

from typing import TYPE_CHECKING

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


_UpperCAmelCase		:   Optional[Any]										=       {
    """configuration_trajectory_transformer""": [
        """TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """TrajectoryTransformerConfig""",
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:   Tuple										=       [
					    """TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TrajectoryTransformerModel""",
					    """TrajectoryTransformerPreTrainedModel""",
					    """load_tf_weights_in_trajectory_transformer""",
					]


if TYPE_CHECKING:
					from .configuration_trajectory_transformer import (
					    TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    TrajectoryTransformerConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_trajectory_transformer import (
										    TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TrajectoryTransformerModel,
										    TrajectoryTransformerPreTrainedModel,
										    load_tf_weights_in_trajectory_transformer,
										)


else:
					import sys

					_UpperCAmelCase		:   Optional[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()


