'''simple docstring'''






def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			str				):
     _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(__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(__snake_case				)				)]

     # for each character in new_string find corresponding palindromic string
     _A    		=  0
     for j in range(len(__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(__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_torch_available,
    is_vision_available,
)


lowercase_									=    {
    "configuration_blip": [
        "BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlipConfig",
        "BlipTextConfig",
        "BlipVisionConfig",
    ],
    "processing_blip": ["BlipProcessor"],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=    ["BlipImageProcessor"]


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=    [
      "BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BlipModel",
      "BlipPreTrainedModel",
      "BlipForConditionalGeneration",
      "BlipForQuestionAnswering",
      "BlipVisionModel",
      "BlipTextModel",
      "BlipForImageTextRetrieval",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=    [
      "TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TFBlipModel",
      "TFBlipPreTrainedModel",
      "TFBlipForConditionalGeneration",
      "TFBlipForQuestionAnswering",
      "TFBlipVisionModel",
      "TFBlipTextModel",
      "TFBlipForImageTextRetrieval",
  ]

if TYPE_CHECKING:
  from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
  from .processing_blip import BlipProcessor

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_blip import BlipImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_blip import (
        BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        BlipForConditionalGeneration,
        BlipForImageTextRetrieval,
        BlipForQuestionAnswering,
        BlipModel,
        BlipPreTrainedModel,
        BlipTextModel,
        BlipVisionModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_blip import (
        TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFBlipForConditionalGeneration,
        TFBlipForImageTextRetrieval,
        TFBlipForQuestionAnswering,
        TFBlipModel,
        TFBlipPreTrainedModel,
        TFBlipTextModel,
        TFBlipVisionModel,
    )

else:
  import sys

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



