




from __future__ import annotations

from collections.abc import Iterator
from typing import Any




class 		UpperCamelCase__     :

    '''simple docstring'''



    def __init__(   self					,  UpperCamelCase__					)					->				None:
           lowerCamelCase       :				Any      			= data
           lowerCamelCase       :				Node | None      			= None







    def __str__(   self					)					->				str:
           return F'''{self.data}'''




class 		UpperCamelCase__     :

    '''simple docstring'''



    def __init__(   self					)					->				None:
           lowerCamelCase       :				Node | None      			= None
           lowerCamelCase       :				Node | None      			= None







    def __iter__(   self					)					->				Iterator[Any]:
           lowerCamelCase       :				str      			= self.front
           while node:
                  yield node.data
                  lowerCamelCase       :				List[Any]      			= node.next







    def __len__(   self					)					->				int:
           return len(tuple(iter(self					)					)					)







    def __str__(   self					)					->				str:
           return " <- ".join(str(UpperCamelCase__					) for item in self					)







    def    _lowercase					(   self					)					->				bool:
           return len(self					) == 0







    def    _lowercase					(   self					,  UpperCamelCase__					)					->				None:
           lowerCamelCase       :				Optional[int]      			= Node(UpperCamelCase__					)
           if self.is_empty():
                  lowerCamelCase       :				Any      			= node
           else:
                  assert isinstance(self.rear					,  UpperCamelCase__					)
                  lowerCamelCase       :				Any      			= node
                  lowerCamelCase       :				Optional[Any]      			= node







    def    _lowercase					(   self					)					->				Any:
           if self.is_empty():
                  raise IndexError("dequeue from empty queue"					)
           assert isinstance(self.front					,  UpperCamelCase__					)
           lowerCamelCase       :				List[str]      			= self.front
           lowerCamelCase       :				Optional[Any]      			= self.front.next
           if self.front is None:
                  lowerCamelCase       :				Any      			= None
           return node.data







    def    _lowercase					(   self					)					->				None:
           lowerCamelCase       :				Optional[Any]      			= None


if __name__ == "__main__":
     from doctest import testmod

     testmod()












from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__	:				Dict  =       {
    'configuration_oneformer': ['ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OneFormerConfig'],
    'processing_oneformer': ['OneFormerProcessor'],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__	:				Optional[Any]  =       ['OneFormerImageProcessor']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__	:				Optional[int]  =       [
           'ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
           'OneFormerForUniversalSegmentation',
           'OneFormerModel',
           'OneFormerPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig
       from .processing_oneformer import OneFormerProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_oneformer import OneFormerImageProcessor
       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_oneformer import (
                  ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  OneFormerForUniversalSegmentation,
                  OneFormerModel,
                  OneFormerPreTrainedModel,
              )


else:
       import sys

       SCREAMING_SNAKE_CASE__	:				str  =       _LazyModule(__name__, globals()['__file__'], _import_structure)






