

from __future__ import annotations

from typing import Generic, TypeVar

_a:			List[str]       							=	TypeVar("""T""")

class   __UpperCamelCase			(    Generic[T]  ):




	def __init__(						self		:  Dict						,		lowerCAmelCase		:  Union[str, Any]							):


		'''simple docstring'''







		UpperCAmelCase_				 =	data  # Assign data
		UpperCAmelCase_				 =	None  # Initialize next as null
		UpperCAmelCase_				 =	None  # Initialize prev as null


class   __UpperCamelCase			(    Generic[T]  ):




	def __init__(						self		:  Any							):


		'''simple docstring'''







		UpperCAmelCase_				 =	None




	def 					__A    (						self		:  List[str]						,		lowerCAmelCase		:  List[str]							):


		'''simple docstring'''







		if self.head is None:
			UpperCAmelCase_				 =	Node(_A							)
		else:
			UpperCAmelCase_				 =	Node(_A							)
			UpperCAmelCase_				 =	new_node
			UpperCAmelCase_				 =	self.head
			UpperCAmelCase_				 =	None
			UpperCAmelCase_				 =	new_node




	def 					__A    (						self		:  Tuple							):


		'''simple docstring'''







		if self.head is None:
			return None
		else:
			assert self.head is not None
			UpperCAmelCase_				 =	self.head.data
			UpperCAmelCase_				 =	self.head.next
			if self.head is not None:
				UpperCAmelCase_				 =	None
			return temp




	def 					__A    (						self		:  Tuple							):


		'''simple docstring'''







		return self.head.data if self.head is not None else None




	def __len__(						self		:  str							):


		'''simple docstring'''







		UpperCAmelCase_				 =	self.head
		UpperCAmelCase_				 =	0
		while temp is not None:
			count += 1
			UpperCAmelCase_				 =	temp.next
		return count




	def 					__A    (						self		:  List[str]							):


		'''simple docstring'''







		return self.head is None




	def 					__A    (						self		:  Any							):


		'''simple docstring'''







		print("stack elements are:"							)
		UpperCAmelCase_				 =	self.head
		while temp is not None:
			print(temp.data						,		end="->"							)
			UpperCAmelCase_				 =	temp.next


# Code execution starts here
if __name__ == "__main__":
				# Start with the empty stack
				_a:			Stack[int]       							=	Stack()

				# Insert 4 at the beginning. So stack becomes 4->None
				print("""Stack operations using Doubly LinkedList""")
				stack.push(4)

				# Insert 5 at the beginning. So stack becomes 4->5->None
				stack.push(5)

				# Insert 6 at the beginning. So stack becomes 4->5->6->None
				stack.push(6)

				# Insert 7 at the beginning. So stack becomes 4->5->6->7->None
				stack.push(7)

				# Print the stack
				stack.print_stack()

				# Print the top element
				print("""\nTop element is """, stack.top())

				# Print the stack size
				print("""Size of the stack is """, len(stack))

				# pop the top element
				stack.pop()

				# pop the top element
				stack.pop()

				# two elements have now been popped off
				stack.print_stack()

				# Print True if the stack is empty else False
				print("""\nstack is empty:""", stack.is_empty())


from typing import TYPE_CHECKING

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


UpperCamelCase__     :					Dict								=			{
    "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__     :					Optional[int]								=			[
           "DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DonutSwinModel",
           "DonutSwinPreTrainedModel",
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__     :					List[Any]								=			["DonutFeatureExtractor"]
       UpperCamelCase__     :					Dict								=			["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__     :					Tuple								=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


