

'''simple docstring'''



from typing import TYPE_CHECKING

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


_UpperCamelCase						:  Dict							       =				{
    """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:
     _UpperCamelCase						:  Optional[Any]							       =				["""LayoutLMv3TokenizerFast"""]

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

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

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase						:  Union[str, Any]							       =				["""LayoutLMv3FeatureExtractor"""]
     _UpperCamelCase						:  Any							       =				["""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

     _UpperCamelCase						:  Union[str, Any]							       =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)












"""simple docstring"""


def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		int				   =			0

						# if input_string is "aba" than new_input_string become "a|b|a"
						UpperCamelCase				:		str				   =			""""""
						UpperCamelCase				:		Dict				   =			""""""

						# append each character + "|" in new_string for range(0, length-1)
						for i in input_string[: len(SCREAMING_SNAKE_CASE     ) - 1]:
												new_input_string += i + "|"
						# append last character
						new_input_string += input_string[-1]

						# we will store the starting and ending of previous furthest ending palindromic
						# substring
						UpperCamelCase   ,						UpperCamelCase				:		int				   =			0, 0

						# length[i] shows the length of palindromic substring with center i
						UpperCamelCase				:		List[Any]				   =			[1 for i in range(len(SCREAMING_SNAKE_CASE     )     )]

						# for each character in new_string find corresponding palindromic string
						UpperCamelCase				:		Optional[Any]				   =			0
						for j in range(len(SCREAMING_SNAKE_CASE     )     ):
												UpperCamelCase				:		Union[str, Any]				   =			1 if j > r else min(length[l + r - j] // 2							,     r - j + 1     )
												while (
												    j - k >= 0
												    and j + k < len(SCREAMING_SNAKE_CASE     )
												    and new_input_string[k + j] == new_input_string[j - k]
												):
																		k += 1

												UpperCamelCase				:		int				   =			2 * k - 1

												# does this string is ending after the previously explored end (that is r) ?
												# if yes the update the new r to the last index of this
												if j + k - 1 > r:
																		UpperCamelCase				:		int				   =			j - k + 1  # noqa: E741
																		UpperCamelCase				:		List[Any]				   =			j + k - 1

												# update max_length and start position
												if max_length < length[j]:
																		UpperCamelCase				:		List[str]				   =			length[j]
																		UpperCamelCase				:		List[str]				   =			j

    # create that string
						UpperCamelCase				:		Optional[Any]				   =			new_input_string[start - max_length // 2 : start + max_length // 2 + 1]
						for i in s:
												if i != "|":
																		output_string += i

						return output_string


if __name__ == "__main__":
		import doctest

		doctest.testmod()



