


"""simple docstring"""




from __future__ import annotations

from typing import TypedDict





class  _a							(    _lowercase):
	_a  :  str
	_a  :  int






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		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 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		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.'''	)

		lowerCAmelCase__       :      Optional[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
		lowerCAmelCase__       :      BWTTransformDict   					= {
		    "bwt_string": "".join([word[-1] for word in rotations]	),
		    "idx_original_string": rotations.index(_a	),
		}
		return response






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






		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:
				lowerCAmelCase__       :      List[str]   					= 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).'''	)

		lowerCAmelCase__       :      int   					= [''''''] * len(_a	)
		for _ in range(len(_a	)	):
				for i in range(len(_a	)	):
						lowerCAmelCase__       :      List[str]   					= bwt_string[i] + ordered_rotations[i]
				ordered_rotations.sort()
		return ordered_rotations[idx_original_string]


if __name__ == "__main__":
		lowerCamelCase						=		'''Provide a string that I will generate its BWT transform: '''
		lowerCamelCase						=		input(entry_msg).strip()
		lowerCamelCase						=		bwt_transform(s)
		print(
		    f'''Burrows Wheeler transform for string \'{s}\' results '''
		    f'''in \'{result["bwt_string"]}\''''
		)
		lowerCamelCase						=		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_torch_available,
    is_vision_available,
)


lowerCamelCase						=		{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		['''BeitFeatureExtractor''']
		lowerCamelCase						=		['''BeitImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BeitForImageClassification''',
		    '''BeitForMaskedImageModeling''',
		    '''BeitForSemanticSegmentation''',
		    '''BeitModel''',
		    '''BeitPreTrainedModel''',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''FlaxBeitForImageClassification''',
		    '''FlaxBeitForMaskedImageModeling''',
		    '''FlaxBeitModel''',
		    '''FlaxBeitPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_beit import BeitFeatureExtractor
				from .image_processing_beit import BeitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_beit import (
				    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BeitForImageClassification,
				    BeitForMaskedImageModeling,
				    BeitForSemanticSegmentation,
				    BeitModel,
				    BeitPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_beit import (
				    FlaxBeitForImageClassification,
				    FlaxBeitForMaskedImageModeling,
				    FlaxBeitModel,
				    FlaxBeitPreTrainedModel,
				)


else:
		import sys

		lowerCamelCase						=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




