
from __future__ import annotations

from random import choice






def   lowerCamelCase__							(							__lowerCAmelCase    :    str							):




			"""simple docstring"""


			return choice(__lowerCAmelCase							)






def   lowerCamelCase__							(							__lowerCAmelCase    :    list[int]       ,				__lowerCAmelCase    :    int							):




			"""simple docstring"""


			lowerCAmelCase_         =      random_pivot(__lowerCAmelCase							)

			# partition based on pivot
			# linear time
			lowerCAmelCase_         =      [e for e in lst if e < pivot]
			lowerCAmelCase_         =      [e for e in lst if e > pivot]

			# if we get lucky, pivot might be the element we want.
			# we can easily see this:
			# small (elements smaller than k)
			# + pivot (kth element)
			# + big (elements larger than k)
			if len(__lowerCAmelCase							) == k - 1:
						return pivot
			# pivot is in elements bigger than k
			elif len(__lowerCAmelCase							) < k - 1:
						return kth_number(__lowerCAmelCase       ,				k - len(__lowerCAmelCase							) - 1							)
			# pivot is in elements smaller than k
			else:
						return kth_number(__lowerCAmelCase       ,				__lowerCAmelCase							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A  =	{"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A  =	[
			    "SEW_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "SEWForCTC",
			    "SEWForSequenceClassification",
			    "SEWModel",
			    "SEWPreTrainedModel",
			]

if TYPE_CHECKING:
			from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_sew import (
						    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SEWForCTC,
						    SEWForSequenceClassification,
						    SEWModel,
						    SEWPreTrainedModel,
						)


else:
			import sys

			_A  =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



