
import argparse
import hashlib  # hashlib is only used inside the Test class
import struct


class     lowercase :



		def __init__(			self    ,				A_	)  -> str:
				"""simple docstring"""
				UpperCamelCase          =					data
				UpperCamelCase          =					[0X67_452_301, 0XEF_CDA_B89, 0X98_BAD_CFE, 0X10_325_476, 0XC3_D2E_1F0]



		@staticmethod
		def __UpperCamelCase			(			A_    ,				A_	)  -> str:
				"""simple docstring"""
				return ((n << b) | (n >> (32 - b))) & 0XFF_FFF_FFF



		def __UpperCamelCase			(			self	)  -> Optional[int]:
				"""simple docstring"""
				UpperCamelCase          =					b'\x80' + b'\x00' * (63 - (len(self.data	) + 8) % 64)
				UpperCamelCase          =					self.data + padding + struct.pack('>Q'    ,				8 * len(self.data	)	)
				return padded_data



		def __UpperCamelCase			(			self	)  -> Tuple:
				"""simple docstring"""
				return [
				    self.padded_data[i : i + 64] for i in range(0    ,				len(self.padded_data	)    ,				64	)
				]



		def __UpperCamelCase			(			self    ,				A_	)  -> List[str]:
				"""simple docstring"""
				UpperCamelCase          =					list(struct.unpack('>16L'    ,				A_	)	) + [0] * 64
				for i in range(16    ,				80	):
						UpperCamelCase          =					self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16])    ,				1	)
				return w



		def __UpperCamelCase			(			self	)  -> Union[str, Any]:
				"""simple docstring"""
				UpperCamelCase          =					self.padding()
				UpperCamelCase          =					self.split_blocks()
				for block in self.blocks:
						UpperCamelCase          =					self.expand_block(A_	)
						UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase          =					self.h
						for i in range(0    ,				80	):
								if 0 <= i < 20:
										UpperCamelCase          =					(b & c) | ((~b) & d)
										UpperCamelCase          =					0X5A_827_999
								elif 20 <= i < 40:
										UpperCamelCase          =					b ^ c ^ d
										UpperCamelCase          =					0X6E_D9E_BA1
								elif 40 <= i < 60:
										UpperCamelCase          =					(b & c) | (b & d) | (c & d)
										UpperCamelCase          =					0X8F_1BB_CDC
								elif 60 <= i < 80:
										UpperCamelCase          =					b ^ c ^ d
										UpperCamelCase          =					0XCA_62C_1D6
								UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase          =					(
								    self.rotate(A_    ,				5	) + f + e + k + expanded_block[i] & 0XFF_FFF_FFF,
								    a,
								    self.rotate(A_    ,				30	),
								    c,
								    d,
								)
						UpperCamelCase          =					(
						    self.h[0] + a & 0XFF_FFF_FFF,
						    self.h[1] + b & 0XFF_FFF_FFF,
						    self.h[2] + c & 0XFF_FFF_FFF,
						    self.h[3] + d & 0XFF_FFF_FFF,
						    self.h[4] + e & 0XFF_FFF_FFF,
						)
				return ("{:08x}" * 5).format(*self.h	)






def 				A	( )       ->  Tuple:
		'''simple docstring'''

		UpperCamelCase          =					B'Test String'
		assert SHAaHash(lowercase			).final_hash() == hashlib.shaa(lowercase			).hexdigest()  # noqa: S324


def 				A	( )       ->  List[Any]:
		'''simple docstring'''

		UpperCamelCase          =					argparse.ArgumentParser(description='Process some strings or files'			)
		parser.add_argument(
		    '--string'   ,	dest='input_string'   ,	default='Hello World!! Welcome to Cryptography'   ,	help='Hash the string'   ,	)
		parser.add_argument('--file'   ,	dest='input_file'   ,	help='Hash contents of a file'			)
		UpperCamelCase          =					parser.parse_args()
		UpperCamelCase          =					args.input_string
		# In any case hash input should be a bytestring
		if args.input_file:
				with open(args.input_file   ,	'rb'			) as f:
						UpperCamelCase          =					f.read()
		else:
				UpperCamelCase          =					bytes(lowercase   ,	'utf-8'			)
		print(SHAaHash(lowercase			).final_hash()			)


if __name__ == "__main__":
					main()
					import doctest

					doctest.testmod()


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


_UpperCAmelCase :			Optional[Any]              =	{
    "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__":
					_UpperCAmelCase :			int              =	"hopper-medium-v2"
					_UpperCAmelCase :			Tuple              =	gym.make(env_name)

					_UpperCAmelCase :			Any              =	ValueGuidedRLPipeline.from_pretrained(
					    "bglick13/hopper-medium-v2-value-function-hor32",
					    env=env,
					)

					env.seed(0)
					_UpperCAmelCase :			Optional[Any]              =	env.reset()
					_UpperCAmelCase :			Union[str, Any]              =	0
					_UpperCAmelCase :			Union[str, Any]              =	0
					_UpperCAmelCase :			Dict              =	1_000
					_UpperCAmelCase :			Tuple              =	[obs.copy()]
					try:
										for t in tqdm.tqdm(range(T)):
															# call the policy
															_UpperCAmelCase :			int              =	pipeline(obs, planning_horizon=32)

															# execute action in environment
															_UpperCAmelCase       ,_UpperCAmelCase       ,_UpperCAmelCase       ,_UpperCAmelCase :			List[Any]              =	env.step(denorm_actions)
															_UpperCAmelCase :			int              =	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())

															_UpperCAmelCase :			Union[str, Any]              =	next_observation
					except KeyboardInterrupt:
										pass

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