



from __future__ import annotations

from collections.abc import Iterator
from typing import Any



class 		_lowercase		:

   def __init__(   self      :							List[str]				, __lowerCAmelCase      :							Any				)							->					None:


    """simple docstring"""






    a							=		data
    a							=		None




   def __str__(   self      :							Union[str, Any]				)							->					str:


    """simple docstring"""






    return f"""{self.data}"""



class 		_lowercase		:

   def __init__(   self      :							Dict				)							->					None:


    """simple docstring"""






    a							=		None
    a							=		None

   def __iter__(   self      :							Dict				)							->					Iterator[Any]:


    """simple docstring"""






    a							=		self.front
    while node:
     yield node.data
     a							=		node.next

   def __len__(   self      :							Optional[Any]				)							->					int:


    """simple docstring"""






    return len(tuple(iter(self				)				)				)

   def __str__(   self      :							Union[str, Any]				)							->					str:


    """simple docstring"""






    return " <- ".join(str(__lowerCAmelCase				) for item in self				)

   def 		A				(   self      :							Optional[Any]				)							->					bool:


    """simple docstring"""






    return len(self				) == 0

   def 		A				(   self      :							List[str]				, __lowerCAmelCase      :							Any				)							->					None:


    """simple docstring"""






    a							=		Node(__lowerCAmelCase				)
    if self.is_empty():
     a							=		a							=		node
    else:
     assert isinstance(self.rear				, __lowerCAmelCase				)
     a							=		node
     a							=		node

   def 		A				(   self      :							Optional[Any]				)							->					Any:


    """simple docstring"""






    if self.is_empty():
     raise IndexError("dequeue from empty queue"				)
    assert isinstance(self.front				, __lowerCAmelCase				)
    a							=		self.front
    a							=		self.front.next
    if self.front is None:
     a							=		None
    return node.data




   def 		A				(   self      :							str				)							->					None:


    """simple docstring"""






    a							=		a							=		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


__UpperCAmelCase   						=     {
    "configuration_donut_swin": ["DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "DonutSwinConfig"],
    "processing_donut": ["DonutProcessor"],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase   						=     [
       "DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
       "DonutSwinModel",
       "DonutSwinPreTrainedModel",
   ]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase   						=     ["DonutFeatureExtractor"]
   __UpperCAmelCase   						=     ["DonutImageProcessor"]


if TYPE_CHECKING:
   from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
   from .processing_donut import DonutProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_donut_swin import (
          DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          DonutSwinModel,
          DonutSwinPreTrainedModel,
      )

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_donut import DonutFeatureExtractor
      from .image_processing_donut import DonutImageProcessor

else:
   import sys

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


