code: 
  
  
  
  
  
  
  """simple docstring"""
  
  from .hash_table import HashTable
  from .number_theory.prime_numbers import is_prime, next_prime
  
  
  class 	__lowerCamelCase       (				A__    ):
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  		def __init__(     self							:			List[str]		,    *a_							:			List[str]		,    **a_							:			Dict			):
  				super().__init__(*a_		,    **a_			)
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Tuple		,    a_							:			str		,    a_							:			List[str]			):
  				lowerCAmelCase_     :							List[Any]             =    (
  				    next_prime(value % self.size_table			)
  				    if not is_prime(value % self.size_table			)
  				    else value % self.size_table
  				)  # gt = bigger than
  				return next_prime_gt - (data % next_prime_gt)
  
  
  
  
  
  		def      lowerCamelCase (     self							:			int		,    a_							:			Union[str, Any]		,    a_							:			Dict		,    a_							:			int			):
  				return (increment * self.__hash_function_a(a_		,    a_			)) % self.size_table
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Optional[Any]		,    a_							:			Any		,    a_							:			List[str]=None			):
  				lowerCAmelCase_     :							Union[str, Any]             =    1
  				lowerCAmelCase_     :							Tuple             =    self.hash_function(a_			)
  
  				while self.values[new_key] is not None and self.values[new_key] != key:
  						lowerCAmelCase_     :							List[Any]             =    (
  						    self.__hash_double_function(a_		,    a_		,    a_			)
  						    if self.balanced_factor() >= self.lim_charge
  						    else None
  						)
  						if new_key is None:
  								break
  						else:
  								i += 1
  
  				return new_key
  
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
      is_vision_available,
  )
  
  
  lowercase__      =				{
      """configuration_mobilevitv2""": [
          """MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
          """MobileViTV2Config""",
          """MobileViTV2OnnxConfig""",
      ],
  }
  
  
  try:
  					if not is_torch_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					lowercase__      =				[
  					    """MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
  					    """MobileViTV2ForImageClassification""",
  					    """MobileViTV2ForSemanticSegmentation""",
  					    """MobileViTV2Model""",
  					    """MobileViTV2PreTrainedModel""",
  					]
  
  if TYPE_CHECKING:
  					from .configuration_mobilevitva import (
  					    MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
  					    MobileViTVaConfig,
  					    MobileViTVaOnnxConfig,
  					)
  
  					try:
  										if not is_torch_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .modeling_mobilevitva import (
  										    MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
  										    MobileViTVaForImageClassification,
  										    MobileViTVaForSemanticSegmentation,
  										    MobileViTVaModel,
  										    MobileViTVaPreTrainedModel,
  										)
  
  else:
  					import sys
  
  					lowercase__      =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  