





'''simple docstring'''

import math

def     __magic_name__							(				__UpperCAmelCase   )    ->       bool:

   '''simple docstring'''







   assert isinstance(__UpperCAmelCase				,						__UpperCAmelCase   ) and (
       number >= 0
   ), "'number' must been an int and positive"

   if 1 < number < 4:
      # 2 and 3 are primes
      return True
   elif number < 2 or not number % 2:
      # Negatives, 0, 1 and all even numbers are not primes
      return False

   __SCREAMING_SNAKE_CASE   				=							range(3				,						int(math.sqrt(__UpperCAmelCase   ) + 1   )				,						2   )
   return not any(not number % i for i in odd_numbers   )







def     __magic_name__							(				__UpperCAmelCase				,						__UpperCAmelCase=1				,						**__UpperCAmelCase   )    ->       str:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							factor * value
   __SCREAMING_SNAKE_CASE   				=							value

   while not is_prime(__UpperCAmelCase   ):
      value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

   if value == first_value_val:
      return next_prime(value + 1				,						**__UpperCAmelCase   )
   return value












'''simple docstring'''

from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a   	=    {
    "configuration_informer": [
        "INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InformerConfig",
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    a   	=    [
        "INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "InformerForPrediction",
        "InformerModel",
        "InformerPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_informer import (
            INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            InformerForPrediction,
            InformerModel,
            InformerPreTrainedModel,
        )

else:
    import sys

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





