



from __future__ import annotations

from typing import Generic, TypeVar

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



class       _lowercase				(  Generic[T]      ):





	"""simple docstring"""




	def __init__(self						,			lowerCamelCase_						):
						"""simple docstring"""

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




class       _lowercase				(  Generic[T]      ):





	"""simple docstring"""




	def __init__(self						):
						"""simple docstring"""

						a   	=  None




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						):
						"""simple docstring"""

						if self.head is None:
											a   	=  Node(lowerCAmelCase_						)
						else:
											a   	=  Node(lowerCAmelCase_						)
											a   	=  new_node
											a   	=  self.head
											a   	=  None
											a   	=  new_node




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

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




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

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




	def __len__(self						):
						"""simple docstring"""

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




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						return self.head is None




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

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


# Code execution starts here
if __name__ == "__main__":
				# Start with the empty stack
				_lowercase:					List[str]      =						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_flax_available,
    is_tf_available,
    is_torch_available,
)


UpperCAmelCase				 =   {
    """configuration_gptsan_japanese""": ["""GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTSanJapaneseConfig"""],
    """tokenization_gptsan_japanese""": ["""GPTSanJapaneseTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase				 =   [
      """GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GPTSanJapaneseForConditionalGeneration""",
      """GPTSanJapaneseModel""",
      """GPTSanJapanesePreTrainedModel""",
  ]
  UpperCAmelCase				 =   [
      """GPTSanJapaneseTokenizer""",
  ]


if TYPE_CHECKING:
  from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
  from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gptsan_japanese import (
        GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTSanJapaneseForConditionalGeneration,
        GPTSanJapaneseModel,
        GPTSanJapanesePreTrainedModel,
    )
    from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer


else:
  import sys

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