



from __future__ import annotations

a__      :				str   	=			tuple[int, int, int]
a__      :				int   	=			tuple[str, str, str]


# used alphabet --------------------------
# from string.ascii_uppercase
a__      :				int   	=			"ABCDEFGHIJKLMNOPQRSTUVWXYZ"

# -------------------------- default selection --------------------------
# rotors --------------------------
a__      :				List[str]   	=			"EGZWVONAHDCLFQMSIPJBYUKXTR"
a__      :				List[str]   	=			"FOBHMDKEXQNRAULPGSJVTYICZW"
a__      :				Optional[int]   	=			"ZJXESIUQLHAVRMDOYGTNFWPBKC"
# reflector --------------------------
a__      :				int   	=			{
    "A": "N",
    "N": "A",
    "B": "O",
    "O": "B",
    "C": "P",
    "P": "C",
    "D": "Q",
    "Q": "D",
    "E": "R",
    "R": "E",
    "F": "S",
    "S": "F",
    "G": "T",
    "T": "G",
    "H": "U",
    "U": "H",
    "I": "V",
    "V": "I",
    "J": "W",
    "W": "J",
    "K": "X",
    "X": "K",
    "L": "Y",
    "Y": "L",
    "M": "Z",
    "Z": "M",
}

# -------------------------- extra rotors --------------------------
a__      :				Any   	=			"RMDJXFUWGISLHVTCQNKYPBEZOA"
a__      :				Tuple   	=			"SGLCPQWZHKXAREONTFBVIYJUDM"
a__      :				List[Any]   	=			"HVSICLTYKQUBXDWAJZOMFGPREN"
a__      :				int   	=			"RZWQHFMVDBKICJLNTUXAGYPSOE"
a__      :				int   	=			"LFKIJODBEGAMQPXVUHYSTCZRWN"
a__      :				str   	=			"KOAEGVDHXPQZMLFTYWJNBRCIUS"

def   _lowerCAmelCase   (						A__						,  A__						,  A__	):
      # Checks if there are 3 unique rotors

      if (unique_rotsel := len(set(A__	)	)) < 3:
            lowercase__     =  F'''Please use 3 unique rotors (not {unique_rotsel})'''
            raise Exception(A__	)

      # Checks if rotor positions are valid
      lowercase__,	lowercase__,	lowercase__     =  rotpos
      if not 0 < rotorposa <= len(A__	):
            lowercase__     =  F'''First rotor position is not within range of 1..26 ({rotorposa}'''
            raise ValueError(A__	)
      if not 0 < rotorposa <= len(A__	):
            lowercase__     =  F'''Second rotor position is not within range of 1..26 ({rotorposa})'''
            raise ValueError(A__	)
      if not 0 < rotorposa <= len(A__	):
            lowercase__     =  F'''Third rotor position is not within range of 1..26 ({rotorposa})'''
            raise ValueError(A__	)

      # Validates string and returns dict
      lowercase__     =  _plugboard(A__	)

      return rotpos, rotsel, pbdict

def   _lowerCAmelCase   (						A__	):

      # tests the input string if it
      # a) is type string
      # b) has even length (so pairs can be made)
      if not isinstance(A__						,  A__	):
            lowercase__     =  F'''Plugboard setting isn\'t type string ({type(A__	)})'''
            raise TypeError(A__	)
      elif len(A__	) % 2 != 0:
            lowercase__     =  F'''Odd number of symbols ({len(A__	)})'''
            raise Exception(A__	)
      elif pbstring == "":
            return {}

      pbstring.replace(' '						,  ''	)

      # Checks if all characters are unique
      lowercase__     =  set()
      for i in pbstring:
            if i not in abc:
                  lowercase__     =  F'''\'{i}\' not in list of symbols'''
                  raise Exception(A__	)
            elif i in tmppbl:
                  lowercase__     =  F'''Duplicate symbol ({i})'''
                  raise Exception(A__	)
            else:
                  tmppbl.add(A__	)
      del tmppbl

