


class 				__SCREAMING_SNAKE_CASE   :


      def __init__(							self							,						SCREAMING_SNAKE_CASE__=None		):
            lowercase			:   Tuple					   =		data
            lowercase			:   Tuple					   =		None






      def __repr__(							self		):
            lowercase			:   Any					   =		''''''
            lowercase			:   int					   =		self
            while temp:
                  string_rep += f"""<{temp.data}> ---> """
                  lowercase			:   List[str]					   =		temp.next
            string_rep += "<END>"
            return string_rep





def 			__lowercase	(						_UpperCamelCase     )    ->List[Any]:







      """simple docstring"""

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

      # Set first element as Head
      lowercase			:   Optional[Any]					   =		Node(elements_list[0]     )
      lowercase			:   Tuple					   =		head
      # Loop through elements from position 1
      for data in elements_list[1:]:
            lowercase			:   Any					   =		Node(_UpperCamelCase     )
            lowercase			:   List[str]					   =		current.next
      return head


__a   				=      [1, 3, 5, 32, 44, 12, 43]
print(F'''List: {list_data}''')
print('''Creating Linked List from List.''')
__a   				=      make_linked_list(list_data)
print('''Linked List:''')



print(linked_list)





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a   				=      {
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   				=      [
      '''DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''DecisionTransformerGPT2Model''',
      '''DecisionTransformerGPT2PreTrainedModel''',
      '''DecisionTransformerModel''',
      '''DecisionTransformerPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_decision_transformer import (
      DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      DecisionTransformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_decision_transformer import (
        DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        DecisionTransformerGPTaModel,
        DecisionTransformerGPTaPreTrainedModel,
        DecisionTransformerModel,
        DecisionTransformerPreTrainedModel,
    )


else:
  import sys

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

