


'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCamelCase       				=	{
    '''configuration_codegen''': ['''CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CodeGenConfig''', '''CodeGenOnnxConfig'''],
    '''tokenization_codegen''': ['''CodeGenTokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       				=	['''CodeGenTokenizerFast''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       				=	[
        '''CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''CodeGenForCausalLM''',
        '''CodeGenModel''',
        '''CodeGenPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
    from .tokenization_codegen import CodeGenTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_codegen_fast import CodeGenTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_codegen import (
            CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
            CodeGenForCausalLM,
            CodeGenModel,
            CodeGenPreTrainedModel,
        )

else:
    import sys

    __lowerCamelCase       				=	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





'''simple docstring'''





from scipy.constants import g


def 					a__    (				UpperCamelCase_	:			float,      UpperCamelCase_	:			float	):
   if mass < 0:
      # handling of negative values of mass
      raise ValueError('''The mass of a body cannot be negative'''	)
   if height < 0:
      # handling of negative values of height
      raise ValueError('''The height above the ground cannot be negative'''	)
   return mass * g * height


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

    testmod(name='''potential_energy''')



