






from typing import TYPE_CHECKING

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


_UpperCAmelCase					:						str         =     {
    'configuration_layoutlm': ['LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMConfig', 'LayoutLMOnnxConfig'],
    'tokenization_layoutlm': ['LayoutLMTokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase					:						Dict         =     ['LayoutLMTokenizerFast']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase					:						Union[str, Any]         =     [
       'LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST',
       'LayoutLMForMaskedLM',
       'LayoutLMForSequenceClassification',
       'LayoutLMForTokenClassification',
       'LayoutLMForQuestionAnswering',
       'LayoutLMModel',
       'LayoutLMPreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase					:						Optional[int]         =     [
       'TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFLayoutLMForMaskedLM',
       'TFLayoutLMForSequenceClassification',
       'TFLayoutLMForTokenClassification',
       'TFLayoutLMForQuestionAnswering',
       'TFLayoutLMMainLayer',
       'TFLayoutLMModel',
       'TFLayoutLMPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMOnnxConfig
   from .tokenization_layoutlm import LayoutLMTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_layoutlm_fast import LayoutLMTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_layoutlm import (
          LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
          LayoutLMForMaskedLM,
          LayoutLMForQuestionAnswering,
          LayoutLMForSequenceClassification,
          LayoutLMForTokenClassification,
          LayoutLMModel,
          LayoutLMPreTrainedModel,
      )
   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_layoutlm import (
          TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFLayoutLMForMaskedLM,
          TFLayoutLMForQuestionAnswering,
          TFLayoutLMForSequenceClassification,
          TFLayoutLMForTokenClassification,
          TFLayoutLMMainLayer,
          TFLayoutLMModel,
          TFLayoutLMPreTrainedModel,
      )

else:
   import sys

   _UpperCAmelCase					:						Optional[Any]         =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







def  UpperCAmelCase__						(    lowerCamelCase	:			list    ):
   lowerCamelCase									=1.3
   lowerCamelCase									=len(lowerCamelCase    )
   lowerCamelCase									=False

   while not completed:
      # Update the gap value for a next comb
      lowerCamelCase									=int(gap / shrink_factor    )
      if gap <= 1:
         lowerCamelCase									=True

      lowerCamelCase									=0
      while index + gap < len(lowerCamelCase    ):
         if data[index] > data[index + gap]:
            # Swap values
            lowerCamelCase				,       lowerCamelCase									=data[index + gap], data[index]
            lowerCamelCase									=False
         index += 1

   return data


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   _UpperCAmelCase					:						List[Any]         =     input('Enter numbers separated by a comma:\n').strip()
   _UpperCAmelCase					:						Optional[Any]         =     [int(item) for item in user_input.split(',')]
   print(comb_sort(unsorted))