE_CASE    ):
    if valid_coloring(graph[index]							, SCREAMING_SNAKE_CASE							, SCREAMING_SNAKE_CASE    ):
      # Color current vertex
      UpperCAmelCase    				=						i
      # Validate coloring
      if util_color(SCREAMING_SNAKE_CASE							, SCREAMING_SNAKE_CASE							, SCREAMING_SNAKE_CASE							, index + 1    ):
        return True
      # Backtrack
      UpperCAmelCase    				=						-1
  return False



def    lowerCamelCase__		(    SCREAMING_SNAKE_CASE   : list[list[int]]							, SCREAMING_SNAKE_CASE   : int    ):
  UpperCAmelCase    				=						[-1] * len(SCREAMING_SNAKE_CASE    )

  if util_color(SCREAMING_SNAKE_CASE							, SCREAMING_SNAKE_CASE							, SCREAMING_SNAKE_CASE							, 0    ):
    return colored_vertices

  return []


