





"""simple docstring"""





from __future__ import annotations






class    _lowerCAmelCase  :
       """simple docstring"""




       def __init__(       self       ,					__UpperCAmelCase=None ):



         '''simple docstring'''

         lowerCAmelCase__     :Union[str, Any]											=				data
         lowerCAmelCase__     :Optional[Any]											=				None






       def __repr__(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :List[Any]											=				[]
         lowerCAmelCase__     :Union[str, Any]											=				self
         while temp:
           string_rep.append(F"{temp.data}" )
           lowerCAmelCase__     :Any											=				temp.next
         return "->".join(snake_case_ )






def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  if not elements_list:
    raise Exception('The Elements List is empty'     )

  lowerCAmelCase__     :str											=				Node(elements_list[0]     )
  for i in range(1	,  len(_lowerCAmelCase     )     ):
    lowerCAmelCase__     :Union[str, Any]											=				Node(elements_list[i]     )
    lowerCAmelCase__     :Tuple											=				current.next
  return head
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->None:





  """simple docstring"""


  if head_node is not None and isinstance(_lowerCAmelCase	,  _lowerCAmelCase     ):
    print_reverse(head_node.next     )
    print(head_node.data     )
def 					__A  ()   ->List[Any]:





  """simple docstring"""


  from doctest import testmod

  testmod()

  lowerCAmelCase__     :Tuple											=				make_linked_list([14, 52, 14, 12, 43]     )
  print('Linked List:'     )
  print(_lowerCAmelCase     )
  print('Elements in Reverse:'     )
  print_reverse(_lowerCAmelCase     )


if __name__ == "__main__":
  main()





'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__a  			=						{
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __a  			=						[
           "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
           "GPTBigCodeForSequenceClassification",
           "GPTBigCodeForTokenClassification",
           "GPTBigCodeForCausalLM",
           "GPTBigCodeModel",
           "GPTBigCodePreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_gpt_bigcode import (
                  GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GPTBigCodeForCausalLM,
                  GPTBigCodeForSequenceClassification,
                  GPTBigCodeForTokenClassification,
                  GPTBigCodeModel,
                  GPTBigCodePreTrainedModel,
              )


else:
       import sys

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