





'''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       lowercase_      (		lowercase__						)   ->str:
						if is_torch_version('<'				,  '2.0.0'						) or not hasattr(lowercase__				,  '_dynamo'						):
												return False
						return isinstance(lowercase__				,  torch._dynamo.eval_frame.OptimizedModule						)





def       lowercase_      (		lowercase__				,  lowercase__ = True						)   ->Any:
						_snake_case:   Any  					=		(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

						_snake_case:   Optional[int]  					=		is_compiled_module(lowercase__						)
						if is_compiled:
												_snake_case:   str  					=		model
												_snake_case:   Tuple  					=		model._orig_mod

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

						while isinstance(lowercase__				,  lowercase__						):
												_snake_case:   str  					=		model.module

						if not keep_fpaa_wrapper:
												_snake_case:   int  					=		getattr(lowercase__				,  'forward'						)
												_snake_case:   Optional[Any]  					=		model.__dict__.pop('_original_forward'				,  lowercase__						)
												if original_forward is not None:
																		while hasattr(lowercase__				,  '__wrapped__'						):
																								_snake_case:   Optional[Any]  					=		forward.__wrapped__
																								if forward == original_forward:
																														break
																		_snake_case:   int  					=		forward
												if getattr(lowercase__				,  '_converted_to_transformer_engine'				,  lowercase__						):
																		convert_model(lowercase__				,  to_transformer_engine=lowercase__						)

						if is_compiled:
												_snake_case:   List[str]  					=		model
												_snake_case:   Dict  					=		compiled_model

						return model





def       lowercase_      (		)   ->int:
						PartialState().wait_for_everyone()





def       lowercase_      (		lowercase__				,  lowercase__						)   ->Optional[Any]:
						if PartialState().distributed_type == DistributedType.TPU:
												xm.save(lowercase__				,  lowercase__						)
						elif PartialState().local_process_index == 0:
												torch.save(lowercase__				,  lowercase__						)





@contextmanager
def       lowercase_      (		**lowercase__						)   ->str:
						for key, value in kwargs.items():
												_snake_case:   List[str]  					=		str(lowercase__						)

						yield

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





def       lowercase_      (		lowercase__						)   ->Any:
						if not hasattr(lowercase__				,  '__qualname__'						) and not hasattr(lowercase__				,  '__name__'						):
												_snake_case:   Dict  					=		getattr(lowercase__				,  '__class__'				,  lowercase__						)
						if hasattr(lowercase__				,  '__qualname__'						):
												return obj.__qualname__
						if hasattr(lowercase__				,  '__name__'						):
												return obj.__name__
						return str(lowercase__						)





def       lowercase_      (		lowercase__				,  lowercase__						)   ->Dict:
						for key, value in source.items():
												if isinstance(lowercase__				,  lowercase__						):
																		_snake_case:   List[Any]  					=		destination.setdefault(lowercase__				,  {}						)
																		merge_dicts(lowercase__				,  lowercase__						)
												else:
																		_snake_case:   Dict  					=		value

						return destination





def       lowercase_      (		lowercase__ = None						)   ->bool:
						if port is None:
												_snake_case:   List[Any]  					=		2_9500
						with socket.socket(socket.AF_INET				,  socket.SOCK_STREAM						) as s:
												return s.connect_ex(('localhost', port)						) == 0












'''simple docstring'''






from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

A   : str             =			TypeVar('T')







class 			lowerCamelCase					(						Generic[T]  ):
					_SCREAMING_SNAKE_CASE							   =    42  # Cache store of keys
					_SCREAMING_SNAKE_CASE							   =    42  # References of the keys in cache
					_SCREAMING_SNAKE_CASE							   =    10  # Maximum capacity of cache


					def __init__(					self	:  List[Any]       ,     __snake_case	:  int       ):





											'''simple docstring'''





											_snake_case:   Dict  					=		deque()
											_snake_case:   Union[str, Any]  					=		set()
											if not n:
																	_snake_case:   Optional[int]  					=		sys.maxsize
											elif n < 0:
																	raise ValueError('n should be an integer greater than 0.'       )
											else:
																	_snake_case:   Tuple  					=		n


					def    SCREAMING_SNAKE_CASE_		(					self	:  Any       ,     __snake_case	:  T       ):





											'''simple docstring'''





											if x not in self.key_reference:
																	if len(self.dq_store       ) == LRUCache._MAX_CAPACITY:
																							_snake_case:   int  					=		self.dq_store.pop()
																							self.key_reference.remove(__snake_case       )
											else:
																	self.dq_store.remove(__snake_case       )

											self.dq_store.appendleft(__snake_case       )
											self.key_reference.add(__snake_case       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  int       ):





											'''simple docstring'''





											for k in self.dq_store:
																	print(__snake_case       )




					def __repr__(					self	:  List[Any]       ):





											'''simple docstring'''





											return f'''LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store       )}'''


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		A   : LRUCache[str | int]             =			LRUCache(4)
		lru_cache.refer('A')
		lru_cache.refer(2)
		lru_cache.refer(3)
		lru_cache.refer('A')
		lru_cache.refer(4)
		lru_cache.refer(5)
		lru_cache.display()

		print(lru_cache)
		assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"





