





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 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		if is_torch_version('<'							,'2.0.0'						) or not hasattr(lowerCAmelCase__							,'_dynamo'						):
				return False
		return isinstance(lowerCAmelCase__							,torch._dynamo.eval_frame.OptimizedModule						)


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__ = True						):
		lowerCamelCase_	:     List[str] 						=      (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

		lowerCamelCase_	:     Optional[Any] 						=      is_compiled_module(lowerCAmelCase__						)
		if is_compiled:
				lowerCamelCase_	:     Optional[int] 						=      model
				lowerCamelCase_	:     Dict 						=      model._orig_mod

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

		while isinstance(lowerCAmelCase__							,lowerCAmelCase__						):
				lowerCamelCase_	:     int 						=      model.module

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

		if is_compiled:
				lowerCamelCase_	:     List[str] 						=      model
				lowerCamelCase_	:     List[str] 						=      compiled_model

		return model


def 		_SCREAMING_SNAKE_CASE     ( ):
		PartialState().wait_for_everyone()


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__						):
		if PartialState().distributed_type == DistributedType.TPU:
				xm.save(lowerCAmelCase__							,lowerCAmelCase__						)
		elif PartialState().local_process_index == 0:
				torch.save(lowerCAmelCase__							,lowerCAmelCase__						)


@contextmanager
def 		_SCREAMING_SNAKE_CASE     ( **lowerCAmelCase__						):
		for key, value in kwargs.items():
				lowerCamelCase_	:     Union[str, Any] 						=      str(lowerCAmelCase__						)

		yield

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


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		if not hasattr(lowerCAmelCase__							,'__qualname__'						) and not hasattr(lowerCAmelCase__							,'__name__'						):
				lowerCamelCase_	:     Union[str, Any] 						=      getattr(lowerCAmelCase__							,'__class__'							,lowerCAmelCase__						)
		if hasattr(lowerCAmelCase__							,'__qualname__'						):
				return obj.__qualname__
		if hasattr(lowerCAmelCase__							,'__name__'						):
				return obj.__name__
		return str(lowerCAmelCase__						)


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__						):
		for key, value in source.items():
				if isinstance(lowerCAmelCase__							,lowerCAmelCase__						):
						lowerCamelCase_	:     Optional[int] 						=      destination.setdefault(lowerCAmelCase__							,{}						)
						merge_dicts(lowerCAmelCase__							,lowerCAmelCase__						)
				else:
						lowerCamelCase_	:     Optional[int] 						=      value

		return destination





def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__ = None						):
		if port is None:
				lowerCamelCase_	:     Tuple 						=      2_95_00
		with socket.socket(socket.AF_INET							,socket.SOCK_STREAM						) as s:
				return s.connect_ex(('localhost', port)						) == 0







_lowercase		:  Any			       =[0, 2, 4, 6, 8]
_lowercase		:  List[Any]			       =[1, 3, 5, 7, 9]


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__						):
		if remaining_length == 0:
				if digits[0] == 0 or digits[-1] == 0:
						return 0

				for i in range(length // 2 - 1							,-1							,-1						):
						remainder += digits[i] + digits[length - i - 1]

						if remainder % 2 == 0:
								return 0

						remainder //= 10

				return 1

		if remaining_length == 1:
				if remainder % 2 == 0:
						return 0

				lowerCamelCase_	:     Dict 						=      0
				for digit in range(10						):
						lowerCamelCase_	:     List[Any] 						=      digit
						result += reversible_numbers(
						    0							,(remainder + 2 * digit) // 10							,lowerCAmelCase__							,lowerCAmelCase__						)
				return result

		lowerCamelCase_	:     List[str] 						=      0
		for digita in range(10						):
				lowerCamelCase_	:     Tuple 						=      digita

				if (remainder + digita) % 2 == 0:
						lowerCamelCase_	:     Dict 						=      ODD_DIGITS
				else:
						lowerCamelCase_	:     str 						=      EVEN_DIGITS

				for digita in other_parity_digits:
						lowerCamelCase_	:     Optional[int] 						=      digita
						result += reversible_numbers(
						    remaining_length - 2							,(remainder + digita + digita) // 10							,lowerCAmelCase__							,lowerCAmelCase__							,)
		return result


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__ = 9						):
		lowerCamelCase_	:     int 						=      0
		for length in range(1							,max_power + 1						):
				result += reversible_numbers(lowerCAmelCase__							,0							,[0] * length							,lowerCAmelCase__						)
		return result


if __name__ == "__main__":
		print(F'''{solution() = }''')
