

'''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 					__UpperCamelCase				(						lowercase__    :	Any			):






     '''simple docstring'''





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

def 					__UpperCamelCase				(						lowercase__    :	int,       lowercase__    :	bool = True			):






     '''simple docstring'''





     __lowercase      		=(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

     __lowercase      		=is_compiled_module(lowercase__			)
     if is_compiled:
          __lowercase      		=model
          __lowercase      		=model._orig_mod

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

     while isinstance(lowercase__,       lowercase__			):
          __lowercase      		=model.module

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

     if is_compiled:
          __lowercase      		=model
          __lowercase      		=compiled_model

     return model

def 					__UpperCamelCase				(						):






     '''simple docstring'''





     PartialState().wait_for_everyone()

def 					__UpperCamelCase				(						lowercase__    :	Any,       lowercase__    :	Optional[Any]			):






     '''simple docstring'''





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

@contextmanager
def 					__UpperCamelCase				(						**lowercase__    :	int			):






     '''simple docstring'''





     for key, value in kwargs.items():
          __lowercase      		=str(lowercase__			)

     yield

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

def 					__UpperCamelCase				(						lowercase__    :	List[Any]			):






     '''simple docstring'''





     if not hasattr(lowercase__,       '__qualname__'			) and not hasattr(lowercase__,       '__name__'			):
          __lowercase      		=getattr(lowercase__,       '__class__',       lowercase__			)
     if hasattr(lowercase__,       '__qualname__'			):
          return obj.__qualname__
     if hasattr(lowercase__,       '__name__'			):
          return obj.__name__
     return str(lowercase__			)

def 					__UpperCamelCase				(						lowercase__    :	Union[str, Any],       lowercase__    :	int			):






     '''simple docstring'''





     for key, value in source.items():
          if isinstance(lowercase__,       lowercase__			):
               __lowercase      		=destination.setdefault(lowercase__,       {}			)
               merge_dicts(lowercase__,       lowercase__			)
          else:
               __lowercase      		=value

     return destination







def 					__UpperCamelCase				(						lowercase__    :	int = None			):






     '''simple docstring'''





     if port is None:
          __lowercase      		=2_95_00
     with socket.socket(socket.AF_INET,       socket.SOCK_STREAM			) as s:
          return s.connect_ex(('localhost', port)			) == 0




"""simple docstring"""




def     __magic_name__		(					UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		)     ->						float:
    a__		=			[redshift, radiation_density, matter_density, dark_energy]
    if any(p < 0 for p in parameters     ):
        raise ValueError('All input parameters must be positive'     )

    if any(p > 1 for p in parameters[1:4]     ):
        raise ValueError('Relative densities cannot be greater than one'     )
    else:
        a__		=			1 - (matter_density + radiation_density + dark_energy)

        a__		=			(
            radiation_density * (redshift + 1) ** 4
            + matter_density * (redshift + 1) ** 3
            + curvature * (redshift + 1) ** 2
            + dark_energy
        )

        a__		=			hubble_constant * e_a ** (1 / 2)
        return hubble


if __name__ == "__main__":
    import doctest

    # run doctest
    doctest.testmod()

    # demo LCDM approximation
    a		:       Any     						=       0.3

    print(
        hubble_parameter(
            hubble_constant=68.3,
            radiation_density=1e-4,
            matter_density=matter_density,
            dark_energy=1 - matter_density,
            redshift=0,
        )
    )


