




from __future__ import annotations

from typing import Generic, TypeVar

lowerCamelCase_  						=       TypeVar("T")
class 				__a (			Generic[T]					):


     """simple docstring"""


     def __init__(     self      :			int    ,_UpperCamelCase      :			T						)		->       int:


         '''simple docstring'''





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






class 				__a (			Generic[T]					):


     """simple docstring"""


     def __init__(     self      :			int						)		->       None:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__       =None




     def   __A    (     self      :			Dict    ,_UpperCamelCase      :			T						)		->       None:


         '''simple docstring'''





         if self.head is None:
             SCREAMING_SNAKE_CASE__       =Node(_UpperCamelCase						)
         else:
             SCREAMING_SNAKE_CASE__       =Node(_UpperCamelCase						)
             SCREAMING_SNAKE_CASE__       =new_node
             SCREAMING_SNAKE_CASE__       =self.head
             SCREAMING_SNAKE_CASE__       =None
             SCREAMING_SNAKE_CASE__       =new_node




     def   __A    (     self      :			int						)		->       T | None:


         '''simple docstring'''





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




     def   __A    (     self      :			Dict						)		->       T | None:


         '''simple docstring'''





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




     def __len__(     self      :			List[str]						)		->       int:


         '''simple docstring'''





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




     def   __A    (     self      :			List[str]						)		->       bool:


         '''simple docstring'''





         return self.head is None




     def   __A    (     self      :			List[Any]						)		->       None:


         '''simple docstring'''





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


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


lowerCamelCase_  						=       {
    "configuration_marian": ["MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "MarianConfig", "MarianOnnxConfig"],
}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_  						=       ["MarianTokenizer"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_  						=       [
        "MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST",
        "MarianForCausalLM",
        "MarianModel",
        "MarianMTModel",
        "MarianPreTrainedModel",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_  						=       ["TFMarianModel", "TFMarianMTModel", "TFMarianPreTrainedModel"]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_  						=       ["FlaxMarianModel", "FlaxMarianMTModel", "FlaxMarianPreTrainedModel"]

if TYPE_CHECKING:
    from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_marian import MarianTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_marian import (
            MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
            MarianForCausalLM,
            MarianModel,
            MarianMTModel,
            MarianPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
    import sys

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






