




"""simple docstring"""







from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_      =					{
    'configuration_deberta_v2': ['DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DebertaV2Config', 'DebertaV2OnnxConfig'],
    'tokenization_deberta_v2': ['DebertaV2Tokenizer'],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE_      =					['DebertaV2TokenizerFast']

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE_      =					[
      'TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFDebertaV2ForMaskedLM',
      'TFDebertaV2ForQuestionAnswering',
      'TFDebertaV2ForSequenceClassification',
      'TFDebertaV2ForTokenClassification',
      'TFDebertaV2Model',
      'TFDebertaV2PreTrainedModel',
  ]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE_      =					[
      'DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
      'DebertaV2ForMaskedLM',
      'DebertaV2ForMultipleChoice',
      'DebertaV2ForQuestionAnswering',
      'DebertaV2ForSequenceClassification',
      'DebertaV2ForTokenClassification',
      'DebertaV2Model',
      'DebertaV2PreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_deberta_va import (
      DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
      DebertaVaConfig,
      DebertaVaOnnxConfig,
  )
  from .tokenization_deberta_va import DebertaVaTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_deberta_va import (
        TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFDebertaVaForMaskedLM,
        TFDebertaVaForQuestionAnswering,
        TFDebertaVaForSequenceClassification,
        TFDebertaVaForTokenClassification,
        TFDebertaVaModel,
        TFDebertaVaPreTrainedModel,
    )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_deberta_va import (
        DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
        DebertaVaForMaskedLM,
        DebertaVaForMultipleChoice,
        DebertaVaForQuestionAnswering,
        DebertaVaForSequenceClassification,
        DebertaVaForTokenClassification,
        DebertaVaModel,
        DebertaVaPreTrainedModel,
    )

else:
  import sys

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





"""simple docstring"""







class 							snake_case_ :







   """simple docstring"""




   def __init__(		self					,				lowerCamelCase_=None)							->      Tuple:
       UpperCamelCase										=  data
       UpperCamelCase										=  None







   def __repr__(		self)							->      Union[str, Any]:
       UpperCamelCase										=  ''''''
       UpperCamelCase										=  self
       while temp:
           string_rep += F'<{temp.data}> ---> '
           UpperCamelCase										=  temp.next
       string_rep += "<END>"
       return string_rep





def     __snake_case   (							_lowercase						):


    """simple docstring"""







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

    # Set first element as Head
    UpperCamelCase										=  Node(elements_list[0]						)
    UpperCamelCase										=  head
    # Loop through elements from position 1
    for data in elements_list[1:]:
        UpperCamelCase										=  Node(_lowercase						)
        UpperCamelCase										=  current.next
    return head


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


print(linked_list)