

def 			A_      (    _UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase				,	):
						SCREAMING_SNAKE_CASE_: Optional[int]  		=       [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:
												SCREAMING_SNAKE_CASE_: int  		=       1 - (matter_density + radiation_density + dark_energy)

												SCREAMING_SNAKE_CASE_: Dict  		=       (
												    radiation_density * (redshift + 1) ** 4
												    + matter_density * (redshift + 1) ** 3
												    + curvature * (redshift + 1) ** 2
												    + dark_energy
												)

												SCREAMING_SNAKE_CASE_: Any  		=       hubble_constant * e_a ** (1 / 2)
												return hubble


if __name__ == "__main__":
						import doctest

						# run doctest
						doctest.testmod()

						# demo LCDM approximation
						lowerCAmelCase							:  List[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,
						    )
						)









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
						from ..ta.tokenization_ta import TaTokenizer
else:
						from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCAmelCase							:  Any   	=						TaTokenizer

if is_tokenizers_available():
						from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
						from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCAmelCase							:  Dict   	=						TaTokenizerFast

lowerCAmelCase							:  Optional[int]   	=						{"""configuration_mt5""": ["""MT5Config""", """MT5OnnxConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  int   	=						[
						    """MT5EncoderModel""",
						    """MT5ForConditionalGeneration""",
						    """MT5ForQuestionAnswering""",
						    """MT5Model""",
						    """MT5PreTrainedModel""",
						    """MT5Stack""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Tuple   	=						["""TFMT5EncoderModel""", """TFMT5ForConditionalGeneration""", """TFMT5Model"""]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  List[str]   	=						["""FlaxMT5EncoderModel""", """FlaxMT5ForConditionalGeneration""", """FlaxMT5Model"""]


if TYPE_CHECKING:
						from .configuration_mta import MTaConfig, MTaOnnxConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mta import (
												    MTaEncoderModel,
												    MTaForConditionalGeneration,
												    MTaForQuestionAnswering,
												    MTaModel,
												    MTaPreTrainedModel,
												    MTaStack,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
						import sys

						lowerCAmelCase							:  Optional[Any]   	=						_LazyModule(
						    __name__,
						    globals()["""__file__"""],
						    _import_structure,
						    extra_objects={"""MT5Tokenizer""": MTaTokenizer, """MT5TokenizerFast""": MTaTokenizerFast},
						    module_spec=__spec__,
						)






