
"""simple docstring"""


def       _snake_case				(		snake_case__   :     float	,      snake_case__   :     float	,      snake_case__   :     float	,      snake_case__   :     float	,      snake_case__   :     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
		_lowercase							   =				0.3

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

"""simple docstring"""


from argparse import ArgumentParser

from . import BaseTransformersCLICommand






def       _snake_case				(		snake_case__   :     Optional[int]     ):
	return DownloadCommand(args.model	,      args.cache_dir	,      args.force	,      args.trust_remote_code     )







class 				lowerCAmelCase_				(      _lowercase    ):



						'''simple docstring'''


						@staticmethod
						def 						_SCREAMING_SNAKE_CASE      ( A_     :      ArgumentParser      )     ->   Any:
							A						   =   parser.add_parser('download'      )
							download_parser.add_argument(
							    '--cache-dir'  ,type=A_  ,default=A_  ,help='Path to location to store the models'      )
							download_parser.add_argument(
							    '--force'  ,action='store_true'  ,help='Force the model to be download even if already in cache-dir'      )
							download_parser.add_argument(
							    '--trust-remote-code'  ,action='store_true'  ,help='Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine'  ,)
							download_parser.add_argument('model'  ,type=A_  ,help='Name of the model to download'      )
							download_parser.set_defaults(func=A_      )


						def __init__( self     :      Dict  ,A_     :      str  ,A_     :      str  ,A_     :      bool  ,A_     :      bool      )     ->   Union[str, Any]:
							A						   =   model
							A						   =   cache
							A						   =   force
							A						   =   trust_remote_code




						def 						_SCREAMING_SNAKE_CASE      ( self     :      Dict      )     ->   Optional[int]:
							from ..models.auto import AutoModel, AutoTokenizer

							AutoModel.from_pretrained(
							    self._model  ,cache_dir=self._cache  ,force_download=self._force  ,trust_remote_code=self._trust_remote_code      )
							AutoTokenizer.from_pretrained(
							    self._model  ,cache_dir=self._cache  ,force_download=self._force  ,trust_remote_code=self._trust_remote_code      )