
from .hash_table import HashTable
from .number_theory.prime_numbers import is_prime, next_prime


class 							lowercase   (						SCREAMING_SNAKE_CASE_  ):



		def __init__(					self							, *A_							, **A_			)    ->   Optional[Any]:
				"""simple docstring"""
				super().__init__(*SCREAMING_SNAKE_CASE_							, **SCREAMING_SNAKE_CASE_			)



		def __UpperCamelCase					(					self							, A_							, A_			)    ->   str:
				"""simple docstring"""
				UpperCamelCase            =	(
				    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 __UpperCamelCase					(					self							, A_							, A_							, A_			)    ->   int:
				"""simple docstring"""
				return (increment * self.__hash_function_a(SCREAMING_SNAKE_CASE_							, SCREAMING_SNAKE_CASE_			)) % self.size_table



		def __UpperCamelCase					(					self							, A_							, A_=None			)    ->   Union[str, Any]:
				"""simple docstring"""
				UpperCamelCase            =	1
				UpperCamelCase            =	self.hash_function(SCREAMING_SNAKE_CASE_			)

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

				return new_key


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase__				:				Dict						=      {
    "configuration_switch_transformers": [
        "SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwitchTransformersConfig",
        "SwitchTransformersOnnxConfig",
    ]
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__				:				List[Any]						=      [
				    "SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "SwitchTransformersEncoderModel",
				    "SwitchTransformersForConditionalGeneration",
				    "SwitchTransformersModel",
				    "SwitchTransformersPreTrainedModel",
				    "SwitchTransformersTop1Router",
				    "SwitchTransformersSparseMLP",
				]


if TYPE_CHECKING:
				from .configuration_switch_transformers import (
				    SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    SwitchTransformersConfig,
				    SwitchTransformersOnnxConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_switch_transformers import (
								    SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SwitchTransformersEncoderModel,
								    SwitchTransformersForConditionalGeneration,
								    SwitchTransformersModel,
								    SwitchTransformersPreTrainedModel,
								    SwitchTransformersSparseMLP,
								    SwitchTransformersTopaRouter,
								)


else:
				import sys

				lowercase__				:				List[Any]						=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




