


"""simple docstring"""




def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__						):
 __lowerCamelCase		:							List[Any]		 =						''
 for ch in key:
  if ch == " " or ch not in key_no_dups and ch.isalpha():
   key_no_dups += ch
 return key_no_dups
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__						):
 __lowerCamelCase		:							Union[str, Any]		 =						[chr(i + 65						) for i in range(26						)]
 # Remove duplicate characters from key
 __lowerCamelCase		:							Optional[int]		 =						remove_duplicates(key.upper()						)
 __lowerCamelCase		:							Optional[int]		 =						len(SCREAMING_SNAKE_CASE__						)
 # First fill cipher with key characters
 __lowerCamelCase		:							int		 =						{alphabet[i]: char for i, char in enumerate(SCREAMING_SNAKE_CASE__						)}
 # Then map remaining characters in alphabet to
 # the alphabet from the beginning
 for i in range(len(SCREAMING_SNAKE_CASE__						)      ,	26						):
  __lowerCamelCase		:							Optional[Any]		 =						alphabet[i - offset]
  # Ensure we are not mapping letters to letters previously mapped
  while char in key:
   offset -= 1
   __lowerCamelCase		:							Any		 =						alphabet[i - offset]
  __lowerCamelCase		:							Optional[Any]		 =						char
 return cipher_alphabet
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						):
 return "".join(cipher_map.get(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						) for ch in message.upper()						)
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						):
 __lowerCamelCase		:							Tuple		 =						{v: k for k, v in cipher_map.items()}
 return "".join(rev_cipher_map.get(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						) for ch in message.upper()						)
def 				UpperCamelCase__					(  ):
 __lowerCamelCase		:							int		 =						input('Enter message to encode or decode: '						).strip()
 __lowerCamelCase		:							Any		 =						input('Enter keyword: '						).strip()
 __lowerCamelCase		:							Tuple		 =						input('Encipher or decipher? E/D:'						).strip()[0].lower()
 try:
  __lowerCamelCase		:							Any		 =						{'e': encipher, 'd': decipher}[option]
 except KeyError:
  raise KeyError('invalid input option'						)
 __lowerCamelCase		:							Optional[Any]		 =						create_cipher_map(SCREAMING_SNAKE_CASE__						)
 print(func(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						)						)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       main()





import darl  # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline


lowercase_	   =     {
    'n_samples': 6_4,
    'horizon': 3_2,
    'num_inference_steps': 2_0,
    'n_guide_steps': 2,  # can set to 0 for faster sampling, does not use value network
    'scale_grad_by_std': True,
    'scale': 0.1,
    'eta': 0.0,
    't_grad_cutoff': 2,
    'device': 'cpu',
}


if __name__ == "__main__":
       lowercase_	   =     'hopper-medium-v2'
       lowercase_	   =     gym.make(env_name)

       lowercase_	   =     ValueGuidedRLPipeline.from_pretrained(
           'bglick13/hopper-medium-v2-value-function-hor32',
           env=env,
       )

       env.seed(0)
       lowercase_	   =     env.reset()
       lowercase_	   =     0
       lowercase_	   =     0
       lowercase_	   =     1_0_0_0
       lowercase_	   =     [obs.copy()]
       try:
              for t in tqdm.tqdm(range(T)):
                     # call the policy
                     lowercase_	   =     pipeline(obs, planning_horizon=3_2)

                     # execute action in environment
                     lowercase_   ,lowercase_   ,lowercase_   ,lowercase_	   =     env.step(denorm_actions)
                     lowercase_	   =     env.get_normalized_score(total_reward)

                     # update return
                     total_reward += reward
                     total_score += score
                     print(
                         F"""Step: {t}, Reward: {reward}, Total Reward: {total_reward}, Score: {score}, Total Score:"""
                         F""" {total_score}"""
                     )

                     # save observations for rendering
                     rollout.append(next_observation.copy())

                     lowercase_	   =     next_observation
       except KeyboardInterrupt:
              pass

       print(F"""Total reward: {total_reward}""")

