






'''simple docstring'''
from __future__ import annotations

from typing import Any


class        _UpperCAmelCase						(		snake_case			):
    pass


class        _UpperCAmelCase						:




    def __init__(			self  :       int  ,     a  :       Any			):






       '''simple docstring'''






       lowercase_	:    Any           =     data
       lowercase_	:    Node | None           =     None




    def __iter__(			self  :       Any			):






       '''simple docstring'''






       lowercase_	:    Tuple           =     self
       lowercase_	:    List[Any]           =     []
       while node:
          if node in visited:
             raise ContainsLoopError
          visited.append(a			)
          yield node.data
          lowercase_	:    str           =     node.next_node





    @property
    def 				lowerCAmelCase__				(			self  :       Tuple			):






       '''simple docstring'''






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


if __name__ == "__main__":
 UpperCamelCase__ =			Node(1)
 UpperCamelCase__ =			Node(2)
 UpperCamelCase__ =			Node(3)
 UpperCamelCase__ =			Node(4)
 print(root_node.has_loop)  # False
 UpperCamelCase__ =			root_node.next_node
 print(root_node.has_loop)  # True

 UpperCamelCase__ =			Node(5)
 UpperCamelCase__ =			Node(6)
 UpperCamelCase__ =			Node(5)
 UpperCamelCase__ =			Node(6)
 print(root_node.has_loop)  # False

 UpperCamelCase__ =			Node(1)
 print(root_node.has_loop)  # False












'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCamelCase__ =			{
    'configuration_encodec': [
        'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EncodecConfig',
    ],
    'feature_extraction_encodec': ['EncodecFeatureExtractor'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__ =			[
     'ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST',
     'EncodecModel',
     'EncodecPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_encodec import (
     ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
     EncodecConfig,
 )
 from .feature_extraction_encodec import EncodecFeatureExtractor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_encodec import (
      ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
      EncodecModel,
      EncodecPreTrainedModel,
  )

else:
 import sys

 UpperCamelCase__ =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




