






'''simple docstring'''





from functools import lru_cache
@lru_cache
def __UpperCAmelCase (			A			:	int						)  -> int:
			if not isinstance(A	,   A						):
						raise TypeError('''k must be an integer.'''						)
			if k < 0:
						raise ValueError('''k integer must be greater or equal to zero.'''						)
			if k == 0:
						return 0
			elif k == 1:
						return 1
			else:
						return fibonacci(k - 1						) + fibonacci(k - 2						)
def __UpperCAmelCase (			A			:	list	,   A			:	int						)  -> int:
			UpperCAmelCase_     :   Any       =   len(A						)
			# Find m such that F_m >= n where F_i is the i_th fibonacci number.
			UpperCAmelCase_     :   Any       =   0
			while True:
						if fibonacci(A						) >= len_list:
									UpperCAmelCase_     :   Tuple       =   i
									break
						i += 1
			UpperCAmelCase_     :   List[str]       =   0
			while fibb_k > 0:
						UpperCAmelCase_     :   Any       =   min(
						    offset + fibonacci(fibb_k - 1						)	,   len_list - 1						)  # Prevent out of range
						UpperCAmelCase_     :   Optional[Any]       =   arr[index_k]
						if item_k_1 == val:
									return index_k
						elif val < item_k_1:
									fibb_k -= 1
						elif val > item_k_1:
									offset += fibonacci(fibb_k - 1						)
									fibb_k -= 2
			else:
						return -1


if __name__ == "__main__":
						import doctest

						doctest.testmod()










'''simple docstring'''





from typing import TYPE_CHECKING

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


_UpperCamelCase		:		Optional[Any]								=			{'configuration_vit_hybrid': ['VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTHybridConfig']}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCamelCase		:		Optional[int]								=			[
						    'VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'ViTHybridForImageClassification',
						    'ViTHybridModel',
						    'ViTHybridPreTrainedModel',
						]

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCamelCase		:		str								=			['ViTHybridImageProcessor']


if TYPE_CHECKING:
						from .configuration_vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_vit_hybrid import (
												    VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ViTHybridForImageClassification,
												    ViTHybridModel,
												    ViTHybridPreTrainedModel,
												)

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_vit_hybrid import ViTHybridImageProcessor


else:
						import sys

						_UpperCamelCase		:		Tuple								=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


