





"""simple docstring"""





from typing import TYPE_CHECKING

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


__A											=						{
    """configuration_layoutlmv3""": [
        """LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """LayoutLMv3Config""",
        """LayoutLMv3OnnxConfig""",
    ],
    """processing_layoutlmv3""": ["""LayoutLMv3Processor"""],
    """tokenization_layoutlmv3""": ["""LayoutLMv3Tokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A											=						["""LayoutLMv3TokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A											=						[
      """LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """LayoutLMv3ForQuestionAnswering""",
      """LayoutLMv3ForSequenceClassification""",
      """LayoutLMv3ForTokenClassification""",
      """LayoutLMv3Model""",
      """LayoutLMv3PreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A											=						[
      """TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFLayoutLMv3ForQuestionAnswering""",
      """TFLayoutLMv3ForSequenceClassification""",
      """TFLayoutLMv3ForTokenClassification""",
      """TFLayoutLMv3Model""",
      """TFLayoutLMv3PreTrainedModel""",
  ]

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A											=						["""LayoutLMv3FeatureExtractor"""]
  __A											=						["""LayoutLMv3ImageProcessor"""]


if TYPE_CHECKING:
  from .configuration_layoutlmva import (
      LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
      LayoutLMvaConfig,
      LayoutLMvaOnnxConfig,
  )
  from .processing_layoutlmva import LayoutLMvaProcessor
  from .tokenization_layoutlmva import LayoutLMvaTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_layoutlmva import (
        LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
        LayoutLMvaForQuestionAnswering,
        LayoutLMvaForSequenceClassification,
        LayoutLMvaForTokenClassification,
        LayoutLMvaModel,
        LayoutLMvaPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_layoutlmva import (
        TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFLayoutLMvaForQuestionAnswering,
        TFLayoutLMvaForSequenceClassification,
        TFLayoutLMvaForTokenClassification,
        TFLayoutLMvaModel,
        TFLayoutLMvaPreTrainedModel,
    )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
    from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
  import sys

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







"""simple docstring"""



def 						__lowercase	(  snake_case_    :    int		)  ->int:



    '''simple docstring'''







    __A       :		str							=	1
    for i in range(1							,num + 1		):
        fact *= i
    return fact







def 						__lowercase	(  snake_case_    :    int		)  ->int:



    '''simple docstring'''







    __A       :		str							=	0
    while number > 0:
        __A       :		Optional[int]							=	number % 10
        sum_of_digits += last_digit
        __A       :		Dict							=	number // 10  # Removing the last_digit from the given number
    return sum_of_digits







def 						__lowercase	(  snake_case_    :    int = 100		)  ->int:



    '''simple docstring'''







    __A       :		Optional[int]							=	factorial(snake_case_		)
    __A       :		Optional[Any]							=	split_and_add(snake_case_		)
    return result


if __name__ == "__main__":
       print(solution(int(input("""Enter the Number: """).strip())))




