'''simple docstring'''





from __future__ import annotations

from typing import Generic, TypeVar

UpperCamelCase       :     List[Any]			=    TypeVar("""T""")



class   UpperCamelCase					(       Generic[T]       ):







    """simple docstring"""





    def __init__(					self     :						List[Any]							,							UpperCAmelCase_     :						T):


         """simple docstring"""







         a					:							Any							= data  # Assign data
         a					:							Node[T] | None							= None  # Initialize next as null
         a					:							Node[T] | None							= None  # Initialize prev as null






class   UpperCamelCase					(       Generic[T]       ):







    """simple docstring"""





    def __init__(					self     :						int):


         """simple docstring"""







         a					:							Node[T] | None							= None





    def    SCREAMING_SNAKE_CASE_     (					self     :						Tuple							,							UpperCAmelCase_     :						T):


         """simple docstring"""







         if self.head is None:
              a					:							int							= Node(UpperCAmelCase_)
         else:
              a					:							Union[str, Any]							= Node(UpperCAmelCase_)
              a					:							List[Any]							= new_node
              a					:							Any							= self.head
              a					:							Tuple							= None
              a					:							int							= new_node





    def    SCREAMING_SNAKE_CASE_     (					self     :						Tuple):


         """simple docstring"""







         if self.head is None:
              return None
         else:
              assert self.head is not None
              a					:							Optional[Any]							= self.head.data
              a					:							Optional[Any]							= self.head.next
              if self.head is not None:
                   a					:							int							= None
              return temp





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


         """simple docstring"""







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





    def __len__(					self     :						Optional[Any]):


         """simple docstring"""







         a					:							Any							= self.head
         a					:							Tuple							= 0
         while temp is not None:
              count += 1
              a					:							str							= temp.next
         return count





    def    SCREAMING_SNAKE_CASE_     (					self     :						List[str]):


         """simple docstring"""







         return self.head is None







    def    SCREAMING_SNAKE_CASE_     (					self     :						Tuple):


         """simple docstring"""







         print('stack elements are:')
         a					:							Tuple							= self.head
         while temp is not None:
              print(temp.data							,							end='->')
              a					:							str							= temp.next


# Code execution starts here
if __name__ == "__main__":
      # Start with the empty stack
      UpperCamelCase       :     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())


'''simple docstring'''





from typing import TYPE_CHECKING

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


UpperCamelCase       :     Tuple			=    {
    """configuration_markuplm""": ["""MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarkupLMConfig"""],
    """feature_extraction_markuplm""": ["""MarkupLMFeatureExtractor"""],
    """processing_markuplm""": ["""MarkupLMProcessor"""],
    """tokenization_markuplm""": ["""MarkupLMTokenizer"""],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase       :     int			=    ["""MarkupLMTokenizerFast"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase       :     Any			=    [
          """MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """MarkupLMForQuestionAnswering""",
          """MarkupLMForSequenceClassification""",
          """MarkupLMForTokenClassification""",
          """MarkupLMModel""",
          """MarkupLMPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
      from .feature_extraction_markuplm import MarkupLMFeatureExtractor
      from .processing_markuplm import MarkupLMProcessor
      from .tokenization_markuplm import MarkupLMTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_markuplm_fast import MarkupLMTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_markuplm import (
                MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
                MarkupLMForQuestionAnswering,
                MarkupLMForSequenceClassification,
                MarkupLMForTokenClassification,
                MarkupLMModel,
                MarkupLMPreTrainedModel,
            )


else:
      import sys

      UpperCamelCase       :     Dict			=    _LazyModule(__name__, globals()["""__file__"""], _import_structure)

