from __future__ import annotations




def     UpperCamelCase						(	__lowercase						:			list[int]     ):
			'''simple docstring'''




			A_		:    Optional[int]         =				len(__lowerCamelCase     ) // 2

			# choose the middle 3 elements
			A_		:    str         =				lst[m - 1 : m + 2]

			# if middle element is peak
			if three[1] > three[0] and three[1] > three[2]:
						return three[1]

			# if increasing, recurse on right
			elif three[0] < three[2]:
						if len(lst[:m]     ) == 2:
									m -= 1
						return peak(lst[m:]     )

			# decreasing
			else:
						if len(lst[:m]     ) == 2:
									m += 1
						return peak(lst[:m]     )


if __name__ == "__main__":
	import doctest

	doctest.testmod()







from typing import TYPE_CHECKING

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


_UpperCAmelCase            =		{
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase            =		[
	    """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            =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