      # Created the dictionary
      lowercase__     =  {}
      for j in range(0						,  len(A__	) - 1						,  2	):
            lowercase__     =  pbstring[j + 1]
            lowercase__     =  pbstring[j]

      return pb

def   _lowerCAmelCase   (						A__						,  A__						,  A__ = (rotora, rotora, rotora)						,  A__ = ""						,  ):
      lowercase__     =  text.upper()
      lowercase__,	lowercase__,	lowercase__     =  _validator(
          A__						,  A__						,  plugb.upper()	)

      lowercase__,	lowercase__,	lowercase__     =  rotor_position
      lowercase__,	lowercase__,	lowercase__     =  rotor_selection
      rotorposa -= 1
      rotorposa -= 1
      rotorposa -= 1

      lowercase__     =  []

      # encryption/decryption process --------------------------
      for symbol in text:
            if symbol in abc:
                  # 1st plugboard --------------------------
                  if symbol in plugboard:
                        lowercase__     =  plugboard[symbol]

                  # rotor ra --------------------------
                  lowercase__     =  abc.index(A__	) + rotorposa
                  lowercase__     =  rotora[index % len(A__	)]

                  # rotor rb --------------------------
                  lowercase__     =  abc.index(A__	) + rotorposa
                  lowercase__     =  rotora[index % len(A__	)]

                  # rotor rc --------------------------
                  lowercase__     =  abc.index(A__	) + rotorposa
                  lowercase__     =  rotora[index % len(A__	)]

                  # reflector --------------------------
                  # this is the reason you don't need another machine to decipher

                  lowercase__     =  reflector[symbol]

                  # 2nd rotors
                  lowercase__     =  abc[rotora.index(A__	) - rotorposa]
                  lowercase__     =  abc[rotora.index(A__	) - rotorposa]
                  lowercase__     =  abc[rotora.index(A__	) - rotorposa]

                  # 2nd plugboard
                  if symbol in plugboard:
                        lowercase__     =  plugboard[symbol]

                  # moves/resets rotor positions
                  rotorposa += 1
                  if rotorposa >= len(A__	):
                        lowercase__     =  0
                        rotorposa += 1
                  if rotorposa >= len(A__	):
                        lowercase__     =  0
                        rotorposa += 1
                  if rotorposa >= len(A__	):
                        lowercase__     =  0

        # else:
        #    pass
        #    Error could be also raised
        #    raise ValueError(
        #       'Invalid symbol('+repr(symbol)+')')
            result.append(A__	)

      return "".join(A__	)


if __name__ == "__main__":
       a__      :				List[Any]   	=			"This is my Python script that emulates the Enigma machine from WWII."
       a__      :				Any   	=			(1, 1, 1)
       a__      :				Union[str, Any]   	=			"pictures"
       a__      :				str   	=			(rotora, rotora, rotora)
       a__      :				List[str]   	=			enigma(message, rotor_pos, rotor_sel, pb)

       print("Encrypted message:", en)
       print("Decrypted message:", enigma(en, rotor_pos, rotor_sel, pb))





import torch

from diffusers import DDIMParallelScheduler

from .test_schedulers import SchedulerCommonTest



class       UpperCAmelCase__(							lowerCamelCase	):

   '''simple docstring'''




   A    :  str       				=    (DDIMParallelScheduler,)
   A    :  Any       				=    (("eta", 0.0), ("num_inference_steps", 50))


   def 			UpperCAmelCase		(						self  :			Union[str, Any]			,				**lowerCAmelCase  :			Optional[int])	->				Dict:




