


"""simple docstring"""


def  __snake_case       (   UpperCamelCase__	)      ->		str:







		"""simple docstring"""





		A					       = 0

		# if input_string is "aba" than new_input_string become "a|b|a"
		A					       = ''
		A					       = ''

		# 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
		A       , A					       = 0, 0

		# length[i] shows the length of palindromic substring with center i
		A					       = [1 for i in range(len(SCREAMING_SNAKE_CASE_	)	)]

		# for each character in new_string find corresponding palindromic string
		A					       = 0
		for j in range(len(SCREAMING_SNAKE_CASE_	)	):
				A					       = 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

				A					       = 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:
						A					       = j - k + 1  # noqa: E741
						A					       = j + k - 1

				# update max_length and start position
				if max_length < length[j]:
						A					       = length[j]
						A					       = j

    # create that string
		A					       = 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()









"""simple docstring"""


from typing import TYPE_CHECKING

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


UpperCamelCase						:				Any             =      {
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				int             =      ["LxmertTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				Union[str, Any]             =      [
	    "LxmertEncoder",
	    "LxmertForPreTraining",
	    "LxmertForQuestionAnswering",
	    "LxmertModel",
	    "LxmertPreTrainedModel",
	    "LxmertVisualFeatureEncoder",
	    "LxmertXLayer",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				Union[str, Any]             =      [
	    "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFLxmertForPreTraining",
	    "TFLxmertMainLayer",
	    "TFLxmertModel",
	    "TFLxmertPreTrainedModel",
	    "TFLxmertVisualFeatureEncoder",
	]


if TYPE_CHECKING:
	from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
	from .tokenization_lxmert import LxmertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_lxmert_fast import LxmertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_lxmert import (
		    LxmertEncoder,
		    LxmertForPreTraining,
		    LxmertForQuestionAnswering,
		    LxmertModel,
		    LxmertPreTrainedModel,
		    LxmertVisualFeatureEncoder,
		    LxmertXLayer,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_lxmert import (
		    TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFLxmertForPreTraining,
		    TFLxmertMainLayer,
		    TFLxmertModel,
		    TFLxmertPreTrainedModel,
		    TFLxmertVisualFeatureEncoder,
		)

else:
	import sys

	UpperCamelCase						:				Dict             =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





