





from .hash_table import HashTable


class 			__lowerCAmelCase				(					_UpperCamelCase			):


	'''simple docstring'''





	def __init__(	self:	Optional[int],				*lowerCamelCase_:	str,				**lowerCamelCase_:	Dict ):
								super().__init__(*lowerCamelCase_,				**lowerCamelCase_ )





	def       snake_case__(	self:	Optional[Any],				lowerCamelCase_:	Tuple,				lowerCamelCase_:	Any=None ):
								lowercase__				:			Optional[Any]            =		1
								lowercase__				:			str            =		self.hash_function(key + i * i )

								while self.values[new_key] is not None and self.values[new_key] != key:
															i += 1
															lowercase__				:			Union[str, Any]            =		(
															    self.hash_function(key + i * i )
															    if not self.balanced_factor() >= self.lim_charge
															    else None
															)

															if new_key is None:
																						break

								return new_key









from typing import TYPE_CHECKING

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


__UpperCamelCase:  Any   =   {
    """configuration_deta""": ["""DETA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DetaConfig"""],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:  Tuple   =   ["""DetaImageProcessor"""]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:  List[str]   =   [
			    """DETA_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """DetaForObjectDetection""",
			    """DetaModel""",
			    """DetaPreTrainedModel""",
			]


if TYPE_CHECKING:
			from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .image_processing_deta import DetaImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_deta import (
						    DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
						    DetaForObjectDetection,
						    DetaModel,
						    DetaPreTrainedModel,
						)

else:
			import sys

			__UpperCamelCase:  int   =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


