

import os

lowerCAmelCase							:  Any            =						{"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1000}







def       A_				(   _UpperCAmelCase   ):
						SCREAMING_SNAKE_CASE_:			Optional[int]  		=	0

						SCREAMING_SNAKE_CASE_:			Any  		=	0
						while index < len(_UpperCAmelCase   ) - 1:
												SCREAMING_SNAKE_CASE_:			Dict  		=	SYMBOLS[numerals[index]]
												SCREAMING_SNAKE_CASE_:			List[str]  		=	SYMBOLS[numerals[index + 1]]
												if current_value < next_value:
																		total_value -= current_value
												else:
																		total_value += current_value
												index += 1
						total_value += SYMBOLS[numerals[index]]

						return total_value







def       A_				(   _UpperCAmelCase   ):
						SCREAMING_SNAKE_CASE_:			Any  		=	""

						SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	num // 10_00
						numerals += m_count * "M"
						num %= 10_00

						SCREAMING_SNAKE_CASE_:			Any  		=	num // 1_00
						if c_count == 9:
												numerals += "CM"
												c_count -= 9
						elif c_count == 4:
												numerals += "CD"
												c_count -= 4
						if c_count >= 5:
												numerals += "D"
												c_count -= 5
						numerals += c_count * "C"
						num %= 1_00

						SCREAMING_SNAKE_CASE_:			str  		=	num // 10
						if x_count == 9:
												numerals += "XC"
												x_count -= 9
						elif x_count == 4:
												numerals += "XL"
												x_count -= 4
						if x_count >= 5:
												numerals += "L"
												x_count -= 5
						numerals += x_count * "X"
						num %= 10

						if num == 9:
												numerals += "IX"
												num -= 9
						elif num == 4:
												numerals += "IV"
												num -= 4
						if num >= 5:
												numerals += "V"
												num -= 5
						numerals += num * "I"

						return numerals







def       A_				(   _UpperCAmelCase = "/p089_roman.txt"   ):
						SCREAMING_SNAKE_CASE_:			int  		=	0

						with open(os.path.dirname(_UpperCAmelCase   ) + roman_numerals_filename   ) as filea:
												SCREAMING_SNAKE_CASE_:			Dict  		=	filea.readlines()

						for line in lines:
												SCREAMING_SNAKE_CASE_:			Optional[int]  		=	line.strip()
												SCREAMING_SNAKE_CASE_:			Tuple  		=	parse_roman_numerals(_UpperCAmelCase   )
												SCREAMING_SNAKE_CASE_:			List[str]  		=	generate_roman_numerals(_UpperCAmelCase   )
												savings += len(_UpperCAmelCase   ) - len(_UpperCAmelCase   )

						return savings


if __name__ == "__main__":
						print(f'''{solution() = }''')









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


lowerCAmelCase							:  Tuple            =						{
    """n_samples""": 64,
    """horizon""": 32,
    """num_inference_steps""": 20,
    """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__":
						lowerCAmelCase							:  Optional[int]            =						"""hopper-medium-v2"""
						lowerCAmelCase							:  Optional[int]            =						gym.make(env_name)

						lowerCAmelCase							:  Optional[int]            =						ValueGuidedRLPipeline.from_pretrained(
						    """bglick13/hopper-medium-v2-value-function-hor32""",
						    env=env,
						)

						env.seed(0)
						lowerCAmelCase							:  Optional[Any]            =						env.reset()
						lowerCAmelCase							:  Union[str, Any]            =						0
						lowerCAmelCase							:  Optional[int]            =						0
						lowerCAmelCase							:  Optional[int]            =						1000
						lowerCAmelCase							:  Dict            =						[obs.copy()]
						try:
												for t in tqdm.tqdm(range(T)):
																		# call the policy
																		lowerCAmelCase							:  Union[str, Any]            =						pipeline(obs, planning_horizon=32)

																		# execute action in environment
																		lowerCAmelCase     ,      lowerCAmelCase     ,      lowerCAmelCase     ,      lowerCAmelCase							:  Dict            =						env.step(denorm_actions)
																		lowerCAmelCase							:  Tuple            =						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())

																		lowerCAmelCase							:  Tuple            =						next_observation
						except KeyboardInterrupt:
												pass

						print(f'''Total reward: {total_reward}''')






