
"""simple docstring"""

UpperCamelCase			:       Optional[int]									=				8.31_44_62  # Unit - J mol-1 K-1






def 							A		(       snake_case   :float       ,      snake_case   :float       ,      snake_case   :float	)   ->			float:
 if moles < 0 or kelvin < 0 or volume < 0:
  raise ValueError('Invalid inputs. Enter positive value.'	)
 return moles * kelvin * UNIVERSAL_GAS_CONSTANT / volume






def 							A		(       snake_case   :float       ,      snake_case   :float       ,      snake_case   :float	)   ->			float:
 if moles < 0 or kelvin < 0 or pressure < 0:
  raise ValueError('Invalid inputs. Enter positive value.'	)
 return moles * kelvin * UNIVERSAL_GAS_CONSTANT / pressure


if __name__ == "__main__":
      from doctest import testmod

      testmod()





"""simple docstring"""

from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase			:       List[str]									=				{
    "configuration_autoformer": [
        "AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "AutoformerConfig",
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase			:       Dict									=				[
          "AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "AutoformerForPrediction",
          "AutoformerModel",
          "AutoformerPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_autoformer import (
          AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          AutoformerConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_autoformer import (
                AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                AutoformerForPrediction,
                AutoformerModel,
                AutoformerPreTrainedModel,
            )

else:
      import sys

      UpperCamelCase			:       int									=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



