






from __future__ import annotations

import random
import string





class        a__      :






		def __init__(      self							, lowercase__ = None						)				->				None:
				__A    =							passcode or self.__passcode_creator()
				__A    =							self.__make_key_list()
				__A    =							self.__make_shift_key()






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






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






		def 					_lowerCamelCase					(      self						)				->				list[str]:
				__A    =							string.ascii_letters + string.digits
				__A    =							[random.choice(lowercase__						) for _ in range(random.randint(10							, 20						)						)]
				return password






		def 					_lowerCamelCase					(      self						)				->				list[str]:
				__A    =							(
				    string.ascii_letters + string.digits + string.punctuation + " \t\n"
				)

				__A    =							[]

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

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

						# 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 					_lowerCamelCase					(      self						)				->				int:
				__A    =							sum(self.__neg_pos([ord(lowercase__						) for x in self.__passcode]						)						)
				return num if num > 0 else len(self.__passcode						)






		def 					_lowerCamelCase					(      self							, lowercase__						)				->				str:
				__A    =							""

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

				return decoded_message






		def 					_lowerCamelCase					(      self							, lowercase__						)				->				str:
				__A    =							""

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

				return encoded_message



def      UpperCAmelCase						( lowerCAmelCase__ = "Hello, this is a modified Caesar cipher"	):


		'''simple docstring'''

		__A    =							ShuffledShiftCipher()
		return cipa.decrypt(cipa.encrypt(lowerCAmelCase__	)	)


if __name__ == "__main__":
					import doctest

					doctest.testmod()






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase:					int      =						logging.get_logger(__name__)

_lowercase:					Dict      =						{
    "google/mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json"
}



class       _lowercase				(  lowerCAmelCase      ):





	"""simple docstring"""
	__A		      =				MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
	__A		      =				"mobilebert"




	def __init__(self						,			lowerCamelCase_=30522						,			lowerCamelCase_=512						,			lowerCamelCase_=24						,			lowerCamelCase_=4						,			lowerCamelCase_=512						,			lowerCamelCase_="relu"						,			lowerCamelCase_=0.0						,			lowerCamelCase_=0.1						,			lowerCamelCase_=512						,			lowerCamelCase_=2						,			lowerCamelCase_=0.02						,			lowerCamelCase_=1E-1_2						,			lowerCamelCase_=0						,			lowerCamelCase_=128						,			lowerCamelCase_=True						,			lowerCamelCase_=True						,			lowerCamelCase_=128						,			lowerCamelCase_=False						,			lowerCamelCase_=True						,			lowerCamelCase_=4						,			lowerCamelCase_="no_norm"						,			lowerCamelCase_=True						,			lowerCamelCase_=None						,			**lowerCamelCase_						,			):
						"""simple docstring"""

						super().__init__(pad_token_id=lowerCamelCase_						,			**lowerCamelCase_						)

						a   	=  vocab_size
						a   	=  hidden_size
						a   	=  num_hidden_layers
						a   	=  num_attention_heads
						a   	=  hidden_act
						a   	=  intermediate_size
						a   	=  hidden_dropout_prob
						a   	=  attention_probs_dropout_prob
						a   	=  max_position_embeddings
						a   	=  type_vocab_size
						a   	=  initializer_range
						a   	=  layer_norm_eps
						a   	=  embedding_size
						a   	=  trigram_input
						a   	=  use_bottleneck
						a   	=  intra_bottleneck_size
						a   	=  use_bottleneck_attention
						a   	=  key_query_shared_bottleneck
						a   	=  num_feedforward_networks
						a   	=  normalization_type
						a   	=  classifier_activation

						if self.use_bottleneck:
											a   	=  intra_bottleneck_size
						else:
											a   	=  hidden_size

						a   	=  classifier_dropout




class       _lowercase				(  lowerCAmelCase      ):





	"""simple docstring"""




	@property
	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						if self.task == "multiple-choice":
											a   	=  {0: "batch", 1: "choice", 2: "sequence"}
						else:
											a   	=  {0: "batch", 1: "sequence"}
						return OrderedDict(
						    [
						        ("input_ids", dynamic_axis),
						        ("attention_mask", dynamic_axis),
						        ("token_type_ids", dynamic_axis),
						    ]						)
