

from typing import TYPE_CHECKING

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


_UpperCAmelCase		:   Any										=       {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:   List[Any]										=       [
					    """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """FocalNetForImageClassification""",
					    """FocalNetForMaskedImageModeling""",
					    """FocalNetBackbone""",
					    """FocalNetModel""",
					    """FocalNetPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_focalnet import (
										    FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    FocalNetBackbone,
										    FocalNetForImageClassification,
										    FocalNetForMaskedImageModeling,
										    FocalNetModel,
										    FocalNetPreTrainedModel,
										)

else:
					import sys

					_UpperCAmelCase		:   Any										=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







"""simple docstring"""


from numpy import exp, pi, sqrt






def     a__    (    __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE = 0.0					, __SCREAMING_SNAKE_CASE = 1.0 )	->	int:
		return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )


if __name__ == "__main__":
			import doctest

			doctest.testmod()


