


from __future__ import annotations

from typing import Generic, TypeVar

__magic_name__       					=      TypeVar('''T''')





class    lowerCAmelCase__				(			Generic[T]       ):






						"""simple docstring"""




						def __init__(   self				,							a_     ):
							lowerCamelCase_			:							Optional[int]      =       data  # Assign data
							lowerCamelCase_			:							Node[T] | None      =       None  # Initialize next as null
							lowerCamelCase_			:							Node[T] | None      =       None  # Initialize prev as null





class    lowerCAmelCase__				(			Generic[T]       ):






						"""simple docstring"""




						def __init__(   self     ):
							lowerCamelCase_			:							Node[T] | None      =       None




						def 					_UpperCamelCase			(   self				,							a_     ):
							if self.head is None:
								lowerCamelCase_			:							Optional[int]      =       Node(a_     )
							else:
								lowerCamelCase_			:							Union[str, Any]      =       Node(a_     )
								lowerCamelCase_			:							List[Any]      =       new_node
								lowerCamelCase_			:							Optional[Any]      =       self.head
								lowerCamelCase_			:							Tuple      =       None
								lowerCamelCase_			:							Tuple      =       new_node




						def 					_UpperCamelCase			(   self     ):
							if self.head is None:
								return None
							else:
								assert self.head is not None
								lowerCamelCase_			:							str      =       self.head.data
								lowerCamelCase_			:							Union[str, Any]      =       self.head.next
								if self.head is not None:
									lowerCamelCase_			:							Dict      =       None
								return temp




						def 					_UpperCamelCase			(   self     ):
							return self.head.data if self.head is not None else None




						def __len__(   self     ):
							lowerCamelCase_			:							Union[str, Any]      =       self.head
							lowerCamelCase_			:							Any      =       0
							while temp is not None:
								count += 1
								lowerCamelCase_			:							Union[str, Any]      =       temp.next
							return count




						def 					_UpperCamelCase			(   self     ):
							return self.head is None




						def 					_UpperCamelCase			(   self     ):
							print("stack elements are:"     )
							lowerCamelCase_			:							Dict      =       self.head
							while temp is not None:
								print(temp.data				,							end="->"     )
								lowerCamelCase_			:							Optional[int]      =       temp.next


# Code execution starts here
if __name__ == "__main__":
							# Start with the empty stack
							__magic_name__       					=      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_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__magic_name__       					=      {
    '''configuration_big_bird''': ['''BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BigBirdConfig''', '''BigBirdOnnxConfig'''],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      ['''BigBirdTokenizer''']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      ['''BigBirdTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      [
							    '''BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''BigBirdForCausalLM''',
							    '''BigBirdForMaskedLM''',
							    '''BigBirdForMultipleChoice''',
							    '''BigBirdForPreTraining''',
							    '''BigBirdForQuestionAnswering''',
							    '''BigBirdForSequenceClassification''',
							    '''BigBirdForTokenClassification''',
							    '''BigBirdLayer''',
							    '''BigBirdModel''',
							    '''BigBirdPreTrainedModel''',
							    '''load_tf_weights_in_big_bird''',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      [
							    '''FlaxBigBirdForCausalLM''',
							    '''FlaxBigBirdForMaskedLM''',
							    '''FlaxBigBirdForMultipleChoice''',
							    '''FlaxBigBirdForPreTraining''',
							    '''FlaxBigBirdForQuestionAnswering''',
							    '''FlaxBigBirdForSequenceClassification''',
							    '''FlaxBigBirdForTokenClassification''',
							    '''FlaxBigBirdModel''',
							    '''FlaxBigBirdPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_big_bird import BigBirdTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_big_bird_fast import BigBirdTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_big_bird import (
														    BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BigBirdForCausalLM,
														    BigBirdForMaskedLM,
														    BigBirdForMultipleChoice,
														    BigBirdForPreTraining,
														    BigBirdForQuestionAnswering,
														    BigBirdForSequenceClassification,
														    BigBirdForTokenClassification,
														    BigBirdLayer,
														    BigBirdModel,
														    BigBirdPreTrainedModel,
														    load_tf_weights_in_big_bird,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_big_bird import (
														    FlaxBigBirdForCausalLM,
														    FlaxBigBirdForMaskedLM,
														    FlaxBigBirdForMultipleChoice,
														    FlaxBigBirdForPreTraining,
														    FlaxBigBirdForQuestionAnswering,
														    FlaxBigBirdForSequenceClassification,
														    FlaxBigBirdForTokenClassification,
														    FlaxBigBirdModel,
														    FlaxBigBirdPreTrainedModel,
														)

else:
							import sys

							__magic_name__       					=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

