



from .hash_table import HashTable
from .number_theory.prime_numbers import is_prime, next_prime
class     lowerCamelCase  (      _lowerCAmelCase    ):






					'''simple docstring'''





					def __init__(	self:							str						,					*snake_case:							Any						,					**snake_case:							List[Any]						)       ->     str:
											super().__init__(*snake_case						,					**snake_case						)






					def        lowerCAmelCase_    (	self:							Optional[Any]						,					snake_case:							str						,					snake_case:							Optional[int]						)       ->     Union[str, Any]:
											snake_case_			: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:							Union[str, Any]						,					snake_case:							Tuple						,					snake_case:							Optional[Any]						,					snake_case:							Dict						)       ->     Dict:
											return (increment * self.__hash_function_a(snake_case						,					snake_case						)) % self.size_table






					def        lowerCAmelCase_    (	self:							List[Any]						,					snake_case:							Any						,					snake_case:							List[Any]=None						)       ->     List[str]:
											snake_case_			:List[str]						=      1
											snake_case_			:Optional[int]						=      self.hash_function(snake_case						)

											while self.values[new_key] is not None and self.values[new_key] != key:
																	snake_case_			:List[Any]						=      (
																	    self.__hash_double_function(snake_case						,					snake_case						,					snake_case						)
																	    if self.balanced_factor() >= self.lim_charge
																	    else None
																	)
																	if new_key is None:
																							break
																	else:
																							i += 1

											return new_key





"""simple docstring"""
from typing import TYPE_CHECKING

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


__a     =    {
    "configuration_xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a     =    ["XLMProphetNetTokenizer"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a     =    [
						    "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "XLMProphetNetDecoder",
						    "XLMProphetNetEncoder",
						    "XLMProphetNetForCausalLM",
						    "XLMProphetNetForConditionalGeneration",
						    "XLMProphetNetModel",
						    "XLMProphetNetPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_xlm_prophetnet import (
												    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    XLMProphetNetDecoder,
												    XLMProphetNetEncoder,
												    XLMProphetNetForCausalLM,
												    XLMProphetNetForConditionalGeneration,
												    XLMProphetNetModel,
												    XLMProphetNetPreTrainedModel,
												)

else:
						import sys

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