

from __future__ import annotations

from typing import TypedDict







class        a__       (   _A       ):







		"""simple docstring"""




		UpperCAmelCase__      : Optional[Any]			       =4_2
		UpperCAmelCase__      : Tuple			       =4_2






def 					__lowercase      (     _A			)     ->						Union[str, Any]:





						if not isinstance(A_						,    A_			):
												raise TypeError("""The parameter s type must be str."""			)

						return [s[i:] + s[:i] for i in range(len(A_			)			)]






def 					__lowercase      (     _A			)     ->						Union[str, Any]:





						if not isinstance(A_						,    A_			):
												raise TypeError("""The parameter s type must be str."""			)
						if not s:
												raise ValueError("""The parameter s must not be empty."""			)

						SCREAMING_SNAKE_CASE :      List[Any]       =   all_rotations(A_			)
						rotations.sort()  # sort the list of rotations in alphabetically order
						# make a string composed of the last char of each rotation
						SCREAMING_SNAKE_CASE :      Dict       =   {
						    """bwt_string""": """""".join([word[-1] for word in rotations]			),
						    """idx_original_string""": rotations.index(A_			),
						}
						return response






def 					__lowercase      (     _A						,    _A			)     ->						Optional[int]:





						if not isinstance(A_						,    A_			):
												raise TypeError("""The parameter bwt_string type must be str."""			)
						if not bwt_string:
												raise ValueError("""The parameter bwt_string must not be empty."""			)
						try:
												SCREAMING_SNAKE_CASE :      Optional[Any]       =   int(A_			)
						except ValueError:
												raise TypeError(
												    """The parameter idx_original_string type must be int or passive"""
												    """ of cast to int."""			)
						if idx_original_string < 0:
												raise ValueError("""The parameter idx_original_string must not be lower than 0."""			)
						if idx_original_string >= len(A_			):
												raise ValueError(
												    """The parameter idx_original_string must be lower than""" """ len(bwt_string)."""			)

						SCREAMING_SNAKE_CASE :      List[Any]       =   [""""""] * len(A_			)
						for _ in range(len(A_			)			):
												for i in range(len(A_			)			):
																		SCREAMING_SNAKE_CASE :      str       =   bwt_string[i] + ordered_rotations[i]
												ordered_rotations.sort()
						return ordered_rotations[idx_original_string]


if __name__ == "__main__":
		UpperCAmelCase__ :     Tuple				    =    'Provide a string that I will generate its BWT transform: '
		UpperCAmelCase__ :     List[Any]				    =    input(entry_msg).strip()
		UpperCAmelCase__ :     List[Any]				    =    bwt_transform(s)
		print(
		    F"""Burrows Wheeler transform for string \'{s}\' results """
		    F"""in \'{result['bwt_string']}\'"""
		)
		UpperCAmelCase__ :     Optional[Any]				    =    reverse_bwt(result["""bwt_string"""], result["""idx_original_string"""])
		print(
		    F"""Reversing Burrows Wheeler transform for entry \'{result['bwt_string']}\' """
		    F"""we get original string \'{original_string}\'"""
		)







from typing import TYPE_CHECKING

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


UpperCAmelCase__ :     List[Any]				    =    {"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTConfig""", """ViTOnnxConfig"""]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__ :     Union[str, Any]				    =    ["""ViTFeatureExtractor"""]
  UpperCAmelCase__ :     List[Any]				    =    ["""ViTImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__ :     List[Any]				    =    [
      """VIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """ViTForImageClassification""",
      """ViTForMaskedImageModeling""",
      """ViTModel""",
      """ViTPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__ :     Tuple				    =    [
      """TFViTForImageClassification""",
      """TFViTModel""",
      """TFViTPreTrainedModel""",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__ :     str				    =    [
      """FlaxViTForImageClassification""",
      """FlaxViTModel""",
      """FlaxViTPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_vit import ViTFeatureExtractor
    from .image_processing_vit import ViTImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_vit import (
        VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
        ViTForImageClassification,
        ViTForMaskedImageModeling,
        ViTModel,
        ViTPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
  import sys

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