         """simple docstring"""

         lowercase__     =  {
             'num_train_timesteps': 10_00,
             'beta_start': 0.00_01,
             'beta_end': 0.02,
             'beta_schedule': 'linear',
             'clip_sample': True,
         }

         config.update(**lowerCAmelCase)
         return config


   def 			UpperCAmelCase		(						self  :			int			,				**lowerCAmelCase  :			str)	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  self.scheduler_classes[0]
         lowercase__     =  self.get_scheduler_config(**lowerCAmelCase)
         lowercase__     =  scheduler_class(**lowerCAmelCase)

         lowercase__,	lowercase__     =  10, 0.0

         lowercase__     =  self.dummy_model()
         lowercase__     =  self.dummy_sample_deter

         scheduler.set_timesteps(lowerCAmelCase)

         for t in scheduler.timesteps:
               lowercase__     =  model(lowerCAmelCase			,				lowerCAmelCase)
               lowercase__     =  scheduler.step(lowerCAmelCase			,				lowerCAmelCase			,				lowerCAmelCase			,				lowerCAmelCase).prev_sample

         return sample


   def 			UpperCAmelCase		(						self  :			Tuple)	->				int:




         """simple docstring"""

         for timesteps in [1_00, 5_00, 10_00]:
               self.check_over_configs(num_train_timesteps=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Tuple)	->				Any:




         """simple docstring"""

         for steps_offset in [0, 1]:
               self.check_over_configs(steps_offset=lowerCAmelCase)

         lowercase__     =  self.scheduler_classes[0]
         lowercase__     =  self.get_scheduler_config(steps_offset=1)
         lowercase__     =  scheduler_class(**lowerCAmelCase)
         scheduler.set_timesteps(5)
         assert torch.equal(scheduler.timesteps			,				torch.LongTensor([8_01, 6_01, 4_01, 2_01, 1]))


   def 			UpperCAmelCase		(						self  :			str)	->				Tuple:




         """simple docstring"""

         for beta_start, beta_end in zip([0.00_01, 0.0_01, 0.01, 0.1]			,				[0.0_02, 0.02, 0.2, 2]):
               self.check_over_configs(beta_start=lowerCAmelCase			,				beta_end=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Optional[int])	->				str:




         """simple docstring"""

         for schedule in ["linear", "squaredcos_cap_v2"]:
               self.check_over_configs(beta_schedule=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			List[str])	->				List[str]:




         """simple docstring"""

         for prediction_type in ["epsilon", "v_prediction"]:
               self.check_over_configs(prediction_type=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			List[Any])	->				str:




         """simple docstring"""

         for clip_sample in [True, False]:
               self.check_over_configs(clip_sample=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Optional[int])	->				int:




         """simple docstring"""

         for timestep_spacing in ["trailing", "leading"]:
               self.check_over_configs(timestep_spacing=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Any)	->				List[str]:




         """simple docstring"""

         for rescale_betas_zero_snr in [True, False]:
               self.check_over_configs(rescale_betas_zero_snr=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			List[str])	->				Optional[int]:




         """simple docstring"""

         self.check_over_configs(thresholding=lowerCAmelCase)
         for threshold in [0.5, 1.0, 2.0]:
               for prediction_type in ["epsilon", "v_prediction"]:
                     self.check_over_configs(
                         thresholding=lowerCAmelCase			,				prediction_type=lowerCAmelCase			,				sample_max_value=lowerCAmelCase			,				)


   def 			UpperCAmelCase		(						self  :			int)	->				Optional[Any]:




         """simple docstring"""

         for t in [1, 10, 49]:
               self.check_over_forward(time_step=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				int:




         """simple docstring"""

         for t, num_inference_steps in zip([1, 10, 50]			,				[10, 50, 5_00]):
               self.check_over_forward(time_step=lowerCAmelCase			,				num_inference_steps=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				List[Any]:




         """simple docstring"""

         for t, eta in zip([1, 10, 49]			,				[0.0, 0.5, 1.0]):
               self.check_over_forward(time_step=lowerCAmelCase			,				eta=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				List[Any]:




