"""simple docstring"""





from __future__ import annotations

import random
import string


class 					UpperCAmelCase_     :


      def __init__(       self		,      a = None							)	-> None:
             lowercase__      :		List[Any]          =     passcode or self.__passcode_creator()
             lowercase__      :		Optional[int]          =     self.__make_key_list()
             lowercase__      :		str          =     self.__make_shift_key()


      def __str__(       self							)	-> str:
             return "".join(self.__passcode							)


      def 		_UpperCAmelCase	(       self		,      a							)	-> list[int]:
             for i in range(1		,      len(a							)		,      2							):
                    iterlist[i] *= -1
             return iterlist


      def 		_UpperCAmelCase	(       self							)	-> list[str]:
             lowercase__      :		Any          =     string.ascii_letters + string.digits
             lowercase__      :		Optional[Any]          =     [random.choice(a							) for _ in range(random.randint(1_0		,      2_0							)							)]
             return password


      def 		_UpperCAmelCase	(       self							)	-> list[str]:
             lowercase__      :		Optional[Any]          =     (
                 string.ascii_letters + string.digits + string.punctuation + ' \t\n'
             )

             lowercase__      :		Tuple          =     []

             # creates points known as breakpoints to break the key_list_options at those
             # points and pivot each substring
             lowercase__      :		str          =     sorted(set(self.__passcode							)							)
             lowercase__      :		list[str]          =     []

             # algorithm for creating a new shuffled list, keys_l, out of key_list_options
             for i in key_list_options:
                    temp_list.extend(a							)

                    # checking breakpoints at which to pivot temporary sublist and add it into
                    # keys_l
                    if i in breakpoints or i == key_list_options[-1]:
                           keys_l.extend(temp_list[::-1]							)
                           temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
             return keys_l


      def 		_UpperCAmelCase	(       self							)	-> int:
             lowercase__      :		List[Any]          =     sum(self.__neg_pos([ord(a							) for x in self.__passcode]							)							)
             return num if num > 0 else len(self.__passcode							)


      def 		_UpperCAmelCase	(       self		,      a							)	-> str:
             lowercase__      :		Tuple          =     ''

             # decoding shift like Caesar cipher algorithm implementing negative shift or
             # reverse shift or left shift
             for i in encoded_message:
                    lowercase__      :		Tuple          =     self.__key_list.index(a							)
                    decoded_message += self.__key_list[
                        (position - self.__shift_key) % -len(self.__key_list							)
                    ]

             return decoded_message


      def 		_UpperCAmelCase	(       self		,      a							)	-> str:
             lowercase__      :		int          =     ''

             # encoding shift like Caesar cipher algorithm implementing positive shift or
             # forward shift or right shift
             for i in plaintext:
                    lowercase__      :		List[Any]          =     self.__key_list.index(a							)
                    encoded_message += self.__key_list[
                        (position + self.__shift_key) % len(self.__key_list							)
                    ]

             return encoded_message





def     a_					(				_lowerCAmelCase  :			str = "Hello, this is a modified Caesar cipher"					):





       '''simple docstring'''

       lowercase__      :		str          =     ShuffledShiftCipher()
       return cipa.decrypt(cipa.encrypt(_lowerCAmelCase					)					)


if __name__ == "__main__":
       import doctest

       doctest.testmod()


"""simple docstring"""





import copy
from typing import Dict, Optional

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


_UpperCamelCase       :						Optional[int]     =   logging.get_logger(__name__)

_UpperCamelCase       :						Any     =   {
    "shi-labs/oneformer_ade20k_swin_tiny": (
        "https://huggingface.co/shi-labs/oneformer_ade20k_swin_tiny/blob/main/config.json"
    ),
    # See all OneFormer models at https://huggingface.co/models?filter=oneformer
}


class 					UpperCAmelCase_     (   _a):
      lowerCamelCase__		:   Optional[Any]			  =  "oneformer"
      lowerCamelCase__		:   Union[str, Any]			  =  {"hidden_size": "hidden_dim"}


