





from typing import TYPE_CHECKING

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


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

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

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

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCAmelCase 	=      [
				    '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

				__lowerCAmelCase 	=      _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))