         """simple docstring"""

         lowercase__     =  self.scheduler_classes[0]
         lowercase__     =  self.get_scheduler_config()
         lowercase__     =  scheduler_class(**lowerCAmelCase)

         assert torch.sum(torch.abs(scheduler._get_variance(0			,				0) - 0.0)) < 1E-5
         assert torch.sum(torch.abs(scheduler._get_variance(4_20			,				4_00) - 0.1_47_71)) < 1E-5
         assert torch.sum(torch.abs(scheduler._get_variance(9_80			,				9_60) - 0.3_24_60)) < 1E-5
         assert torch.sum(torch.abs(scheduler._get_variance(0			,				0) - 0.0)) < 1E-5
         assert torch.sum(torch.abs(scheduler._get_variance(4_87			,				4_86) - 0.0_09_79)) < 1E-5
         assert torch.sum(torch.abs(scheduler._get_variance(9_99			,				9_98) - 0.02)) < 1E-5


   def 			UpperCAmelCase		(						self  :			Dict)	->				Tuple:




         """simple docstring"""

         lowercase__     =  self.scheduler_classes[0]
         lowercase__     =  self.get_scheduler_config()
         lowercase__     =  scheduler_class(**lowerCAmelCase)

         lowercase__,	lowercase__     =  10, 0.0
         scheduler.set_timesteps(lowerCAmelCase)

         lowercase__     =  self.dummy_model()
         lowercase__     =  self.dummy_sample_deter
         lowercase__     =  self.dummy_sample_deter + 0.1
         lowercase__     =  self.dummy_sample_deter - 0.1

         lowercase__     =  samplea.shape[0]
         lowercase__     =  torch.stack([samplea, samplea, samplea]			,				dim=0)
         lowercase__     =  torch.arange(lowerCAmelCase)[0:3, None].repeat(1			,				lowerCAmelCase)

         lowercase__     =  model(samples.flatten(0			,				1)			,				timesteps.flatten(0			,				1))
         lowercase__     =  scheduler.batch_step_no_noise(lowerCAmelCase			,				timesteps.flatten(0			,				1)			,				samples.flatten(0			,				1)			,				lowerCAmelCase)

         lowercase__     =  torch.sum(torch.abs(lowerCAmelCase))
         lowercase__     =  torch.mean(torch.abs(lowerCAmelCase))

         assert abs(result_sum.item() - 11_47.79_04) < 1E-2
         assert abs(result_mean.item() - 0.49_82) < 1E-3


   def 			UpperCAmelCase		(						self  :			Any)	->				int:




         """simple docstring"""

         lowercase__     =  self.full_loop()

         lowercase__     =  torch.sum(torch.abs(lowerCAmelCase))
         lowercase__     =  torch.mean(torch.abs(lowerCAmelCase))

         assert abs(result_sum.item() - 1_72.00_67) < 1E-2
         assert abs(result_mean.item() - 0.22_39_67) < 1E-3


   def 			UpperCAmelCase		(						self  :			int)	->				List[Any]:




         """simple docstring"""

         lowercase__     =  self.full_loop(prediction_type='v_prediction')

         lowercase__     =  torch.sum(torch.abs(lowerCAmelCase))
         lowercase__     =  torch.mean(torch.abs(lowerCAmelCase))

         assert abs(result_sum.item() - 52.53_02) < 1E-2
         assert abs(result_mean.item() - 0.06_84) < 1E-3


   def 			UpperCAmelCase		(						self  :			str)	->				Dict:




         """simple docstring"""

         lowercase__     =  self.full_loop(set_alpha_to_one=lowerCAmelCase			,				beta_start=0.01)
         lowercase__     =  torch.sum(torch.abs(lowerCAmelCase))
         lowercase__     =  torch.mean(torch.abs(lowerCAmelCase))

         assert abs(result_sum.item() - 1_49.82_95) < 1E-2
         assert abs(result_mean.item() - 0.19_51) < 1E-3



   def 			UpperCAmelCase		(						self  :			str)	->				List[Any]:




         """simple docstring"""

         lowercase__     =  self.full_loop(set_alpha_to_one=lowerCAmelCase			,				beta_start=0.01)
         lowercase__     =  torch.sum(torch.abs(lowerCAmelCase))
         lowercase__     =  torch.mean(torch.abs(lowerCAmelCase))

         assert abs(result_sum.item() - 1_49.07_84) < 1E-2
         assert abs(result_mean.item() - 0.19_41) < 1E-3