      def __init__(       self		,      a = None		,      a = 2_5_5		,      a = 1_5_0		,      a = 0.1		,      a = 2.0		,      a = 5.0		,      a = 5.0		,      a = 0.5		,      a = 0.07		,      a = 1_2_5_4_4		,      a = 3.0		,      a = 0.75		,      a = 0.02		,      a = 1.0		,      a = 1e-05		,      a = False		,      a = True		,      a = True		,      a = [4, 8, 1_6, 3_2]		,      a = 7_7		,      a = 2_5_6		,      a = 7_7		,      a = 6		,      a = 4_9_4_0_8		,      a = 2		,      a = 1_6		,      a = 2_5_6		,      a = 2_5_6		,      a = 2_5_6		,      a = 1_0_2_4		,      a = "GN"		,      a = 6		,      a = 1_0		,      a = True		,      a = 8		,      a = 0.1		,      a = 2_0_4_8		,      a = False		,      a = False		,      a = 2		,      a = 4		,      **a		,      )	-> List[Any]:
             if backbone_config is None:
                    logger.info('`backbone_config` is unset. Initializing the config with the default `Swin` backbone.'							)
                    lowercase__      :		List[str]          =     CONFIG_MAPPING['swin'](
                        image_size=2_2_4		,      in_channels=3		,      patch_size=4		,      embed_dim=9_6		,      depths=[2, 2, 6, 2]		,      num_heads=[3, 6, 1_2, 2_4]		,      window_size=7		,      drop_path_rate=0.3		,      use_absolute_embeddings=a		,      out_features=['stage1', 'stage2', 'stage3', 'stage4']		,      )
             elif isinstance(a		,      a							):
                    lowercase__      :		Union[str, Any]          =     backbone_config.get('model_type'							)
                    lowercase__      :		Optional[int]          =     CONFIG_MAPPING[backbone_model_type]
                    lowercase__      :		Optional[Any]          =     config_class.from_dict(a							)

             lowercase__      :		Tuple          =     backbone_config

             lowercase__      :		Optional[Any]          =     ignore_value
             lowercase__      :		int          =     num_queries
             lowercase__      :		str          =     no_object_weight
             lowercase__      :		str          =     class_weight
             lowercase__      :		Dict          =     mask_weight
             lowercase__      :		str          =     dice_weight
             lowercase__      :		Union[str, Any]          =     contrastive_weight
             lowercase__      :		Tuple          =     contrastive_temperature
             lowercase__      :		List[str]          =     train_num_points
             lowercase__      :		Tuple          =     oversample_ratio
             lowercase__      :		Tuple          =     importance_sample_ratio
             lowercase__      :		Optional[int]          =     init_std
             lowercase__      :		Optional[int]          =     init_xavier_std
             lowercase__      :		List[str]          =     layer_norm_eps
             lowercase__      :		str          =     is_training
             lowercase__      :		Dict          =     use_auxiliary_loss
             lowercase__      :		Any          =     output_auxiliary_logits
             lowercase__      :		str          =     strides
             lowercase__      :		Any          =     task_seq_len
             lowercase__      :		List[Any]          =     text_encoder_width
             lowercase__      :		Dict          =     text_encoder_context_length
             lowercase__      :		Any          =     text_encoder_num_layers
             lowercase__      :		Any          =     text_encoder_vocab_size
             lowercase__      :		str          =     text_encoder_proj_layers
             lowercase__      :		str          =     text_encoder_n_ctx
             lowercase__      :		List[Any]          =     conv_dim
             lowercase__      :		Optional[Any]          =     mask_dim
             lowercase__      :		List[Any]          =     hidden_dim
             lowercase__      :		int          =     encoder_feedforward_dim
             lowercase__      :		List[str]          =     norm
             lowercase__      :		Union[str, Any]          =     encoder_layers
             lowercase__      :		List[Any]          =     decoder_layers
             lowercase__      :		int          =     use_task_norm
             lowercase__      :		Union[str, Any]          =     num_attention_heads
             lowercase__      :		Union[str, Any]          =     dropout
             lowercase__      :		Any          =     dim_feedforward
             lowercase__      :		Optional[int]          =     pre_norm
             lowercase__      :		Tuple          =     enforce_input_proj
             lowercase__      :		List[Any]          =     query_dec_layers
             lowercase__      :		Optional[int]          =     common_stride
             lowercase__      :		str          =     decoder_layers

             super().__init__(**a							)


      def 		_UpperCAmelCase	(       self							)	-> Dict[str, any]:
             lowercase__      :		str          =     copy.deepcopy(self.__dict__							)
             lowercase__      :		Union[str, Any]          =     self.backbone_config.to_dict()
             lowercase__      :		str          =     self.__class__.model_type
             return output

