



from __future__ import annotations

from typing import TypedDict



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	42
							lowerCamelCase__         =	42






def        A       (      _lowerCamelCase						):





							'''simple docstring'''




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

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






def        A       (      _lowerCamelCase						):





							'''simple docstring'''




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

							_lowerCAmelCase  :							int				     =					all_rotations(_lowerCamelCase						)
							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(_lowerCamelCase						),
							}
							return response






def        A       (      _lowerCamelCase       ,				_lowerCamelCase						):





							'''simple docstring'''




							if not isinstance(_lowerCamelCase       ,				_lowerCamelCase						):
														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  :							Tuple				     =					int(_lowerCamelCase						)
							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(_lowerCamelCase						):
														raise ValueError(
														    "The parameter idx_original_string must be lower than" " len(bwt_string)."						)

							_lowerCAmelCase  :							Optional[int]				     =					[""] * len(_lowerCamelCase						)
							for _ in range(len(_lowerCamelCase						)						):
														for i in range(len(_lowerCamelCase						)						):
																					_lowerCAmelCase  :							List[str]				     =					bwt_string[i] + ordered_rotations[i]
														ordered_rotations.sort()
							return ordered_rotations[idx_original_string]


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





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


_snake_case	=						logging.get_logger(__name__)



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	'upernet'







							def __init__(     self,    __a=None,    __a=512,    __a=0.02,    __a=[1, 2, 3, 6],    __a=True,    __a=0.4,    __a=384,    __a=256,    __a=1,    __a=False,    __a=255,    **__a,    ):

														'''simple docstring'''

														super().__init__(**__a)

														if backbone_config is None:
																					logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.")
																					_lowerCAmelCase  :							List[str]				     =					CONFIG_MAPPING["resnet"](out_features=["stage1", "stage2", "stage3", "stage4"])
														elif isinstance(__a,    __a):
																					_lowerCAmelCase  :							List[Any]				     =					backbone_config.get("model_type")
																					_lowerCAmelCase  :							Dict				     =					CONFIG_MAPPING[backbone_model_type]
																					_lowerCAmelCase  :							Optional[Any]				     =					config_class.from_dict(__a)

														_lowerCAmelCase  :							Tuple				     =					backbone_config
														_lowerCAmelCase  :							List[Any]				     =					hidden_size
														_lowerCAmelCase  :							Union[str, Any]				     =					initializer_range
														_lowerCAmelCase  :							str				     =					pool_scales
														_lowerCAmelCase  :							List[str]				     =					use_auxiliary_head
														_lowerCAmelCase  :							Dict				     =					auxiliary_loss_weight
														_lowerCAmelCase  :							Tuple				     =					auxiliary_in_channels
														_lowerCAmelCase  :							Optional[Any]				     =					auxiliary_channels
														_lowerCAmelCase  :							str				     =					auxiliary_num_convs
														_lowerCAmelCase  :							Union[str, Any]				     =					auxiliary_concat_input
														_lowerCAmelCase  :							Dict				     =					loss_ignore_index







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Any				     =					copy.deepcopy(self.__dict__)
														_lowerCAmelCase  :							List[Any]				     =					self.backbone_config.to_dict()
														_lowerCAmelCase  :							Optional[Any]				     =					self.__class__.model_type
														return output
