from __future__ import annotations

from typing import Any







class __snake_case       (		snake_case__	):
   pass







class __snake_case       :




   def __init__(					self    :       str ,			_lowercase    :       Any   ):



         """simple docstring"""






         SCREAMING_SNAKE_CASE__    							=   data
         SCREAMING_SNAKE_CASE__    							=   None




   def __iter__(					self    :       Union[str, Any]   ):



         """simple docstring"""






         SCREAMING_SNAKE_CASE__    							=   self
         SCREAMING_SNAKE_CASE__    							=   []
         while node:
               if node in visited:
                     raise ContainsLoopError
               visited.append(UpperCAmelCase_   )
               yield node.data
               SCREAMING_SNAKE_CASE__    							=   node.next_node




   @property
   def 			__a		(					self    :       str   ):



         """simple docstring"""






         try:
               list(self   )
               return False
         except ContainsLoopError:
               return True


if __name__ == "__main__":
   __lowerCamelCase    :				Dict							     =	Node(1)
   __lowerCamelCase    :				Tuple							     =	Node(2)
   __lowerCamelCase    :				Optional[int]							     =	Node(3)
   __lowerCamelCase    :				str							     =	Node(4)
   print(root_node.has_loop)  # False
   __lowerCamelCase    :				List[Any]							     =	root_node.next_node
   print(root_node.has_loop)  # True

   __lowerCamelCase    :				Dict							     =	Node(5)
   __lowerCamelCase    :				Optional[int]							     =	Node(6)
   __lowerCamelCase    :				List[Any]							     =	Node(5)
   __lowerCamelCase    :				Optional[int]							     =	Node(6)
   print(root_node.has_loop)  # False

   __lowerCamelCase    :				Dict							     =	Node(1)
   print(root_node.has_loop)  # False

from typing import TYPE_CHECKING

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


__lowerCamelCase    :				List[Any]							     =	{
    '''configuration_informer''': [
        '''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InformerConfig''',
    ],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase    :				Union[str, Any]							     =	[
       '''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

   __lowerCamelCase    :				Dict							     =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
