

import random
from typing import List, Optional, Union

import numpy as np
import torch

from ..state import AcceleratorState
from .constants import CUDA_DISTRIBUTED_TYPES
from .dataclasses import DistributedType, RNGType
from .imports import is_npu_available, is_tpu_available, is_xpu_available


if is_tpu_available(check_device=False):
  import torch_xla.core.xla_model as xm
def 					a				(      A__     :       Union[str, Any]				,       A__     :       Optional[Any] = False					)   ->				List[Any]:





      """simple docstring"""



      if device_specific:
            seed += AcceleratorState().process_index
      random.seed(A_					)
      np.random.seed(A_					)
      torch.manual_seed(A_					)
      if is_xpu_available():
            torch.xpu.manual_seed_all(A_					)
      elif is_npu_available():
            torch.npu.manual_seed_all(A_					)
      else:
            torch.cuda.manual_seed_all(A_					)
      # ^^ safe to call this function even if cuda is not available
      if is_tpu_available():
            xm.set_rng_state(A_					)
def 					a				(      A__     :       Any = None				,       A__     :       Any = None					)   ->				List[Any]:





      """simple docstring"""



      if rng_type == RNGType.TORCH:
            _lowercase     	=torch.get_rng_state()
      elif rng_type == RNGType.CUDA:
            _lowercase     	=torch.cuda.get_rng_state()
      elif rng_type == RNGType.XLA:
            assert is_tpu_available(), "Can't synchronize XLA seeds on an environment without TPUs."
            _lowercase     	=torch.tensor(xm.get_rng_state()					)
      elif rng_type == RNGType.NPU:
            assert is_npu_available(), "Can't synchronize NPU seeds on an environment without NPUs."
            _lowercase     	=torch.npu.get_rng_state()
      elif rng_type == RNGType.XPU:
            assert is_xpu_available(), "Can't synchronize XPU seeds on an environment without XPUs."
            _lowercase     	=torch.xpu.get_rng_state()
      elif rng_type == RNGType.GENERATOR:
            assert generator is not None, "Need a generator to synchronize its seed."
            _lowercase     	=generator.get_state()

      # Broadcast the rng state from device 0 to other devices
      _lowercase     	=AcceleratorState()
      if state.distributed_type == DistributedType.TPU:
            _lowercase     	=rng_state.to(xm.xla_device()					)
            xm.collective_broadcast([rng_state]					)
            xm.mark_step()
            _lowercase     	=rng_state.cpu()
      elif (
          state.distributed_type in CUDA_DISTRIBUTED_TYPES
          or state.distributed_type == DistributedType.MULTI_NPU
          or state.distributed_type == DistributedType.MULTI_XPU
      ):
            _lowercase     	=rng_state.to(state.device					)
            torch.distributed.broadcast(A_				,       0					)
            _lowercase     	=rng_state.cpu()
      elif state.distributed_type == DistributedType.MULTI_CPU:
            torch.distributed.broadcast(A_				,       0					)

      # Set the broadcast rng state
      if rng_type == RNGType.TORCH:
            torch.set_rng_state(A_					)
      elif rng_type == RNGType.CUDA:
            torch.cuda.set_rng_state(A_					)
      elif rng_type == RNGType.NPU:
            torch.npu.set_rng_state(A_					)
      elif rng_type == RNGType.XPU:
            torch.xpu.set_rng_state(A_					)
      elif rng_type == RNGType.XLA:
            xm.set_rng_state(rng_state.item()					)
      elif rng_type == RNGType.GENERATOR:
            generator.set_state(A_					)







def 					a				(      A__     :       List[Any]				,       A__     :       Tuple = None					)   ->				Union[str, Any]:





      """simple docstring"""



      for rng_type in rng_types:
            synchronize_rng_state(RNGType(A_					)				,       generator=A_					)





from __future__ import annotations

import random
import string





class 			__lowerCAmelCase					:




  def __init__(    self							,       lowerCAmelCase = None )  ->			None:
        '''simple docstring'''






        _lowercase     	=passcode or self.__passcode_creator()
        _lowercase     	=self.__make_key_list()
        _lowercase     	=self.__make_shift_key()




  def __str__(    self )  ->			str:
        '''simple docstring'''






        return "".join(self.__passcode )




  def   A__					(    self							,       lowerCAmelCase )  ->			list[int]:
        '''simple docstring'''






        for i in range(1							,       len(lowerCAmelCase )							,       2 ):
              iterlist[i] *= -1
        return iterlist




  def   A__					(    self )  ->			list[str]:
        '''simple docstring'''






        _lowercase     	=string.ascii_letters + string.digits
        _lowercase     	=[random.choice(lowerCAmelCase ) for _ in range(random.randint(10							,       20 ) )]
        return password




  def   A__					(    self )  ->			list[str]:
        '''simple docstring'''






        _lowercase     	=(
            string.ascii_letters + string.digits + string.punctuation + ' \t\n'
        )

        _lowercase     	=[]

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

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

              # 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   A__					(    self )  ->			int:
        '''simple docstring'''






        _lowercase     	=sum(self.__neg_pos([ord(lowerCAmelCase ) for x in self.__passcode] ) )
        return num if num > 0 else len(self.__passcode )




  def   A__					(    self							,       lowerCAmelCase )  ->			str:
        '''simple docstring'''






        _lowercase     	=''

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

        return decoded_message




  def   A__					(    self							,       lowerCAmelCase )  ->			str:
        '''simple docstring'''






        _lowercase     	=''

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

        return encoded_message
def 					a				(      A__     :       str = "Hello, this is a modified Caesar cipher"					)   ->				str:





      """simple docstring"""



      _lowercase     	=ShuffledShiftCipher()
      return cipa.decrypt(cipa.encrypt(A__					)					)


if __name__ == "__main__":
  import doctest

  doctest.testmod()


