






from typing import TYPE_CHECKING

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


__snake_case     :     Optional[int]       =  {"""configuration_vilt""": ["""VILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViltConfig"""]}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case     :     int       =  ["""ViltFeatureExtractor"""]
					__snake_case     :     Tuple       =  ["""ViltImageProcessor"""]
					__snake_case     :     List[str]       =  ["""ViltProcessor"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case     :     List[Any]       =  [
					    """VILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """ViltForImageAndTextRetrieval""",
					    """ViltForImagesAndTextClassification""",
					    """ViltForTokenClassification""",
					    """ViltForMaskedLM""",
					    """ViltForQuestionAnswering""",
					    """ViltLayer""",
					    """ViltModel""",
					    """ViltPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_vilt import ViltFeatureExtractor
										from .image_processing_vilt import ViltImageProcessor
										from .processing_vilt import ViltProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_vilt import (
										    VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ViltForImageAndTextRetrieval,
										    ViltForImagesAndTextClassification,
										    ViltForMaskedLM,
										    ViltForQuestionAnswering,
										    ViltForTokenClassification,
										    ViltLayer,
										    ViltModel,
										    ViltPreTrainedModel,
										)


else:
					import sys

					__snake_case     :     Union[str, Any]       =  _LazyModule(__name__, globals()["""__file__"""], _import_structure)






from .number_theory.prime_numbers import next_prime




class  __lowerCAmelCase	:



 '''simple docstring'''

 def __init__(      self							:		List[Any]							,      lowerCamelCase							:		int							,      lowerCamelCase							:		int | None = None							,      lowerCamelCase							:		float | None = None							,      )			->				None:
        _UpperCamelCase  :							Tuple	    =	size_table
        _UpperCamelCase  :							Tuple	    =	[None] * self.size_table
        _UpperCamelCase  :							int	    =	0.7_5 if lim_charge is None else lim_charge
        _UpperCamelCase  :							Tuple	    =	1 if charge_factor is None else charge_factor
        _UpperCamelCase  :							list	    =	[]
        _UpperCamelCase  :							dict	    =	{}

 def        __snake_case       (      self							:		List[Any]	)			->				Union[str, Any]:
        return self._keys

 def        __snake_case       (      self							:		List[Any]	)			->				Optional[int]:
        return sum(1 for slot in self.values if slot is not None	) / (
            self.size_table * self.charge_factor
        )

 def        __snake_case       (      self							:		Union[str, Any]							,      lowerCamelCase							:		int	)			->				Any:
        return key % self.size_table

 def        __snake_case       (      self							:		Any							,      lowerCamelCase							:		Any	)			->				Optional[Any]:
        print(f"step {step_ord}"	)
        print(list(range(len(self.values	)	)	)	)
        print(self.values	)

 def        __snake_case       (      self							:		Tuple							,      lowerCamelCase							:		Optional[int]	)			->				Any:
        _UpperCamelCase  :							int	    =	1
        _UpperCamelCase  :							Union[str, Any]	    =	values
        for value in values:
               self.insert_data(lowerCamelCase	)
               self._step_by_step(lowerCamelCase	)
               i += 1

 def        __snake_case       (      self							:		Optional[Any]							,      lowerCamelCase							:		Any							,      lowerCamelCase							:		Optional[int]	)			->				Any:
        _UpperCamelCase  :							int	    =	data
        _UpperCamelCase  :							Optional[int]	    =	data

 def        __snake_case       (      self							:		Optional[int]							,      lowerCamelCase							:		Optional[int]							,      lowerCamelCase							:		str=None	)			->				List[Any]:
        _UpperCamelCase  :							Union[str, Any]	    =	self.hash_function(key + 1	)

        while self.values[new_key] is not None and self.values[new_key] != key:
               if self.values.count(lowerCamelCase	) > 0:
                      _UpperCamelCase  :							Optional[int]	    =	self.hash_function(new_key + 1	)
               else:
                      _UpperCamelCase  :							Tuple	    =	None
                      break

        return new_key

 def        __snake_case       (      self							:		Optional[Any]	)			->				Optional[Any]:
        _UpperCamelCase  :							Union[str, Any]	    =	[value for value in self.values if value is not None]
        _UpperCamelCase  :							Union[str, Any]	    =	next_prime(self.size_table							,      factor=2	)
        self._keys.clear()
        _UpperCamelCase  :							Tuple	    =	[None] * self.size_table  # hell's pointers D: don't DRY ;/
        for value in survivor_values:
               self.insert_data(lowerCamelCase	)

 def        __snake_case       (      self							:		Tuple							,      lowerCamelCase							:		str	)			->				Union[str, Any]:
        _UpperCamelCase  :							Dict	    =	self.hash_function(lowerCamelCase	)

        if self.values[key] is None:
               self._set_value(lowerCamelCase							,      lowerCamelCase	)

        elif self.values[key] == data:
               pass

        else:
               _UpperCamelCase  :							Tuple	    =	self._collision_resolution(lowerCamelCase							,      lowerCamelCase	)
               if collision_resolution is not None:
                      self._set_value(lowerCamelCase							,      lowerCamelCase	)
               else:
                      self.rehashing()
                      self.insert_data(lowerCamelCase	)



